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--
-- Table structure for table `sci_term_taxonomy`
--

CREATE TABLE `sci_term_taxonomy` (
  `term_taxonomy_id` bigint unsigned NOT NULL AUTO_INCREMENT,
  `term_id` bigint unsigned NOT NULL DEFAULT '0',
  `taxonomy` varchar(32) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL DEFAULT '',
  `description` longtext CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL,
  `parent` bigint unsigned NOT NULL DEFAULT '0',
  `count` bigint NOT NULL DEFAULT '0',
  PRIMARY KEY (`term_taxonomy_id`),
  UNIQUE KEY `term_id_taxonomy` (`term_id`,`taxonomy`),
  KEY `taxonomy` (`taxonomy`)
) ENGINE=InnoDB AUTO_INCREMENT=275 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `sci_term_taxonomy`
--

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--
-- Table structure for table `sci_users`
--

CREATE TABLE `sci_users` (
  `ID` bigint unsigned NOT NULL AUTO_INCREMENT,
  `user_login` varchar(60) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL DEFAULT '',
  `user_pass` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL DEFAULT '',
  `user_nicename` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL DEFAULT '',
  `user_email` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL DEFAULT '',
  `user_url` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL DEFAULT '',
  `user_registered` datetime NOT NULL DEFAULT '0000-00-00 00:00:00',
  `user_activation_key` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL DEFAULT '',
  `user_status` int NOT NULL DEFAULT '0',
  `display_name` varchar(250) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL DEFAULT '',
  PRIMARY KEY (`ID`),
  KEY `user_login_key` (`user_login`),
  KEY `user_nicename` (`user_nicename`),
  KEY `user_email` (`user_email`)
) ENGINE=InnoDB AUTO_INCREMENT=14 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `sci_users`
--

INSERT INTO `sci_users` VALUES (2,'cheryl','$P$Be6bN6QAulLv9qdLB2Wdl2OSTpcYTM.','cheryl','vansindata+cheryl@gmail.com','','2017-04-14 09:36:40','',0,'cheryl'),(3,'lillian','$P$B9KvLUm8ogKQIBSjBpMKUF1hucG13Q/','lillian','vansindata+lillian@gmail.com','','2017-06-30 08:17:24','',0,'lillian'),(4,'kate','$P$BFkUUgLNnm9nc7OQ10kqCIXxQYQ91l0','kate','vansindata+katekuen@gmail.com','','2017-08-09 09:03:17','',0,'kate'),(7,'katieyth','$P$Ba9wif3Lyue9MFMM5Pw.JHk2xBEQke.','katieyth','vansindata+katieyth@gmail.com','','2017-09-18 07:15:42','',0,'katieyth'),(9,'designer','$P$Bh68/8I1jLuscmFalLyeO6k107x7Ei0','designer','asdkslaf@asdlkfjalkdfja.com','','2020-09-16 02:45:54','1600224354:$P$Bi8iDaR.W4rON9OVc13ZW4HXQU/l9N0',0,'designer'),(10,'rebecca','$P$BL7v1aks83TKUZt8VlncRIF5xTOXCn.','rebecca','rebeccas@sted.tw','','2021-08-21 02:45:31','1629513931:$P$BTRZYGgiUFxFJtfA/du2k10yovVQUA.',0,'rebecca'),(11,'helper','$P$Bmy9K2xrqnO3KD3fqnxdcJ0sb55FWV.','helper','web@sted.tw','','2021-09-04 08:52:39','',0,'helper'),(12,'viewer','$P$BwrsJtoFCeOJvqPKf5oDT46UxzLw/Q0','viewer','conf2023@sted.tw','','2022-04-30 07:29:42','',0,'viewer'),(13,'Ben','$P$BPrC8paNu9KBLqyxbuTuDSWK.FDqVb/','ben','ben.wang@sted.tw','','2022-08-25 09:15:10','',0,'王 炳勛');

--
-- Table structure for table `speaker_company`
--

CREATE TABLE `speaker_company` (
  `company` varchar(99) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci NOT NULL,
  `company_short` varchar(99) NOT NULL COMMENT 'for agenda 主持人'
) ENGINE=InnoDB DEFAULT CHARSET=latin1;

--
-- Dumping data for table `speaker_company`
--


--
-- Table structure for table `speakers`
--

CREATE TABLE `speakers` (
  `id` smallint unsigned NOT NULL,
  `hide` tinyint unsigned NOT NULL DEFAULT '0',
  `sort` mediumint unsigned NOT NULL,
  `conf` varchar(10) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `name` varchar(60) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci NOT NULL COMMENT 'main name',
  `name2` varchar(60) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'nickname or english-name or other name',
  `anchor` varchar(100) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `talk_title` varchar(200) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci DEFAULT NULL,
  `talk_lang` varchar(200) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `can_playback` varchar(200) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `talkfile_link` text CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci,
  `company` varchar(255) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `position` varchar(255) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `photo` varchar(255) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'on datasci.tw',
  `left` varchar(9) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `top` varchar(9) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `front_photo` varchar(255) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'on google',
  `desc` text CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci COMMENT '講題描述',
  `desc_refined` text CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci,
  `me_desc` text CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci COMMENT '自述',
  `me_desc_refined` text CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci,
  `website` varchar(255) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `company2` varchar(255) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'Added in 2023, we display both English and Chinese simultaneously.',
  `position2` varchar(100) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'Added in 2023, we display both English and Chinese simultaneously.',
  `company_for_agenda` varchar(100) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `position_for_agenda` varchar(100) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `lecture_type` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'Added in 2024',
  `difficulty_level` varchar(100) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'The difficulty level of the speech content, Added in 2024',
  `post_id` varchar(100) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'Added in 2024',
  `talk_title2` varchar(100) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'Added in 2024,中文講題',
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb3 COLLATE=utf8mb3_unicode_ci;

--
-- Dumping data for table `speakers`
--

INSERT INTO `speakers` VALUES (1,1,9999,'主持人','郭秉宸','Benjamin Kuo','benjamin-kuo',NULL,'中文','','','台灣人工智慧學校','產學長','/img/speaker/35d7ecbe.png',NULL,NULL,NULL,'',NULL,'',NULL,NULL,'','','台灣人工智慧學校','校務長','🎊 開幕致詞','','10915',''),(2,0,9999,'致詞嘉賓','陳伶志','Ling-Jyh Chen','ling-jyh-chen',NULL,'中文','','','台灣人工智慧學校','執行長','/img/speaker/2d4d1967.png',NULL,NULL,NULL,'',NULL,'經歷：\r\n資訊服務處處長（2018/01/01 迄今）\r\n資訊服務處代理處長（2017/10/01-2017/12/31）\r\n研究員，資訊科學研究所 （2017/12 迄今）\r\n副研究員，資訊科學研究所 （2011/01–2017/12）\r\n助研究員，資訊科學研究所 （2005/09–2011/01）\r\n\r\n學歷：\r\n博士，資訊科學系，加州大學洛杉磯分校，美國 （2003/01–2005/06）\r\n碩士，資訊科學系，加州大學洛杉磯分校，美國 （2001/09–2002/12）\r\n大學，資訊教育系，國立臺灣師範大學，中華民國 （1993/09–1998/06）','<section>\r\n  <p>▍簡介</p>\r\n  <ul>\r\n    <li>財團法人台灣人工智慧學校基金會執行長</li>\r\n    <li>中央研究院資訊科學所研究員</li>\r\n    <li>中央研究院資訊服務處處長</li>\r\n  </ul>\r\n</section>\r\n\r\n<section>\r\n  <p>▍經歷</p>\r\n  <ul>\r\n    <li>中央研究院資訊服務處處長（2018/01 迄今）</li>\r\n    <li>中央研究院資訊科學研究所研究員（2017/12 迄今）</li>\r\n    <li>行政院災害防救專家諮詢委員（2024/08 迄今）</li>\r\n    <li>國際科學與技術資料委員會中華民國委員會主任委員（2025/03 迄今）</li>\r\n    <li>國際科學與技術資料委員會中華民國委員會執行秘書（2019/03 – 2025/03）</li>\r\n    <li>太平洋鄰里協會中華民國委員會委員（2019/01 迄今）</li>\r\n    <li>國立臺灣師範大學資訊工程系兼任教授（2018/08 迄今）</li>\r\n    <li>台灣人工智慧學校策略長（2024/06–2025/01）</li>\r\n    <li>科技政策諮詢專家室資通訊群組共同召集人（2024/06–2024/12）</li>\r\n    <li>科技政策諮詢專家室資通訊群組領域專家（2023/03–2024/06）</li>\r\n    <li>教育部顧問（2021/01–2022/12）</li>\r\n    <li>太平洋鄰里協會執行長（2017/10–2019/12）</li>\r\n    <li>中央研究院資訊服務處代理處長（2017/10–2017/12）</li>\r\n    <li>中央研究院資訊科學研究所副研究員（2011/01–2017/12）</li>\r\n    <li>中央研究院資訊科學研究所助研究員（2005/09–2011/01）</li>\r\n  </ul>\r\n</section>\r\n',NULL,'','','台灣人工智慧學校','執行長','🎊 開幕致詞','','10916',''),(3,0,9999,'致詞嘉賓','陳炳宇',NULL,'speaker-3',NULL,'中文','','','國家科學及技術委員會 ','副主委','/img/speaker/ca5c6bd8.png',NULL,NULL,NULL,'',NULL,'國家科學及技術委員會副主任委員\n主要研究領域\n• 人機互動\n• 電腦圖學\n• 視訊及影像處理\n• 創新創業教育','<p>\r\n  國家科學及技術委員會副主任委員\r\n</p>\r\n<p><strong>主要研究領域：</strong></p>\r\n<ul>\r\n  <li>人機互動</li>\r\n  <li>電腦圖學</li>\r\n  <li>視訊及影像處理</li>\r\n  <li>創新\r\n',NULL,'','','國家科學及技術委員會','副主委','🎊 開幕致詞','','10917',''),(4,0,9999,'致詞嘉賓','林宜敬',NULL,'speaker-4',NULL,'中文','','','數位發展部 ','次長','/img/speaker/ea31451e.png',NULL,NULL,NULL,'',NULL,'學歷\n1995 美國布朗大學電腦科學博士\n1987 臺灣大學資訊工程系學士\n經歷\n2002-2024 艾爾科技創辦人兼執行長\n2021-2023 印刻文學生活誌專欄作家\n1999-2001 趨勢科技新產品研發部協理\n1996-1999 華通電腦資訊工程部副理\n1995-1996 美國 IBM 華生研究中心博士後研究員','<p><strong>學歷：</strong></p>\r\n<ul>\r\n  <li>1995 美國布朗大學電腦科學博士</li>\r\n  <li>1987 臺灣大學資訊工程系學士</li>\r\n</ul>\r\n\r\n<p><strong>經歷：</strong></p>\r\n<ul>\r\n  <li>2002–2024 艾爾科技創辦人兼執行長</li>\r\n  <li>2021–2023 印刻文學生活誌專欄作家</li>\r\n  <li>1999–2001 趨勢科技新產品研發部協理</li>\r\n  <li>1996–1999 華通電腦資訊工程部副理</li>\r\n  <li>1995–1996 美國 IBM 華生研究中心博士後研究員</li>\r\n</ul>\r\n',NULL,'','','數位發展部','次長','🎊 開幕致詞','','10918',''),(5,0,9999,'AI','黃瀚萱','Bor-Sung Liang','bor-sung-liang',NULL,'中文','','','中研院資訊科學研究所','副研究員','/img/speaker/f9521fcf.png',NULL,NULL,NULL,'',NULL,'Dr. Huang\'\'s research focuses on the investigation of computational approaches for modeling the interplay between figurative language processing and human knowledge representation, leading the pioneering work in Chinese discourse analysis. His works have been published in SCI/SSCI journals and top-tier conferences in the venues of artificial intelligence, computational linguistics, natural language processing, and information retrieval. Prior to joining the Institute of Information Science, Academia Sinica, Dr. Huang was an assistant professor in the Department of Computer Science at the National Chengchi University. His award and honors include the Honorable Mention of Doctoral Dissertation Award of ACLCLP in 2014 and the Honorable Mention of Master Thesis Award of ACLCLP in 2008. He served as the registration chair of TAAI 2017, the publication chair of ROCLING 2020, and as PC members of representative conferences in computational linguistics including ACL, COLING, EMNLP, and NAACL. He was one of organizers of FinNum Task at NTCIR-2014 and FinNLP Workshop at IJCAI 2019.',NULL,NULL,'','','中研院資訊科學研究所','副研究員','','','10919','開源 LLM 版圖導航：如何為應用選擇合適的模型'),(6,1,9999,'PANEL','侯宜秀','Isabel Hou','isabel-hou',NULL,'中文','','','財團法人台灣人工智慧學校基金會','秘書長','/img/speaker/41ebeef3.png',NULL,NULL,NULL,'',NULL,'律師，專注於創新科技、開放資料、開放政府等數位治理議題及相關法律規範。2012 年以來持續參與 g0v 公民科技社群，從中習得「揪團打怪」技能：多方協作推動社會創新。\r\n2017 年協助設立台灣人工智慧學校基金會，2021 年起擔任秘書長，推動課程轉型及開源 AI 平台「風火輪計畫」。\r\n2020-2022 年擔任立法院開放國會委員會民間委員，推動完成台灣立法院首份「開放國會行動方案」。近來與台灣公民社群夥伴協作推動「數位公民素養」行動計畫作為台灣新世代社會基礎建設。','<p>律師，專注於創新科技、開放資料、開放政府等數位治理議題及相關法律規範。2012 年以來持續參與 g0v 公民科技社群，從中習得「揪團打怪」技能：多方協作推動社會創新。</p>\r\n<p>2017 年協助設立台灣人工智慧學校基金會，2021 年起擔任秘書長，推動課程轉型及開源 AI 平台「風火輪計畫」。</p>\r\n<p>2020-2022 年擔任立法院開放國會委員會民間委員，推動完成台灣立法院首份「開放國會行動方案」。近來與台灣公民社群夥伴協作推動「數位公民素養」行動計畫作為台灣新世代社會基礎建設。</p>',NULL,'','','財團法人台灣人工智慧學校基金會','秘書長','開源模型論壇','','10920','開源模型論壇'),(7,0,9999,'PANEL','洪士灝','Shih-Hao Hung','shih-hao-hung',NULL,'中文','','','臺大資工系','教授','/img/speaker/bb2d9300.png',NULL,NULL,NULL,'',NULL,'臺灣大學資訊工程學系教授\n研究專長: 電腦應用與架構相互最佳化、計算機架構與平行處理、計算機效能評估與最佳化、嵌入式系統設計\n\n','<p>臺灣大學資訊工程學系教授</p>\r\n<p>研究專長: 電腦應用與架構相互最佳化、計算機架構與平行處理、計算機效能評估與最佳化、嵌入式系統設計</p>\r\n',NULL,'','','臺大資工系','教授','開源模型論壇','','10921','開源模型論壇'),(8,0,9999,'PANEL','蔡祈岩','Rock TSAI','rock-tsai',NULL,'中文','','','台灣大哥大 ','資訊長','/img/speaker/3bbf7d27.png',NULL,NULL,NULL,'',NULL,'Dr. Rock Tsai, holding a Ph.D. in Management Science and Engineering from Central South University, China, currently serves as Chief Information Officer at Taiwan Mobile and Chairman of the Information Management Association (IMA). He started programming in elementary school and took on freelance projects in junior high. In the 1990s, as a freshman at National Yang Ming Chiao Tung University’s Department of Computer Science, he developed a game called “Face to Face,” which took Asia by storm, selling close to 100,000 copies. \nDr. Tsai has previously served as Senior VP at HSBC Bank (China), Group Chief Information Officer at Sinyi Realty, and Head of Technology at DBS Bank (Taiwan). He received the awards of “Most Valuable CIO in China” in 2011, “Distinguished CIO in China” in 2012, “Outstanding CIO in Taiwan” in 2017, and IMA’s “Outstanding Information Director” in 2022.  \nHe joined Taiwan Mobile in February 2022, taking on the significant responsibility of managing the group’s IT transformation. ','<p>Dr. Rock Tsai, holding a Ph.D. in Management Science and Engineering from Central South University, China, currently serves as Chief Information Officer at Taiwan Mobile and Chairman of the Information Management Association (IMA).</p>\r\n<p>He started programming in elementary school and took on freelance projects in junior high. In the 1990s, as a freshman at National Yang Ming Chiao Tung University’s Department of Computer Science, he developed a game called “Face to Face,” which took Asia by storm, selling close to 100,000 copies. </p>\r\n<p>Dr. Tsai has previously served as Senior VP at HSBC Bank (China), Group Chief Information Officer at Sinyi Realty, and Head of Technology at DBS Bank (Taiwan). He received the awards of “Most Valuable CIO in China” in 2011, “Distinguished CIO in China” in 2012, “Outstanding CIO in Taiwan” in 2017, and IMA’s “Outstanding Information Director” in 2022.</p>  \r\n<p>He joined Taiwan Mobile in February 2022, taking on the significant responsibility of managing the group’s IT transformation.</p> ',NULL,'','','台灣大哥大 ','資訊長','開源模型論壇','','10922','開源模型論壇'),(9,0,9999,'PANEL','許永真',NULL,'speaker-9',NULL,'中文','','','長庚大學智慧運算學院','院長','/img/speaker/ed0e1a3c.png',NULL,NULL,NULL,'',NULL,'許永真教授現任於臺大資訊工程學系暨網路與多媒體研究所，曾任臺大資訊系主任。許教授致力於人工智慧研究領域逾三十年，研究主題含智慧型多代理人、資料分析、知識建構、常識運算、感知服務、及智慧型物聯網技術。 自2012年起，許教授擔任Intel台大創新研究中心主任，積極進行跨國、跨校、跨領域、跨產學合作，研發物聯網於智慧農業、智慧運輸、與智慧家庭之相關技術。2016年在台大、科技部、英特爾實驗室、台達電、與研華共同支持下，開始進行擴充人機互動於未來智慧製造之研究。以「臺大智慧聯網創新研究中心」的新標幟，成長發展為物聯網、人工智慧、與人機互動相關研究的重鎮。\n許教授活躍於國際學術領域，曾擔任台灣人工智慧學會理事長，TAAI、IEEE iThings、AAAI SocialNLP Workshop等國際會議的議程主席; 以及Intelligent Data Analysis, Service-Oriented Computing and Applications, JISE等國際期刊之編輯委員。許教授目前於資訊系開授人工智慧相關課程，並合授網媒所「物聯網產品設計與創新」、創新設計學院「智齡設計—老人科技福祉專題」，透過跨領域合作來激發學生創新思考與前瞻技術實現。','<p>許永真教授現任於臺大資訊工程學系暨網路與多媒體研究所，曾任臺大資訊系主任。許教授致力於人工智慧研究領域逾三十年，研究主題含智慧型多代理人、資料分析、知識建構、常識運算、感知服務、及智慧型物聯網技術。</p>\r\n\r\n<p>自2012年起，許教授擔任Intel台大創新研究中心主任，積極進行跨國、跨校、跨領域、跨產學合作，研發物聯網於智慧農業、智慧運輸、與智慧家庭之相關技術。2016年在台大、科技部、英特爾實驗室、台達電、與研華共同支持下，開始進行擴充人機互動於未來智慧製造之研究。以「臺大智慧聯網創新研究中心」的新標幟，成長發展為物聯網、人工智慧、與人機互動相關研究的重鎮。</p>\r\n\r\n<p>許教授活躍於國際學術領域，曾擔任台灣人工智慧學會理事長，TAAI、IEEE iThings、AAAI SocialNLP Workshop等國際會議的議程主席；以及Intelligent Data Analysis, Service-Oriented Computing and Applications, JISE等國際期刊之編輯委員。</p>\r\n\r\n<p>許教授目前於資訊系開授人工智慧相關課程，並合授網媒所「物聯網產品設計與創新」、創新設計學院「智齡設計—老人科技福祉專題」，透過跨領域合作來激發學生創新思考與前瞻技術實現。</p>\r\n',NULL,'','','長庚大學智慧運算學院','院長','開源模型論壇','','10923','開源模型論壇'),(10,1,9999,'AI','TBD',NULL,'speaker-10',NULL,'中文','','','','',NULL,NULL,NULL,NULL,'',NULL,'',NULL,NULL,'','',NULL,NULL,'','','10924',''),(11,1,9999,'AI','TBD',NULL,'speaker-11',NULL,'中文','','','','',NULL,NULL,NULL,NULL,'',NULL,'',NULL,NULL,'','',NULL,NULL,'','','10925',''),(12,1,9999,'AI','TBD',NULL,'speaker-12',NULL,'中文','','','','',NULL,NULL,NULL,NULL,'',NULL,'',NULL,NULL,'','',NULL,NULL,'','','10926',''),(13,0,9999,'AIK','梁伯嵩',NULL,'speaker-13',NULL,'中文','','','聯發科技 企業策略與前瞻技術','資深處長','/img/speaker/18b4ca96.png',NULL,NULL,NULL,'AI 發展迅速，大型語言模型（LLM） 的演進，展現傑出的內容生成能力。但AI 計算量龐大，讓全世界競相建置運算資源，而讓世界半導體的需求高速成長。在此，我們討論大型語言模型的演進。尤其 AI 運算規模擴大規則 (Scaling Law)範圍，已由訓練時期運算 (Pre-Training & Post-Training)，進展到推理時期運算 (Test-Time Compute)。蒸餾模型 (Distilled Model) 可顯著降低運算又保持相當的AI性能，搭配開源模型的趨勢，對邊緣設備的AI推理運算有相當的助益。在未來AI 技術成長主軸，將會討論 Agentic AI 、Physical AI的發展，以及對AI產業發展的展望。',NULL,'梁伯嵩博士現為 聯發科技 企業策略與前瞻技術 資深處長，與聯發科技教育基金會董事。兼任 國立臺灣大學 電機資訊學院 資訊工程系 與 重點科技研究學院 合聘之 客座教授，以及 國立陽明交通大學 電機學院 客座教授、產學創新研究學院 教授級專業技術人員。並擔任 國際電機電子工程學會 中華民國分會  (IEEE Taipei section) 理事。\n\n梁博士於 國立交通大學 電子研究所 獲得博士學位，並於 國立臺灣大學 管理學院 EMBA 商學組 畢業。曾獲得 中華民國十大傑出青年 (科技發展類)、三度獲得 經濟部智慧財產局 國家發明創作獎 (發明獎一金二銀) 、經濟部技術處 產業科技發展獎-傑出青年創新獎、資訊月傑出資訊人才獎、李國鼎青年研究獎等重要獎項。','<p>梁伯嵩博士現為 聯發科技 企業策略與前瞻技術 資深處長，與聯發科技教育基金會董事。兼任 國立臺灣大學 電機資訊學院 資訊工程系 與 重點科技研究學院 合聘之 客座教授，以及 國立陽明交通大學 電機學院 客座教授、產學創新研究學院 教授級專業技術人員。並擔任 國際電機電子工程學會 中華民國分會  (IEEE Taipei section) 理事。</p>\r\n\r\n<p>梁博士於 國立交通大學 電子研究所 獲得博士學位，並於 國立臺灣大學 管理學院 EMBA 商學組 畢業。曾獲得 中華民國十大傑出青年 (科技發展類)、三度獲得 經濟部智慧財產局 國家發明創作獎 (發明獎一金二銀) 、經濟部技術處 產業科技發展獎-傑出青年創新獎、資訊月傑出資訊人才獎、李國鼎青年研究獎等重要獎項。</p>',NULL,'','','聯發科技 企業策略與前瞻技術','資深處長','KEYNOTE','','10927','AI 運算的衝擊及展望'),(14,0,9999,'AI','林旅強',NULL,'speaker-14',NULL,'中文','','','零一萬物開源','前負責人','/img/speaker/d0aabc21.png',NULL,NULL,NULL,'',NULL,'林旅強｜以開源佈道為志業，以開放、自由、共享、創新為信仰。現負責華為雲 AI 開發者生態發展；曾任華為開發者社區運營總監。曾於中央研究院自由軟體鑄造場 (OSSF) 投入開源授權研究和校園社群推廣工作。',NULL,NULL,'','','零一萬物開源','前負責人','','','10928','中國的 AI 開源生態系現狀'),(15,0,9999,'AI','蔡政霖',NULL,'speaker-15',NULL,'中文','','','台灣人工智慧學校','技術處副組長','/img/speaker/7df5ff29.png',NULL,NULL,NULL,'',NULL,'現任財團法人台灣人工智慧學校技術發展處副組長，是一位經驗豐富的 AI 工程師，專精於生成式人工智慧領域的應用。他的專業涵蓋了大型語言模型 (LLM) 以及提升效率的自動化平台。生成式 AI 的實際應用方面擁有深厚的經驗，曾多次應邀至學術界與產業夥伴分享其專業知識，例如在 Google、電通台灣、廣達電腦、統一超商、中華電信電信學院等知名機構進行交流與合作。他也積極在各類研討會與工作坊分享，涵蓋了生成式 AI 工具的應用、AI 技術的整合運用。致力於推廣生成式 AI 技術的普及與發展，並關注開源技術應用。憑藉其專業知識與豐富經驗，在推動生成式 AI 技術的創新與應用上扮演著重要的角色。',NULL,NULL,'','','台灣人工智慧學校','技術處副組長','','','10929','生成式 AI 的開源工具應用'),(16,0,9999,'AI','邵懿文','Shao, Yi-Wen','shao-yi-wen',NULL,'中文','','','台灣電通','策略創新長','/img/speaker/8bda2aba.png',NULL,NULL,NULL,'',NULL,'工作經歷\n\n目前任職於電通安吉斯集團，成立顧問事業-商業加速中心，協助客戶數位轉型與品牌轉型的顧顧問服務。 曾服務於安索帕數位行銷公司 (電通安吉斯集團旗下品牌公司)、意識形態廣告公司、傳立媒體、 奧美廣告、與超級電視臺。25年以上跨媒體、網路、社群行銷, 數據與技術整合行銷傳播經驗。 2000年加入安索帕，正式投入網路行銷的世界， 2004年起擔任執行副總負責臺灣區公司的公司營運，於2007年升任臺灣區董事總經理職務。 2013年8月，升任集團職務擔擔任數位長，負責電通安吉斯集團臺灣數位策略發展及布局。 2019年起擔任天下創新學院數位轉型導師。\n\n個人獎項肯定\n\n榮獲《經理人月刊》主辦之「第五屆100 MVP經理人-數位策略Digital Strategy」、2013年度傑出廣告專業經理人獎、2012年動腦雜誌和臺灣廣告主協會主辦之「2012行銷傳播傑出貢獻獎」以及獲頒2012「年度傑出網路行銷公司經營者」。','<p><strong>工作經歷</strong></p>\r\n<p>目前任職於電通安吉斯集團，成立顧問事業－商業加速中心，協助客戶數位轉型與品牌轉型的顧問服務。曾服務於安索帕數位行銷公司（電通安吉斯集團旗下品牌公司）、意識形態廣告公司、傳立媒體、奧美廣告、與超級電視臺。擁有 25 年以上跨媒體、網路、社群行銷、數據與技術整合行銷傳播經驗。</p>\r\n\r\n<p>2000 年加入安索帕，正式投入網路行銷的世界；2004 年起擔任執行副總，負責臺灣區公司營運；於 2007 年升任臺灣區董事總經理職務。2013 年 8 月升任集團職務，擔任數位長，負責電通安吉斯集團臺灣數位策略發展及布局。2019 年起擔任天下創新學院數位轉型導師。</p>\r\n\r\n<p><strong>個人獎項肯定</strong></p>\r\n<p>榮獲《經理人月刊》主辦之「第五屆 100 MVP 經理人－數位策略 Digital Strategy」、2013 年度傑出廣告專業經理人獎、2012 年動腦雜誌和臺灣廣告主協會主辦之「2012 行銷傳播傑出貢獻獎」，以及獲頒 2012「年度傑出網路行銷公司經營者」。</p>\r\n',NULL,'','','台灣電通','策略創新長','','','10930','行銷人的 GenAI 必修課'),(17,0,9999,'AI','侯宜秀','Isabel Hou','isabel-hou-2',NULL,'中文','','','財團法人台灣人工智慧學校基金會','秘書長','/img/speaker/2d9bce16.png',NULL,NULL,NULL,'',NULL,'律師，專注於創新科技、開放資料、開放政府等數位治理議題及相關法律規範。2012 年以來持續參與 g0v 公民科技社群，從中習得「揪團打怪」技能：多方協作推動社會創新。\n\n2017 年協助設立台灣人工智慧學校基金會，2021 年起擔任秘書長，推動課程轉型及開源 AI 平台「風火輪計畫」。\n\n2020-2022 年擔任立法院開放國會委員會民間委員，推動完成台灣立法院首份「開放國會行動方案」。近來與台灣公民社群夥伴協作推動「數位公民素養」行動計畫作為台灣新世代社會基礎建設。',NULL,NULL,'','','財團法人台灣人工智慧學校基金會','秘書長','','','10970','開源與 AI 治理： 負責任的 AI 開發與應用'),(18,0,9999,'AI','蔡明順','Richie Tsai','richie-tsai',NULL,'中文','','','台灣人工智慧學校','校務長','/img/speaker/7fc093cf.png',NULL,NULL,NULL,'',NULL,'Richie Tsai is the Provost of the Taiwan AI Academy, Taiwan\'s leading institution in AI education. He oversees the Academy\'s operations, consulting services, and research development, transforming it into a dynamic platform for collaboration across AI disciplines and sectors. Taiwan AI Academy educates over 11,000 AI talents from 2,200 organizations in 15 industries. \nBefore joining Taiwan AI Academy, Tsai served as Senior Director for SAP Greater China, overseeing market strategy, technical services, and business operations. His previous roles include senior roles at Oracle and  at Teradata. With over 25 years of experience in emerging information technology fields such as artificial intelligence, data science, cloud services, and digital transformation, Richie is an AI evangelist with deep expertise in information technology and ecosystem development.\n\n現職：\n- 台灣人工智慧學校校務長\n- 國科會Taiwan AI 卓越中心策略委員\n- 中華民國人工智慧學會理事\n\n經歷:\n- 台灣人工智慧學校營運長/ 代理執行長\n- SAP 德商思愛普 大中華區資深副總經理\n- Oracle 美商甲骨文 應用軟體部副總經理\n- Teradata 美商天睿資訊系統 資深協理\n\n學歷:\n國立清華大學工學博士候選人','<p>Richie Tsai is the Provost of the Taiwan AI Academy, Taiwan\'s leading institution in AI education. He oversees the Academy\'s operations, consulting services, and research development, transforming it into a dynamic platform for collaboration across AI disciplines and sectors. Taiwan AI Academy educates over 11,000 AI talents from 2,200 organizations in 15 industries. \r\nBefore joining Taiwan AI Academy, Tsai served as Senior Director for SAP Greater China, overseeing market strategy, technical services, and business operations. His previous roles include senior roles at Oracle and  at Teradata. With over 25 years of experience in emerging information technology fields such as artificial intelligence, data science, cloud services, and digital transformation, Richie is an AI evangelist with deep expertise in information technology and ecosystem development.</p>\r\n<p> <strong>現職</strong></p>\r\n<ul><li> 台灣人工智慧學校校務長</li><li> 國科會 Taiwan AI 卓越中心策略委員</li><li> 中華民國人工智慧學會理事</li></ul>\r\n<p> <strong>經歷</strong></p>\r\n<ul><li> 台灣人工智慧學校營運長 / 代理執行長</li><li>SAP 德商思愛普 大中華區資深副總經理</li><li>Oracle 美商甲骨文 應用軟體部副總經理</li><li>Teradata 美商天睿資訊系統 資深協理</li></ul>\r\n<p><strong>學歷</strong></p>\r\n<ul><li> 國立清華大學工學博士候選人</li></ul>',NULL,'','','台灣人工智慧學校','校務長','','','10973','開源趨勢下的 AI 人才認證計畫');

--
-- Table structure for table `speakers_2023`
--

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  `conf` varchar(10) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL,
  `name` varchar(60) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci NOT NULL COMMENT 'main name',
  `name2` varchar(60) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'nickname or english-name or other name',
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  `front_photo` varchar(255) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'on google',
  `desc` text CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci COMMENT '講題描述',
  `desc_refined` text CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci,
  `me_desc` text CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci COMMENT '自述',
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  `company2` varchar(255) CHARACTER SET utf8mb3 COLLATE utf8mb3_unicode_ci DEFAULT NULL COMMENT 'Added in 2023, we display both English and Chinese simultaneously.',
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INSERT INTO `speakers_2023` VALUES (1,1,9999,'致詞嘉賓','廖俊智','James C. Liao','james-c-liao','','中文','no','簡報1','Academia Sinica','President ','/img/speaker/35d7ecbe.jpg',NULL,NULL,NULL,'',NULL,'','',NULL,'','','Academia Sinica','院長','Welcome & Opening Remarks'),(2,1,9999,'致詞嘉賓','吳政忠','Tsung-Tsong Wu','tsung-tsong-wu','','中文','no','簡報2','National Science and Technology Council','Minister','/img/speaker/2d4d1967.jpg',NULL,NULL,NULL,'',NULL,'','',NULL,'','','NSTC\r','主委',NULL),(3,0,9999,'AIK','林百里','Barry Lam','barry-lam','Prompting The Future: Transforming Medicine through Generative AI','中文','yes','X','Quanta Computer Inc.','Chairman','/img/speaker/ca5c6bd8.png',NULL,NULL,NULL,'Medicine, a discipline rooted in centuries of knowledge and practice, is  now at the brink of one of its most transformative phases, spurred by the  rise of generative AI. This speech delves into this impending revolution,  shedding light on how artificial intelligence is poised to reshape our  healthcare paradigms from the perspective of Quanta Computer, a  leading AI platform provider for smart medicine and digital health. From  AI-driven diagnostics that predict with unprecedented accuracy to  personalized treatments tailored to individual genetic imprints, we are  witnessing the dawn of a new era. This discourse not only celebrates the  remarkable innovations that AI promises but also engages in a critical  examination of the challenges and ethical dilemmas it presents. As we  navigate this uncharted territory, the speech emphasizes the need for  synergy between human insight and machine intelligence, ensuring that  the future of medicine is not just technologically advanced but also',NULL,'Mr. Barry Lam, the founder and CEO of Quanta Group, is a guiding figure in the IT industry. With a master\'s degree in Electrical Engineering from National Taiwan University, he has stood at the forefront of technological waves for decades, leading industry transformation.   From the 1980s to the 1990s, Mr. Lam steered Quanta\'s focus towards computer hardware technology, engaging in in-depth research and innovation. As cloud technology emerged in the mid-2000s, the company innovatively developed hardware and software solutions, continuously exploring new territories. In recent years, his vision extended to artificial intelligence (AI), 5G technology, and next-gen metaverse computing platforms, actively driving advancements in smart manufacturing, transportation, healthcare, and other emerging fields, thereby promoting a new wave of digital transformation for businesses.  Beyond excelling in the business domain, Mr. Lam founded the Quanta Culture and Education Foundation, championing the idea of cultural enrichment for all. Through the \"\"Immersed in Creativity\"\" project, he introduced art to campuses, seamlessly integrating art education into students\' daily lives. Simultaneously, the foundation\'s \"\"Immersed in AI\"\" project deeply engages with education in preparation for Taiwan\'s embrace of the AI era, injecting new vitality. These efforts underscore his sense of social responsibility and dedication to education.','<p>Mr. Barry Lam, the founder and CEO of Quanta Group, is a guiding figure in the IT industry. With a master\\\'s degree in Electrical Engineering from National Taiwan University, he has stood at the forefront of technological waves for decades, leading industry transformation.</p>\r\n\r\n<p>From the 1980s to the 1990s, Mr. Lam steered Quanta\\\'s focus towards computer hardware technology, engaging in in-depth research and innovation. As cloud technology emerged in the mid-2000s, the company innovatively developed hardware and software solutions, continuously exploring new territories. In recent years, his vision extended to artificial intelligence (AI), 5G technology, and next-gen metaverse computing platforms, actively driving advancements in smart manufacturing, transportation, healthcare, and other emerging fields, thereby promoting a new wave of digital transformation for businesses.</p>\r\n\r\n<p>Beyond excelling in the business domain, Mr. Lam founded the Quanta Culture and Education Foundation, championing the idea of cultural enrichment for all. Through the\\\"\\\"Immersed in Creativity\\\"\\\"project, he introduced art to campuses, seamlessly integrating art education into students\\\' daily lives. Simultaneously, the foundation\\\'s\\\"\\\"Immersed in AI\\\"\\\"project deeply engages with education in preparation for Taiwan\\\'s embrace of the AI era, injecting new vitality. These efforts underscore his sense of social responsibility and dedication to education.</p>',NULL,'','','錄影','董事長','KEYNOTE '),(4,0,9999,'AIK','紀懷新','Ed H. Chi','ed-h-chi','The LLM Revolution: Implications from Chatbots and Tool-use to Reasoning','中文','no','X','Google DeepMind','Distinguished Scientist','/img/speaker/ea31451e.jpg',NULL,NULL,NULL,'The LLM (Large Language Model) Revolution: Implications from Chatbots and Tool-use to Reasoning  Deep learning is a shock to our field in many ways, yet still many of us were surprised at the incredible performance of Large Language Models (LLMs). LLM uses new deep learning techniques with massively large data sets to understand, predict, summarize, and generate new content.  LLMs like ChatGPT and Bard have seen a dramatic increase in their capabilities---generating text that is nearly indistinguishable from human-written text, translating languages with amazing accuracy, and answering your questions in an informative way. This has led to a number of exciting research directions for chatbots, tool-use, and reasoning:   - Chatbots: LLM chatbots that are more engaging and informative than traditional chatbots. First, LLMs can understand the context of a conversation better than ever before, allowing them to provide more relevant and helpful responses.  Second, LLMs enable more engaging conversations than traditional chatbots, because they can understand the nuances of human language and respond in a more natural way. For example, LLMs can make jokes, ask questions, and provide feedback.  Finally, because LLM chatbots can hold conversations on a wide range of topics, they can eventually learn and adapt to the user\'s individual preferences.     - Tool-use, Retrieval Augmentation and Multi-modality: LLMs are also being used to create tools that help us with everyday tasks. For example, LLMs can be used to generate code, write emails, and even create presentations.  Beyond human-like responses in Chatbots, later LLM innovators realized LLM’s ability to incorporate tool-use, including calling search and recommendation engines, which means that they could effectively become human assistants in synthesizing summaries from web search and recommendation results.  Tool-use integration have also enabled multimodal capabilities, which means that the chatbot can produce text, speech, images, and video.   - Reasoning: LLMs are also being used to develop new AI systems that can reason and solve problems. Using Chain-of-Thought approaches, we have shown LLM\'s ability to break down problems, and then use logical reasoning to solve each of these smaller problems, and then combine the solutions to reach the final answer.  LLMs can answer common-sense questions by using their knowledge of the world to reason about the problem, and then use their language skills to generate text that is both creative and informative.   In this talk, I will cover recent advances in these 3 major areas, attempting to draw connections between them, and paint a picture of where major advances might still come from.  While the LLM revolution is still in its early stages, it has the potential to revolutionize the way we interact with AI, and make a significant impact on our lives.','<p>The LLM (Large Language Model) Revolution: Implications from Chatbots and Tool-use to Reasoning</p>\r\n<p>Deep learning is a shock to our field in many ways, yet still many of us were surprised at the incredible performance of Large Language Models (LLMs). LLM uses new deep learning techniques with massively large data sets to understand, predict, summarize, and generate new content.  LLMs like ChatGPT and Bard have seen a dramatic increase in their capabilities---generating text that is nearly indistinguishable from human-written text, translating languages with amazing accuracy, and answering your questions in an informative way. This has led to a number of exciting research directions for chatbots, tool-use, and reasoning:</p>\r\n\r\n\r\n<p>- Chatbots: LLM chatbots that are more engaging and informative than traditional chatbots. First, LLMs can understand the context of a conversation better than ever before, allowing them to provide more relevant and helpful responses.  Second, LLMs enable more engaging conversations than traditional chatbots, because they can understand the nuances of human language and respond in a more natural way. For example, LLMs can make jokes, ask questions, and provide feedback.  Finally, because LLM chatbots can hold conversations on a wide range of topics, they can eventually learn and adapt to the user\'s individual preferences.  </p>\r\n\r\n\r\n<p>- Tool-use, Retrieval Augmentation and Multi-modality: LLMs are also being used to create tools that help us with everyday tasks. For example, LLMs can be used to generate code, write emails, and even create presentations.  Beyond human-like responses in Chatbots, later LLM innovators realized LLM’s ability to incorporate tool-use, including calling search and recommendation engines, which means that they could effectively become human assistants in synthesizing summaries from web search and recommendation results.  Tool-use integration have also enabled multimodal capabilities, which means that the chatbot can produce text, speech, images, and video.</p>\r\n\r\n\r\n<p>- Reasoning: LLMs are also being used to develop new AI systems that can reason and solve problems. Using Chain-of-Thought approaches, we have shown LLM\'s ability to break down problems, and then use logical reasoning to solve each of these smaller problems, and then combine the solutions to reach the final answer.  LLMs can answer common-sense questions by using their knowledge of the world to reason about the problem, and then use their language skills to generate text that is both creative and informative.</p>\r\n\r\n\r\n<p>In this talk, I will cover recent advances in these 3 major areas, attempting to draw connections between them, and paint a picture of where major advances might still come from.  While the LLM revolution is still in its early stages, it has the potential to revolutionize the way we interact with AI, and make a significant impact on our lives.</p>','Ed H. Chi is a Distinguished Scientist at Google DeepMind, leading machine learning research teams working on large language models (LaMDA/Bard), neural recommendations, and reliable machine learning. With 39 patents and ~200 research articles, he is also known for research on user behavior in web and social media.  As the Research Platform Lead, he helped launched Bard, a conversational AI experiment, and delivered significant improvements for YouTube, News, Ads, Google Play Store at Google with >720 product improvements since 2013.   Prior to Google, he was Area Manager and Principal Scientist at Xerox Palo Alto Research Center\'s Augmented Social Cognition Group in researching how social computing systems help groups of people to remember, think and reason. Ed earned his 3 degrees (B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota. Inducted as an ACM Fellow and into the CHI Academy, he also received a 20-year Test of Time award for research in information visualization. He has been featured and quoted in the press, including the Economist, Time Magazine, LA Times, and the Associated Press.  An avid golfer, swimmer, photographer and snowboarder in his spare time, he also has a blackbelt in Taekwondo.','<p>Ed H. Chi is a Distinguished Scientist at Google DeepMind, leading machine learning research teams working on large language models (LaMDA/Bard), neural recommendations, and reliable machine learning. With 39 patents and ~200 research articles, he is also known for research on user behavior in web and social media.  As the Research Platform Lead, he helped launched Bard, a conversational AI experiment, and delivered significant improvements for YouTube, News, Ads, Google Play Store at Google with >720 product improvements since 2013. </p>\r\n\r\n<p>Prior to Google, he was Area Manager and Principal Scientist at Xerox Palo Alto Research Center\'s Augmented Social Cognition Group in researching how social computing systems help groups of people to remember, think and reason. Ed earned his 3 degrees (B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota. Inducted as an ACM Fellow and into the CHI Academy, he also received a 20-year Test of Time award for research in information visualization. He has been featured and quoted in the press, including the Economist, Time Magazine, LA Times, and the Associated Press.  An avid golfer, swimmer, photographer and snowboarder in his spare time, he also has a blackbelt in Taekwondo.</p>','https://Edchi.net','','','Google DeepMind','Distinguished Scientist & Research Lead','陳昇瑋紀念講座 KEYNOTE'),(5,0,9999,'PANEL','簡立峰','Lee-Feng Chien','lee-feng-chien','生成式 AI 開啟的技術與產業革新','中文','yes','X','Appier and iKala','Board Director ','/img/speaker/f9521fcf.jpg',NULL,NULL,NULL,'',NULL,'Dr. Lee-Feng Chien has spent a career immersed in innovative industries where he has worked to advance technology and scientific and technological talent. In 2006, he became Google’s first employee in Taiwan when he joined as Managing Director.   Since retiring from Google in 2020, he has actively supported the development of Taiwanese startups, including serving as Board Director of AI pioneers such as Appier, which went public in 2021, and iKala, and a mentor to numerous individual entrepreneurs and publishes articles that encourage internationalization and innovative thinking for software startups.   Dr. Chien is a leading expert in Chinese information retrieval and natural language processing technology. He is a former Research Fellow and Deputy Director of the Institute of Information Science, Academia Sinica, and a co-appointed Professor of the Department of Information Management at National Taiwan University, where he earned a PhD in Computer Science in 1991.” ','<p>Dr. Lee-Feng Chien has spent a career immersed in innovative industries where he has worked to advance technology and scientific and technological talent. In 2006, he became Google’s first employee in Taiwan when he joined as Managing Director.</p>\r\n\r\n<p>Since retiring from Google in 2020, he has actively supported the development of Taiwanese startups, including serving as Board Director of AI pioneers such as Appier, which went public in 2021, and iKala, and a mentor to numerous individual entrepreneurs and publishes articles that encourage internationalization and innovative thinking for software startups.</p>\r\n\r\n<p>Dr. Chien is a leading expert in Chinese information retrieval and natural language processing technology. He is a former Research Fellow and Deputy Director of the Institute of Information Science, Academia Sinica, and a co-appointed Professor of the Department of Information Management at National Taiwan University, where he earned a PhD in Computer Science in 1991.</p>',NULL,'','',NULL,NULL,'生成式 AI 開啟的技術與產業革新'),(6,0,9999,'PANEL','張嘉淵','Ted Chang','ted-chang','生成式 AI 開啟的技術與產業革新','中文','yes','簡報6','Quanta Computer','CTO','/img/speaker/41ebeef3.jpg',NULL,NULL,NULL,'',NULL,'','<p>Dr. Ted Chang is a highly accomplished Chief Technology Officer, Vice President and General Manager of Quanta Computer, which is the world’s largest computer ODM and laptop computer maker. He has more than 20 years of experience in leading global corporations and has been instrumental in driving corporate technology strategy and global research partnership. In addition, Dr. Chang is responsible for overseeing the Quanta Research Institute (QRI) for advanced research and BU12, a business unit dedicated to integration of AI, IoT and cloud computing as a platform solution for smart transformation of Heathcare, Medicine and Agriculture.</p>\r\n<p>Dr. Chang has been appointed as representatives of Taiwan for APEC Business Advisory Council (ABAC) since 2019. Academically, Dr. Chang holds various guest professorships in the EECS colleges of National Taiwan University (NTU), National Cheng-Kung University (NCKU), Asia University (AU) and the AI college of National Yang-Ming Chao-Tung University (NYCU). He serves as a member of the board for several educational and research foundations, including the Epoch Foundation, Spring Foundation, Quanta Culture and Education Foundation (QCEF), Chinese Medical Advancement Foundation, and Ming Dao Culture and Education Foundation.</p>\r\n<p>Among many honors, Dr. Chang recently received the Japan Good Design Best 100 award in 2022, five REDDOT Design Awards on Smart Medicine (2021 and 2022), and IF Design Award on Smart Agriculture in 2021. He was also awarded distinguished alumni awards from both NCKU and Chia-Yi High School in 2021. He led the Quanta-NCTU Joint AI Center to win the CES Innovation Award and WITSA in 2020 Award. He was the chief advisor to the Taiwan Pavilion “Swingphony” at London Design Biennale 2020.</p>\r\n<p>Dr. Chang is a prolific inventor with over 220 patents granted globally by Oct. 2022. His invention in 2001, \\\"\\\"A Network Object Delivery System for Personal Computing Device,\\\"\\\" defined the \\\"\\\"Application Module Store.\\\"\\\" Dr. Chang joined Quanta in 2000, promoted as VP in 2009 and promoted as the first CTO in Quanta history in 2010. Since 2004, Dr. Chang has led the strategic research collaboration on future computing with MIT Computer Science and Artificial Lab (CSAIL) to support the transformation of Quanta. The partnership started with TParty project on Human Centric Computing, Qmulus Project on Cloud Computing and now on AIM project with focus on AI medicine and computational health. Dr. Chang\\\'s past projects, One Laptop Per Child (OLPC) and the QRI research model, were published as business cases by Harvard Business School.</p>',NULL,'','','Quanta\r','技術長',NULL),(7,0,9999,'PANEL','李育杰','Yuh-Jye Lee','yuh-jye-lee','生成式 AI 開啟的技術與產業革新','中文','yes','簡報7','Research Center for Information Technology Innovation, Academia Sinica','CEO, TWISC','/img/speaker/bb2d9300.jpg',NULL,NULL,NULL,'',NULL,'Prof. Yuh-Jye Lee is a computer scientist who holds a PhD in Computer Sciences from UW-Madison (2001). He has held positions at esteemed universities, including National Chun Cheng University, Taiwan Tech, and National Yang Ming Chiao Tung University.  Prof. Lee also had the opportunity to serve the government from November 2020 to January 2023 as the Deputy Executive Secretary of the Office of Science and Technology Policy, National Science and Technology Council. This office is responsible for Taiwan\'s science and technology policies, budget allocation, and the review of national-level science and technology projects. Currently, he serves as the Chief Executive Officer of the Taiwan Information Security Center at the Research Center for Information Technology Innovation, Academia Sinica.  Prof. Lee\'s research primarily focuses on AI, data science, machine learning, federated learning, and information security, with a specific interest in developing lightweight anomaly detection techniques for IoT applications. Over the past decade, he has developed numerous efficient machine learning algorithms such as SSVM and RSVM that have been successfully applied in various fields, including breast cancer diagnosis and prognosis, network intrusion detection, and fake news prevention. In essence, his research is centered on AI in security and security in AI. He is also in charge of the TAIDE project, which stands for Trustworthy AI Dialogue Engine. ','<p>Prof. Yuh-Jye Lee is a computer scientist who holds a PhD in Computer Sciences from UW-Madison (2001). He has held positions at esteemed universities, including National Chun Cheng University, Taiwan Tech, and National Yang Ming Chiao Tung University.East</p>\r\n\r\n<p>Prof. Lee also had the opportunity to serve the government from November 2020 to January 2023 as the Deputy Executive Secretary of the Office of Science and Technology Policy, National Science and Technology Council. This office is responsible for Taiwan\'s science and technology policies, budget allocation, and the review of national-level science and technology projects. Currently, he serves as the Chief Executive Officer of the Taiwan Information Security Center at the Research Center for Information Technology Innovation, Academia Sinica.</p>\r\n\r\n<p>Prof. Lee\'s research primarily focuses on AI, data science, machine learning, federated learning, and information security, with a specific interest in developing lightweight anomaly detection techniques for IoT applications. Over the past decade, he has developed numerous efficient machine learning algorithms such as SSVM and RSVM that have been successfully applied in various fields, including breast cancer diagnosis and prognosis, network intrusion detection, and fake news prevention. In essence, his research is centered on AI in security and security in AI. He is also in charge of the TAIDE project, which stands for Trustworthy AI Dialogue Engine.</p>','https://www.citi.sinica.edu.tw/pages/yuh-jye/contact_en.html','','','Academia Sinica\r','研究員',NULL),(8,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(9,0,9999,'AI','劉思泰','ST Liew','st-liew','The Future of AI is on-device','中文','yes','X','Qualcomm Technologies','President, Taiwan & SEA\r Australia, New Zealand\r Vice President','/img/speaker/ed0e1a3c.jpg',NULL,NULL,NULL,'Qualcomm has been cultivating AI technology for more than ten years and foresees that AI applications bring unlimited possibilities with innovation to every industry. As generative AI adoption grows at record-setting speeds and drives higher demand for compute, we believe the future of AI is on-device. In this session, you will see how we fuel on-device AI to enable generative AI to scale with more diversified fields, and what benefits will bring to enhance the user experience through AI.',NULL,'ST Liew is a Vice President of Qualcomm Technologies, Inc. and the President of Qualcomm Taiwan and South East Asia, Australia, New Zealand. ST was born in Malaysia and was educated in Malaysia, Singapore and the UK. His permanent home is Singapore.  In this role, ST is responsible for leading all business and operational functions for Qualcomm in the region. Prior to this role, ST served as the Vice President and President of Qualcomm Taiwan.  ST has more than 30 years of experience leading businesses and R&D in the telecommunication industry. Most recently ST was the President of Acer’s new Business Group SPBG that focused on R&D and Sales of non PC lines of product for the global market while living in Switzerland and later in Taiwan.  Before joining Acer, ST was in Motorola for over 18 years leading Regional R&D Teams and later in Product planning, business Teams across the world in products ranging from Mobile radios, Pagers, Data terminals to Cellular phones. ST has lived in China, Korea, USA and India during his tenure.  Liew received his MBA from the National University of Singapore, and holds a BSc. in Electrical and Electronic Engineering from the University of Leeds, UK. ','<p>ST Liew is a Vice President of Qualcomm Technologies, Inc. and the President of Qualcomm Taiwan and South East Asia, Australia, New Zealand. ST was born in Malaysia and was educated in Malaysia, Singapore and the UK. His permanent home is Singapore. </p>\r\n<p>In this role, ST is responsible for leading all business and operational functions for Qualcomm in the region. Prior to this role, ST served as the Vice President and President of Qualcomm Taiwan. </p>\r\n<p>ST has more than 30 years of experience leading businesses and R&D in the telecommunication industry. Most recently ST was the President of Acer’s new Business Group SPBG that focused on R&D and Sales of non PC lines of product for the global market while living in Switzerland and later in Taiwan. </p>\r\n<p>Before joining Acer, ST was in Motorola for over 18 years leading Regional R&D Teams and later in Product planning, business Teams across the world in products ranging from Mobile radios, Pagers, Data terminals to Cellular phones. ST has lived in China, Korea, USA and India during his tenure. </p>\r\n<p>Liew received his MBA from the National University of Singapore, and holds a BSc. in Electrical and Electronic Engineering from the University of Leeds, UK.</p>',NULL,'','','Qualcomm\r','副總裁暨台灣、東南亞與紐澳區總裁',NULL),(10,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(11,0,9999,'AI','吳漢章','Peter Wu','peter-wu',' Democratizing LLM to Empower Generative AI Innovations','中文','yes','Ｘ','TWSC','CEO','/img/speaker/5113be18.jpg',NULL,NULL,NULL,'Generative AI is sparking a revolutionary shift in how humanity harnesses information technology, triggering a wave of innovation. Its applications are diversifying across various sectors, promising new opportunities. Generative AI is a knowledge-based technology, and currently, many countries are actively crafting legislation to regulate the risks associated with its development and use. To manage these risks, we rely on democratizing LLM AI technology, open-source models, and data governance, especially in critical areas like healthcare. Taiwan boasts a solid industrial foundation for promoting democratizing AI, with strengths in computing power, semiconductor manufacturing, systems, and IT services. With government support, Taiwan aims to emerge as a leader in both Generative AI and Trusted AI.','<p>Generative AI is sparking a revolutionary shift in how humanity harnesses information technology, triggering a wave of innovation. Its applications are diversifying across various sectors, promising new opportunities. Generative AI is a knowledge-based technology, and currently, many countries are actively crafting legislation to regulate the risks associated with its development and use.</p>\r\n<p>To manage these risks, we rely on democratizing LLM AI technology, open-source models, and data governance, especially in critical areas like healthcare. Taiwan boasts a solid industrial foundation for promoting democratizing AI, with strengths in computing power, semiconductor manufacturing, systems, and IT services. With government support, Taiwan aims to emerge as a leader in both Generative AI and Trusted AI.</p>','Current Job: CEO of ASUS Cloud and TWSC\r Education\r • Ph.D., Biomedical Engineering, National Taiwan University\r • Electrical Engineering, National Taiwan University\r Peter Wu is a highly accomplished executive with a diverse range of experiences\r and achievements in the technology industry. He currently holds two prominent\r positions, serving as the CEO of ASUS Cloud of Taiwan Web Service Corporation.\r In addition to his current roles, Peter Wu is actively involved in various\r organizations and committees. He serves as a committee member of the\r Biotechnology and Pharmaceutical Industries Promotion Office under the\r Ministry of Economic Affairs. Peter Wu is also holds the position of Director at\r Information Service Industry Association of R.O.C., Supervisor at the Cloud\r Computing &amp; IoT Association in Taiwan and serves as the Deputy Director of the\r Policy and Legal Committee and President of Taipei Computer Association AI\r Alliance. Through these roles, he helps drive policy discussions and promote the\r growth of cloud computing in Taiwan.\r Recognized for his expertise and insights, Peter Wu was appointed as a member\r of the Advisory Committee on Bio Taiwan Committee by the Executive Yuan in\r 2017 and 2019. In this capacity, he provided valuable guidance and advice on the\r strategic direction of the biotechnology industry in Taiwan.\r With a wealth of experience and a passion for technology and innovation, Peter\r Wu is a highly respected leader in the industry. His contributions to the\r advancement of cloud computing, smart healthcare, and the software industry\r have been instrumental in driving growth and shaping the future of Taiwan&#39;s\r technology landscape.','<p>Current Job: CEO of ASUS Cloud and TWSC Education<br>\r\n• Ph.D., Biomedical Engineering, National Taiwan University<br>\r\n• Electrical Engineering, National Taiwan University\r\n</p>\r\n<p>Peter Wu is a highly accomplished executive with a diverse range of experiences and achievements in the technology industry. He currently holds two prominent positions, serving as the CEO of ASUS Cloud of Taiwan Web Service Corporation. In addition to his current roles, Peter Wu is actively involved in various organizations and committees. He serves as a committee member of the Biotechnology and Pharmaceutical Industries Promotion Office under the Ministry of Economic Affairs. Peter Wu is also holds the position of Director at Information Service Industry Association of R.O.C., Supervisor at the Cloud Computing &amp; IoT Association in Taiwan and serves as the Deputy Director of the Policy and Legal Committee and President of Taipei Computer Association AI Alliance. Through these roles, he helps drive policy discussions and promote the growth of cloud computing in Taiwan.</p>\r\n<p>Recognized for his expertise and insights, Peter Wu was appointed as a member of the Advisory Committee on Bio Taiwan Committee by the Executive Yuan in 2017 and 2019. In this capacity, he provided valuable guidance and advice on the strategic direction of the biotechnology industry in Taiwan.</p>\r\n<p>With a wealth of experience and a passion for technology and innovation, Peter Wu is a highly respected leader in the industry. His contributions to the advancement of cloud computing, smart healthcare, and the software industry have been instrumental in driving growth and shaping the future of Taiwan&#39;s technology landscape.</p>','https://tws.twcc.ai/team/','','','Taiwan Web Service\r','總經理',NULL),(12,0,9999,'AI','許大山','Da-shan Shiu','da-shan-shiu','Case Studies of Applying Generative AI Concepts to Low Resource Domains','中文','yes','V','MediaTek Research','Managing Director','/img/speaker/82486038.jpg',NULL,NULL,NULL,'Generative AI has achieved significant advances in a very short amount of time, in areas of language, vision, coding, speech and audio. In this talk we share two cases in which generative AI are applied to two low resource scenarios. In the first case, we have some very precious samples of cellular channel responses from real-world measurement. We would like to draw synthetic channel responses from the same distribution. In the second case, we are asked to customize an automatic speech recognition system to a use doamin, for which we do not have any audio-transcript pairs. We share our experience in how to tackle such low or even no resource challenges. ',NULL,'Dr. Da-shan Shiu is currently the Managing Director of MediaTek Research. Prior to this, he co-founded Mobilepeak Systems and served as its Chief Technology Officer. He was also an Associate Professor at the Department of Electrical Engineering and the Graduate School of Communications Engineering of National Taiwan University, as well as leading the Cellular modem algorithm development of Qualcomm in San Jose. He holds a Ph.D. from UC Berkeley. His research interests lie in fundamental communication and computational theory. He applies theoretical principles to practical applications, such as cellular communications, virtual and augmented reality, foundation model-driven autonomous agents, and machine learning for electronic design automation (EDA).','','https://www.linkedin.com/in/da-shan-shiu/','','','MediaTek\r','創新基地總監',NULL),(13,0,9999,'AI','沈文冰','Wenping Shen','wenping-shen','Fine-tuning LLMs for Your Enterprise Applications','中文','yes','X','TSMC','AI Application & Integration Division, Deputy Director ','/img/speaker/18b4ca96.jpg',NULL,NULL,NULL,'As the field of LLM research continues to rapidly evolve, enterprises must constantly \"Fine-Tune\" their LLMs to leverage the benefits of SOTA models. Here, we explore the practical reasons for fine-tuning LLMs for enterprise applications and share strategies for meeting these challenges head-on.',NULL,'Over 25 years of experience in enterprise IT and held senior positions in a variety of industries, including semiconductor manufacturing (TSMC), finance and insurance (MetLife), and electrification and automation (ABB).  ','',NULL,'','','TSMC\r','智慧應用整合處副處長',NULL),(14,0,9999,'AIK','Thomas Scialom','','thomas-scialom','The AI Revolution','中文','yes','V','Meta AI','Research Scientist (LLMs)','/img/speaker/d0aabc21.jpg',NULL,NULL,NULL,'The rapid evolution of artificial intelligence is ushering in a new era, where large language models are outpacing human experts in fields as diverse as law and medicine. Comprehending this trajectory is essential for gauging the technology\'s future implications.\r\n In this keynote, Dr. Scialom offers a unique vantage point on the exponential rise and unfolding direction of AI. Through the lens of his own career—from the nascent stages of language models that could barely construct a sentence, to groundbreaking creations like his recent Llama 2—Thomas Scialom will share his personal perspective into the expanding competencies and complexities of Generative AI and large language models.\r\n','<p>The rapid evolution of artificial intelligence is ushering in a new era, where large language models are outpacing human experts in fields as diverse as law and medicine. Comprehending this trajectory is essential for gauging the technology\'s future implications.</p>\r\n<p>In this keynote, Dr. Scialom offers a unique vantage point on the exponential rise and unfolding direction of AI. Through the lens of his own career—from the nascent stages of language models that could barely construct a sentence, to groundbreaking creations like his recent Llama 2—Thomas Scialom will share his personal perspective into the expanding competencies and complexities of Generative AI and large language models.</p>','Thomas Scialom is behind some of the world\'s best-known Generative A.I. projects including Llama 2  (Co-Lead), Toolformer, Galactica and Unnatural Instruction.    •  Llama 2 is today\'s top open-source LLM  •  Toolformer is an LLM that learns how to use tools •  Galactica is an LLM for science   Dr. Scialom: • Is an A.I. Research Scientist at Meta. • Has lectured at many of the top A.I. labs (e.g., Google, Stanford, MILA). • Is contributing to the development of Artificial General Intelligence (AGI). • Holds a PhD from Sorbonne University, where he specialized in Natural-Language Generation with Reinforcement Learning.','<p>Thomas Scialom is behind some of the world\'s best-known Generative A.I. projects including Llama 2 </p>\r\n<p>(Co-Lead), Toolformer, Galactica and Unnatural Instruction.  </p>\r\n<br>\r\n<p>•  Llama 2 is today\'s top open-source LLM </p>\r\n<p>•  Toolformer is an LLM that learns how to use tools</p>\r\n<p>•  Galactica is an LLM for science </p>\r\n<br>\r\n<p>\r\nDr. Scialom:\r\n<ul>\r\n<li style=\"list-style-type:disc;\">Is an A.I. Research Scientist at Meta.</li>\r\n<li style=\"list-style-type:disc;\">Has lectured at many of the top A.I. labs (e.g., Google, Stanford, MILA).</li>\r\n<li style=\"list-style-type:disc;\">Is contributing to the development of Artificial General Intelligence (AGI).</li>\r\n<li style=\"list-style-type:disc;\">Holds a PhD from Sorbonne University, where he specialized in Natural-Language Generation with Reinforcement Learning.</li>\r\n</ul>\r\n</p> ','https://www.linkedin.com/in/tscialom/','','','Meta AI','Research Scientist','KEYNOTE'),(15,0,9999,'AI','王宗業','Chungyeh Wang','chungyeh-wang','Generative AI on Intel® architecture','中文','yes','X','Intel','Platform Software Architect','/img/speaker/7df5ff29.jpg',NULL,NULL,NULL,'Generative AI is causing impacts across various industries worldwide. For Taiwan\'s industries, it represents a significant challenge, but also a rare opportunity. Currently, there are numerous open-source generative AI pre-trained models, platforms services and resources available. The ability to optimize open-source pre-trained models and tools will be crucial for unique competitive advantages.  Intel AI Everywhere can accelerate innovation throughout the entire AI product development cycle. It allows you to maximize the value of your products and services, and enables easy deployment on both the cloud and edge, while maintaining information security and regulatory compliance. Through examples of popular applications like Stable Diffusion and Llama2 in generative AI, we will explore how the advantages of Intel\'s software and hardware architecture empower everyone to grasp the opportunities of generative AI.  生成式AI正在對全球各個產業帶來衝擊，對臺灣產業是巨大挑戰，更是難得的機遇. 目前有許多 open source 的生成式AI 預訓練模型跟平台服務與資源，擁有優化開源預訓練模型與工具的能力將會是產生獨特競爭力的關鍵.  Intel AI Everywhere可以加速整個AI產品開發週期的創新,讓你的產品與服務價值最大化,並且可以方便的在受到資安保護且符合法規的條件下布署到cloud以及edge. 透過最熱門的stable diffusion 以及llama2等生成式AI應用實例的方享, 探討Intel 軟硬體架構的優勢如何讓大家掌握生成式AI的機遇.','<p>Generative AI is causing impacts across various industries worldwide. For Taiwan\'s industries, it represents a significant challenge, but also a rare opportunity. Currently, there are numerous open-source generative AI pre-trained models, platforms services and resources available. The ability to optimize open-source pre-trained models and tools will be crucial for unique competitive advantages.</p>\r\n\r\n<p>Intel AI Everywhere can accelerate innovation throughout the entire AI product development cycle. It allows you to maximize the value of your products and services, and enables easy deployment on both the cloud and edge, while maintaining information security and regulatory compliance. Through examples of popular applications like Stable Diffusion and Llama2 in generative AI, we will explore how the advantages of Intel\'s software and hardware architecture empower everyone to grasp the opportunities of generative AI.</p>\r\n\r\n<p>生成式AI正在對全球各個產業帶來衝擊，對臺灣產業是巨大挑戰，更是難得的機遇. 目前有許多 open source 的生成式AI 預訓練模型跟平台服務與資源，擁有優化開源預訓練模型與工具的能力將會是產生獨特競爭力的關鍵.</p>\r\n\r\n<p>Intel AI Everywhere可以加速整個AI產品開發週期的創新,讓你的產品與服務價值最大化,並且可以方便的在受到資安保護且符合法規的條件下布署到cloud以及edge. 透過最熱門的stable diffusion 以及llama2等生成式AI應用實例的方享, 探討Intel 軟硬體架構的優勢如何讓大家掌握生成式AI的機遇,</p>','美商英特爾公司平台研發協理，負責 Intel Edge AI 平台的客戶以及生態系統開發。擔任過台灣人工智慧學校經理人班，技術領袖班與 Edge AI 專班以及大專院校的深度學習課程業師，具有豐富的產業經驗。','',NULL,'','','Intel\r','研發協理',NULL),(16,0,9999,'AI','李百飛','Brian Lee','brian-lee','Green Technologies Embedded for Big Data + GenAI Platform','中文','yes','X','Dell Technologies ','Technical VP','/img/speaker/8bda2aba.jpg',NULL,NULL,NULL,'Combining GenAI with big data to create a competitive advantage for businesses is a prevailing trend today. However, both big data and GenAI are huge investments in IT resources. How to achieve optimal computing performance, storage SLA with sufficient capacity, minimal energy consumption, and minimal human intervention to meet the lowest TCO is a key challenge. In this agenda, we will unveil the best Big Data + GenAI framework and the green energy technologies used to simultaneously achieve highest efficiency, great energy savings with carbon reduction, and best TCO, while creating a competitive edge.',NULL,'I am currently employed at Dell Technologies in Taiwan with over 25 years of IT experience. My technical expertise particularly focuses on: •        Building private clouds and integrating public clouds to implement optimal multi-cloud strategies. •        Integrating the GenAI framework into big data platforms, establishing a solid foundation for intelligent transformation. •        Planning IT architectures to mitigate geopolitical risks. •        Utilizing Green Data Center technologies to enhance the ESG journey. ','<p>I am currently employed at Dell Technologies in Taiwan with over 25 years of IT experience. My technical expertise particularly focuses on:</p>\r\n<ul>\r\n<li style=\\\"list-style-type: disc;\\\">Building private clouds and integrating public clouds to implement optimal multi-cloud strategies.</li>\r\n<li style=\\\"list-style-type: disc;\\\">Integrating the GenAI framework into big data platforms, establishing a solid foundation for intelligent transformation.</li>\r\n<li style=\\\"list-style-type: disc;\\\">Planning IT architectures to mitigate geopolitical risks.</li>\r\n<li style=\\\"list-style-type: disc;\\\">Utilizing Green Data Center technologies to enhance the ESG journey.</li>\r\n</ul>',NULL,'System Engineering','','Dell','技術副總經理',NULL),(17,0,9999,'AI','陳贈文','Vince Chen','vince-chen','Green AI Infrastructure for Business Transformation','中文','no','X','Super Micro Computer, Inc.','Sr. Director of Solutions Architecture','/img/speaker/2d9bce16.jpg',NULL,NULL,NULL,'In the era of blooming AI everywhere, transforming the business by adopting AI capabilities has no longer planning but actions.  In the session we’d talk about the leading edge technologies and solutions Supermicro can bring to the customers, not just to get high performance and best TCO but also to have the efficient and sustainable infrastructure.',NULL,'Vince Chen is a Sr. Director of Solutions Architecture in Supermicro’s System Product Group, focused on executing company’s solution business strategy. Since the time of joining Supermicro in 2017, He has been leading a team of Solutions Architects and successfully architected, implemented and delivered optimized solutions to large scale data center and enterprise customers. He has over 25 years of experience in IT industry, with the specialties in server and datacenter technologies and solutions.  He started early career as a hard-core engineering developing generations of enterprise server systems, followed by driving ecosystem collaboration to deliver datacenter technology innovations, to current role of delivering turn-key solutions to customers and helping them achieve their business goals with latest and greatest technologies.','',NULL,'','','SuperMicro\r','資深協理',NULL),(18,0,9999,'AI','康勝閔','Eric Kang','eric-kang','NVIDIA Grace Hopper Superchip Architecture In-Depth','中文','yes','X','NVIDIA','Senior Manger, Solution Architect ','/img/speaker/7fc093cf.png',NULL,NULL,NULL,'The NVIDIA Grace Hopper Superchip Architecture is the first true heterogeneous accelerated platform for high-performance computing (HPC) and AI workloads. It accelerates applications with the strengths of both GPUs and CPUs while providing the simplest and most productive distributed heterogeneous programming model to date. Scientists and engineers can focus on solving the world’s most important problems. The NVIDIA Grace Hopper Superchip architecture brings together the groundbreaking performance of the NVIDIA Hopper GPU with the versatility of the NVIDIA Grace CPU, connected with a high bandwidth and memory coherent NVIDIA NVLink Chip-2-Chip (C2C) interconnect in a single superchip, and support for the new NVIDIA NVLink Switch System.',NULL,'Eric Kang leading the Solutions Architect team in NVIDIA, working with customers and partners to deliver the world\'s best solutions for artificial intelligence, deep learning and machine learning, professional visualization, and high-performance computing. Specializing in NVIDIA\'s advanced solutions architecture planning, he has in-depth research on high-performance computing and deep learning computing architecture and participates in relevant important projects architecture planning. Prior to joining NVIDIA, he served in HP Enterprise and as solutions consultant lead for data center transformation practice. Experience including high-performance computing, advanced data center planning, private cloud and public cloud management solutions, data center management automation.','',NULL,'','','NVIDIA\r','資深解決方案架構協理',NULL),(19,0,9999,'AI','沈仲杰','JongJye Sheen','jongjye-sheen','AMD Instinct GPU – 1.19 ExaFlops System and LLM','中文','yes','V','AMD','Sr. Market Development Manager','/img/speaker/87f459d5.jpeg',NULL,NULL,NULL,'   AMD has been designing high end Graphic Processors for a long period. In the 2010s, AMD joined the HPC project with DOE in the States and delivered the first ExaFlops system – Frontier. Frontier has not only achieved more than 1.1 Exa 64 bits Flops (2022 Jun), but also is the first system to deliver more than 60GFlops/Watt which provides extraordinary energy efficiency. With the breakthrough in performance, the comprehensive GPU software development environment named ROCm was used to provide necessary tools (Compiler, Debugger, Profiler) and software libraries for the software experts to develop GPU codes to run on AMD MI-Instinct GPU.      ​   AMD MI250X GPU was the GPU that used to build the Frontier system. The MI250X GPU Architecture has Hardware level Unify memory feature. CPU and GPU are connected with AMD XGMI Infinity fabrics. The following on generation MI300A, which is another breakthrough that integrated CPU and GPU in the same Socket to have all HBM shared between GPU and CPU which could eliminate the costly memory copy between System memory and HBM memory. Expected memory bound applications will be benefited by this architecture. Another coming product, MI300X, which follows OAM design standard, will provide 192GB HBM3 memory and 5.2TBs internal HBM memory bandwidth, that is suitable for LLM applications. AMD chip-let architecture has been proven as a successful technology that provides flexibility and scale up ​capability within a socket, and is able to deliver versatile processing/memory ​combination on a single Socket to support the  growing demand of ​different workload​.        AMD ROCm is now an official support platform of Pytroch, Many AI models and Frameworks has been supported on ROCm environment and lots of them has containers built for test and available in GitHub. AMD ROCm inherited the philosophy of Open Source Community. AMD ROCm HPL and HPCG source code is downloadable. (https://community.amd.com/t5/rocm/rocm-hpl-code-now-open-sourced-for-amd-instinct-accelerators/ba-p/540113AMD). AMD believe with collaboration and share with the Open Source Community, technology development will be thrived and fruitful. ROCm learning environment and materials is also available on WEB for general access.      ','<p>AMD has been designing high end Graphic Processors for a long period. In the 2010s, AMD joined the HPC project with DOE in the States and delivered the first ExaFlops system – Frontier. Frontier has not only achieved more than 1.1 Exa 64 bits Flops (2022 Jun), but also is the first system to deliver more than 60GFlops/Watt which provides extraordinary energy efficiency. With the breakthrough in performance, the comprehensive GPU software development environment named ROCm was used to provide necessary tools (Compiler, Debugger, Profiler) and software libraries for the software experts to develop GPU codes to run on AMD MI-Instinct GPU.</p>\r\n<p>​AMD MI250X GPU was the GPU that used to build the Frontier system. The MI250X GPU Architecture has Hardware level Unify memory feature. CPU and GPU are connected with AMD XGMI Infinity fabrics. The following on generation MI300A, which is another breakthrough that integrated CPU and GPU in the same Socket to have all HBM shared between GPU and CPU which could eliminate the costly memory copy between System memory and HBM memory. Expected memory bound applications will be benefited by this architecture. Another coming product, MI300X, which follows OAM design standard, will provide 192GB HBM3 memory and 5.2TBs internal HBM memory bandwidth, that is suitable for LLM applications. AMD chip-let architecture has been proven as a successful technology that provides flexibility and scale up ​capability within a socket, and is able to deliver versatile processing/memory ​combination on a single Socket to support the  growing demand of ​different workload​.</p>',' JongJye started his HPC career in 2002. He has delivered the first 1TFlops system in Taiwan (based on HP Itanium) to NCHC in 2003. He has been working in APAC region and look after HyperScale computing business mainly focus in North Asia area. He is now in AMD and supporting DC GPU business.','',NULL,'Data Center Accelerator BU','','AMD\r','資深經理',NULL),(20,0,9999,'AI','洪嘉明','Chia-Ming Hung','chia-ming-hung','Designing Industry-Leading Energy-Efficient AI Chips','中文','yes','X','NEUCHIPS','R&D department, Manager','/img/speaker/a5afcb98.jpg',NULL,NULL,NULL,'In the presentation, we will use NEUCHIPS\'s product as an example to show the challenges of creating cutting-edge energy-efficient AI chips. We will talk about the strategies and technologies used in the design process, highlighting impressive MLPerf benchmarks achievements in energy efficiency. Moreover, we\'ll discuss the future possibilities and trends in deep-learning recommendation systems and generative AI.',NULL,'Chia-Ming Hung is Research and Development Manager at NEUCHIPS, with responsibilities encompassing the guidance of SoC platform and AI chip architecture design. With an extensive background spanning around 15 years in the IC design industry and considerable experience in chip tape-outs, he brings a wealth of expertise to his role. His academic journey led him to graduate from the Master\'s program in the Department of Computer Science at National Tsing Hua University, Taiwan.','','https://www.linkedin.com/in/chiaming-hung-5a720291/','','','NEUCHIPS\r','經理',NULL),(21,0,9999,'AI','吳偉壽','Wayne Wu','wayne-wu','Liberate Data Performance, Embrace a Highly Flexible and Intelligent Cloud.','中文','yes','V','NetApp','Solution Engineer','/img/speaker/c426af56.jpg',NULL,NULL,NULL,'1. Why do the vast majority of IT experts and enterprise customers choose NetApp products? 2. NetApp can assist you in effortlessly integrating data into the cloud, simplifying data management, and optimizing your resource utilization. 3. Sharing the key points and benefits of implementing an AI architecture. ','<ol>\r\n<li>Why do the vast majority of IT experts and enterprise customers choose NetApp products?</li>\r\n<li>NetApp can assist you in effortlessly integrating data into the cloud, simplifying data management, and optimizing your resource utilization.</li>\r\n<li>Sharing the key points and benefits of implementing an AI architecture.</li>\r\n</ol>','Mr. Wu(Wayne Wu), currently serving as a solutions engineering at NetApp Taiwan, has extensive experience in the IT field. He has worked as a technical engineer, senior project manager, and sales technical consultant in well-known companies in the healthcare and telecommunications industries. He holds professional certifications in VＭware, NetApp, AWS, ISO, and more.  Mr. Wu specializes in information system architecture integration, hybrid cloud environment deployment, information security, and data center design planning. He has successfully executed and assisted in implementing numerous practical projects, serving clients in various sectors, including government agencies, education, telecommunications, and healthcare. With a wealth of experience in optimizing information system performance and risk management in setup and operations, he is a consultant well-versed in both expertise and industry operations knowledge. ','<p>Mr. Wu(Wayne Wu), currently serving as a solutions engineering at NetApp Taiwan, has extensive experience in the IT field. He has worked as a technical engineer, senior project manager, and sales technical consultant in well-known companies in the healthcare and telecommunications industries. He holds professional certifications in VＭware, NetApp, AWS, ISO, and more.</p>\r\n\r\n<p>Mr. Wu specializes in information system architecture integration, hybrid cloud environment deployment, information security, and data center design planning. He has successfully executed and assisted in implementing numerous practical projects, serving clients in various sectors, including government agencies, education, telecommunications, and healthcare. With a wealth of experience in optimizing information system performance and risk management in setup and operations, he is a consultant well-versed in both expertise and industry operations knowledge.</p>',NULL,'','','NetApp\r','技術顧問',NULL),(22,0,9999,'AI','李昕穎','Hsin-Ying Lee','hsin-ying-lee','From 2D to 3D / From Image to Video','中文','yes','V','Snap Inc.','Senior Research Scientist, Creative Vision Team, Snap Research','/img/speaker/bb251f90.png',NULL,NULL,NULL,'Generative models, particularly  diffusion models, have revolutionized the field of artificial intelligence by enabling machines to autonomously generate realistic and creative content. While the primary emphasis has been on generating and manipulating static 2D images, recent months have borne witness to a captivating surge in advancements pertaining to 3D content and dynamic videos. This juncture marks a significant extension in both spatial and temporal dimensions, transitioning from 2D to 3D and from images to videos, respectively. In this intricate expansion lies a confluence of intriguing shared properties and formidable challenges. This talk will briefly introduce the current research landscape for both 3D and video synthesis, shedding light on their distinctive attributes and common hurdles.',NULL,'Hsin-Ying Lee is a senior research scientist in the Creative Vision team at Snap Research. He has been working on generative models since 2017. His recent research interests lie in 3D and 4D generation. ','','http://hsinyinglee.com/','','','Snap\r','資深研究科學家',NULL),(23,0,9999,'AI','邱浩修','Hao-Hsiu Chiu','hao-hsiu-chiu','Creativity with Generative AI in the Design and Architecture Industry','中文','yes','V','Tunghai Uiversity','Department of Architecture, Associate Professor','/img/speaker/8a3da100.png',NULL,NULL,NULL,'Generative AI is undoubtedly making dramatic changes in many industries and cultures, including architecture. It allows us to imagine more efficiently, produce a greater variety of design solutions, test the effectiveness of our solutions with simulations, and control the performance of buildings once they are constructed. For the first time, the evolution of AI technology has transformed from an external &quot;productivity improvement&quot; of design tools to an internal &quot;replacement of thinking power&quot;? Even touching the new boundary of &quot;creative reinvention&quot;. As an architect who has always integrated creativity into practice, how should we make adjustments and respond to the intelligent design process? This talk intends to demonstrates various possibilities of how the architecture and design industry can effectively use visual generated AI to accelerate design creativity and motivate innovation.  AI人工智慧無疑將會對未來建築文化，產生多方面的重大改變。它將允許我們更有效率地進行 設計、生產更多樣的設計方案、以模擬測試我們方案的有效性，以及控制建築建造後的效能。 尤其是生成式人工智慧的急速發展，AI技術演進第一次從一種外在設計工具的“生產力提升”， 轉變為一種內在的“思考力替代”？甚至觸碰到“創造力重塑”的新邊界。向來作為創意到實踐整 合的建築師，面對智能化的建築生產過程，該如何做出調整與因應？本演講分享將就建築與設 計產業如何有效運用圖像生成式AI，加速設計創意與流程創新的各種可能。','<p>Generative AI is undoubtedly making dramatic changes in many industries and cultures, including\r\narchitecture. It allows us to imagine more efficiently, produce a greater variety of design solutions,\r\ntest the effectiveness of our solutions with simulations, and control the performance of buildings\r\nonce they are constructed. For the first time, the evolution of AI technology has transformed from an\r\nexternal \"productivity improvement\" of design tools to an internal \"replacement of thinking power\"?\r\nEven touching the new boundary of \"creative reinvention\". As an architect who has always integrated\r\ncreativity into practice, how should we make adjustments and respond to the intelligent design\r\nprocess? This talk intends to demonstrates various possibilities of how the architecture and design\r\nindustry can effectively use visual generated AI to accelerate design creativity and motivate\r\ninnovation.</p>\r\n\r\n<p>AI人工智慧無疑將會對未來建築文化，產生多方面的重大改變。它將允許我們更有效率地進行\r\n設計、生產更多樣的設計方案、以模擬測試我們方案的有效性，以及控制建築建造後的效能。\r\n尤其是生成式人工智慧的急速發展，AI技術演進第一次從一種外在設計工具的“生產力提升”，\r\n轉變為一種內在的“思考力替代”？甚至觸碰到“創造力重塑”的新邊界。向來作為創意到實踐整\r\n合的建築師，面對智能化的建築生產過程，該如何做出調整與因應？本演講分享將就建築與設\r\n計產業如何有效運用圖像生成式AI，加速設計創意與流程創新的各種可能。</p>','Specializes in contemporary architectural criticism, parametric design and digital construction, hybrid (virtual-real) integrated space design, and smart design in sustainability. Academic research and design practice have been committed to exploring how the continuous evolution of contemporary digital and smart technology can affect global and local social culture. Focusing on digital design methods and application theories he tries to construct the meaningful dialogue and dialectical possibility  between Taiwan and the world through architectural discourse, curation and creation.  專長為當代建築評論、參數設計與數位構築、虛實整合空間設計、智慧永續設計，過去幾年教學研究與設計實踐，致力於探索持續進化的當代數位互動與智慧化技術，如何在全球與在地的社會文化與建築產業脈絡下，從概念到實踐挖掘出新的設計觀點、設計方法與應用理論。同時也關注當代建築的發展，嘗試以建築論述、策展與創作方式建構台灣在地性與世界建築思潮的積極對話與辯證的可能。 ','<p>Specializes in contemporary architectural criticism, parametric design and digital construction, hybrid (virtual-real) integrated space design, and smart design in sustainability. Academic research and design practice have been committed to exploring how the continuous evolution of contemporary digital and smart technology can affect global and local social culture. Focusing on digital design methods and application theories he tries to construct the meaningful dialogue and dialectical possibility  between Taiwan and the world through architectural discourse, curation and creation.</p>\r\n\r\n<p>專長為當代建築評論、參數設計與數位構築、虛實整合空間設計、智慧永續設計，過去幾年教學研究與設計實踐，致力於探索持續進化的當代數位互動與智慧化技術，如何在全球與在地的社會文化與建築產業脈絡下，從概念到實踐挖掘出新的設計觀點、設計方法與應用理論。同時也關注當代建築的發展，嘗試以建築論述、策展與創作方式建構台灣在地性與世界建築思潮的積極對話與辯證的可能。</p>',NULL,'','','Tunghai University\r','副教授',NULL),(24,0,9999,'AI','鄭生懋','Thomas Cheng','thomas-cheng','Challenges and Opportunities of Machine Tool Industry in Taiwan ','中文','yes','X','Victor Taichung ','General Management Division / Manager','/img/speaker/1689e304.png',NULL,NULL,NULL,'',NULL,'鄭生懋，清華物理與智慧製造學程雙碩士，曾任職於台積電擔任製程工程師，移居台中後轉戰工具機產業，目前任職於台中精機擔任總經理室經理。參與精機公司新廠產線佈建、資訊系統整合、工具機產品整合技術開發等重大專案。在底蘊深厚的工具機產業中，看到台灣機械產業的美麗與憂愁，在大環境競爭加劇的現在與未來，始終相信以技術與管理為雙軸核心，在台灣製造業的跨業合作與AI賦能的加速下，台灣機械產業定能轉型成功更上層樓。','',NULL,'','','VICTOR TAICHUNG\r','經理',NULL),(25,0,9999,'AI','陳昱中','Yuchung Chen','yuchung-chen','The Practice Principles of Smart Manufacturing','中文','yes','V','eCloudvalley Digital Technology','TW Dept. Technical Director','/img/speaker/23ca8a24.jpg',NULL,NULL,NULL,'While the value of generative AI and related applications is well-known, many fields have not fully leveraged AI due to challenges in implementation. The manufacturing industry, in particular, faces issues with OT/IT integration and data collection. In this presentation, we will share how ECV\'s expertise in building OT data collection platforms and leverage cloud services to accelerate service development, making it easier to implement AI solutions.   儘管生成式AI及其他相關應用的價值廣為人知，但由於落地的種種挑戰，仍有許多場域尚未利用AI創造效益，尤其是製造業更會遇到許多OT/IT整合問題及資料收集挑戰。此次演講我們將藉由ECV在IoT領域的專業與導入經驗，分享如何建構現場資料收集的平台，以及利用雲端服務加速服務發展，讓倡議者可以更好的將AI方案落地。',NULL,'Yu Chung is responsible for technical pre-sales and service delivery for eCloudvalley Taiwan. Leveraging eCloudvalley\'s leading expertise and practical experience in Asia, he assists businesses in planning their cloud strategies and provides end-to-end lifecycle services from migration to continuous optimization.  Yu Chung has been involved in various teams at eCloudvalley, including MSP services, platform development, and core processes. He has participated in eCloudvalley\'s rapid growth journey from Taiwan to 10+ global regions and has experience serving hundreds of enterprise clients.','<p>Yu Chung is responsible for technical pre-sales and service delivery for eCloudvalley Taiwan. Leveraging eCloudvalley\\\'s leading expertise and practical experience in Asia, he assists businesses in planning their cloud strategies and provides end-to-end lifecycle services from migration to continuous optimization.</p>\r\n\r\n<p>Yu Chung has been involved in various teams at eCloudvalley, including MSP services, platform development, and core processes. He has participated in eCloudvalley\\\'s rapid growth journey from Taiwan to 10+ global regions and has experience serving hundreds of enterprise clients.</p>','https://www.linkedin.com/in/yuchung-chen-a60219117/','','','eCloudvalley Digital Technology\r','台灣區技術總監',NULL),(26,0,9999,'AI','趙新民','Shin-Min Chao','shin-min-chao','A Sustainable and Smart Manufacturing for Productivity Improvement','中文','yes','V','AUO Digitech','Executive Vice President ','/img/speaker/e2942050.jpg',NULL,NULL,NULL,'This presentation will sharing AUO\'s experience of digital transformation. We will present the smart green manufacturing services provided by AUO Digitech, including: AIoT, AOI and iAMHS. Through these technologies, the productivity of factory can be effectively improved.  ',NULL,'Dr.Chao graduated from the IE&M of Yuan Ze University. He is currently the EVP of AUO Digitech. Before joining AUO Digitech, he was the CEO of Smile Technology. Dr. Chao’s professional fields are machine vision, pattern recognition, and process improvement.','',NULL,'','','AUO Digitech\r','執行副總經理',NULL),(27,0,9999,'AI','吳振和','Wu, Cheng-Ho','wu-cheng-ho','Cloud Empowerment and Rapid Deployment of Generative AI','中文','no','X','cacaFly','VP of Technology','/img/speaker/043e518f.jpg',NULL,NULL,NULL,'How to leverage the robust resource flexibility of the cloud to enable a more rapid and efficient transformation of Generative AI innovation into tangible products or services, and to realize quick deployment of applications through the cloud framework! 如何利用雲端的強大資源彈性，使生成式AI的創新更快速、更有效地轉化為實際產品或服務，並通過雲端框架實現應用的快速落地！','<p>How to leverage the robust resource flexibility of the cloud to enable a more rapid and efficient transformation of Generative AI innovation into tangible products or services, and to realize quick deployment of applications through the cloud framework!</p>\r\n<p>如何利用雲端的強大資源彈性，使生成式AI的創新更快速、更有效地轉化為實際產品或服務，並通過雲端框架實現應用的快速落地！</p>','cacaFly VP, Technolog、台科大兼任教師。曾開發數百萬下載、Google、Apple排行榜熱門APP及數百大億數據流量網路服務。TEDx、AWS SUMMIT  講者、台灣人工智慧年會講者。','',NULL,'','','cacaFly\r','技術副總',NULL),(28,0,9999,'AI','孫弘岳','Hung-Yue Suen','hung-yue-suen','Harnessing GAI: Revolutionizing HR Practices','中文','yes','V','National Taiwan Normal University','echnology Application And Human Resource Development / Distinguished Associate Professor','/img/speaker/dc28f7fc.jpg',NULL,NULL,NULL,'Today, we\'re on the brink of an extraordinary revelation that promises to reshape the very core of Human Resources (HR) practices. The captivating force of Generative AI, or GAI, isn\'t just a concept; it\'s a strategic enabler for HR professionals like us. We\'ve gathered here to embark on a journey through the practical landscape of harnessing GAI\'s potential.',NULL,'With prior experience as an HR Director in financial holding companies, Dr. Suen enriches his academic pursuits with practical insights. His role involved overseeing HR functions internationally and domestically. Dr. Suen\'s research focuses on Affective Computing, Human-Computer Interaction, and the application of Artificial Intelligence (AI) in Human Resources. His work has been featured in esteemed international journals.','','https://www.linkedin.com/in/collinsuen/','','','National Taiwan Normal University\r','副教授',NULL),(29,0,9999,'AI','李怡志','Richy Li','richy-li','Unlocking Innovation with LLM: Integrating Prompt Engineering in Product Development','中文','yes','V','National Chengchi University','Assistant Prof., Dept. of Journalism','/img/speaker/df8d9abd.png',NULL,NULL,NULL,'In this session, product planning is an example to demonstrate how large language models can take on multiple roles and guide project completion through ChatGPT. The speaker will demonstrate the process from chaos to order, guiding ChatGPT to propose operational workflow and thinking frameworks, present counter arguments, and act as a discussant.','<p>In this session, product planning is an example to demonstrate how large language models can take on multiple roles and guide project completion through ChatGPT.</p>\r\n<p>The speaker will demonstrate the process from chaos to order, guiding ChatGPT to propose operational workflow and thinking frameworks, present counter arguments, and act as a discussant.</p>','Richy Li is currently a faculty member at the Department of Journalism, National Chengchi University, where he teaches Information Visualization, Internet Product Development, and New Feature Reporting. His research focuses on the impact of technology on news organizations and innovation within the newsroom. Starting in 2023, he has incorporated Generative AI into several courses. He has previously served as the Editor-in-Chief at Yahoo Taiwan, and his work has been honored with a Digital Golden Tripod Award, as well as a nomination for the Online Journalism Awards in the USA.','',NULL,'','','National Chengchi University\r','助理教授',NULL),(30,0,9999,'AI','許凱程','Kai-Cheng Hsu','kai-cheng-hsu','Transforming Smart Healthcare with Generative AI','中文','yes','V','China Medical University Hospital','Artificial Intelligence Center / Director','/img/speaker/1dd4b08a.jpg',NULL,NULL,NULL,'The speech provided a compelling insight into the potential of Generative AI to revolutionize healthcare, focusing on a pioneering collaboration between the China Medical University Hospital and Microsoft Taiwan.  The gHi System, a groundbreaking AI solution born out of this collaboration, is globally recognized as the first generative AI medical system constructed in Chinese. Utilizing Microsoft\'s Azure platform and the cutting-edge language model GPT-4, the gHi System significantly reduces time spent on medical record-keeping, improving administrative efficiency and freeing medical professionals to focus more on patient care.  The speech further highlighted how generative AI can transcend record-keeping by aiding in predicting disease patterns, personalizing treatment plans, and facilitating communication in patient care.  In summary, the speech painted a future of smart healthcare where the intersection of Generative AI and medicine promotes more efficient, effective, and patient-centric medical practices. It highlighted the impressive achievements of collaborative technological innovation, opening up a conversation on the future of smart healthcare.','<p>The speech provided a compelling insight into the potential of Generative AI to revolutionize healthcare, focusing on a pioneering collaboration between the China Medical University Hospital and Microsoft Taiwan.</p>\r\n<p>The gHi System, a groundbreaking AI solution born out of this collaboration, is globally recognized as the first generative AI medical system constructed in Chinese. Utilizing Microsoft\'s Azure platform and the cutting-edge language model GPT-4, the gHi System significantly reduces time spent on medical record-keeping, improving administrative efficiency and freeing medical professionals to focus more on patient care.</p>\r\n<p>The speech further highlighted how generative AI can transcend record-keeping by aiding in predicting disease patterns, personalizing treatment plans, and facilitating communication in patient care.</p>\r\n<p>In summary, the speech painted a future of smart healthcare where the intersection of Generative AI and medicine promotes more efficient, effective, and patient-centric medical practices. It highlighted the impressive achievements of collaborative technological innovation, opening up a conversation on the future of smart healthcare.</p>','Dr. Kai-Cheng Hsu is the Director of the Artificial Intelligence Center (AIC) for Medical Diagnosis at China Medical University Hospital (CMUH) and an Attending Physician at the Neurology Department of CMUH. He acquired a Medical Doctor from National Taiwan University, a Master of Electrical Engineering, and a Ph.D. in Chemical Engineering from National Chung Cheng University. He visited the National Institutes of Health (USA) for Medical Artificial Intelligence training from 2018 to 2020. His areas of research interest include artificial intelligence applications in medical images, biomedical signals, electronic health records, and bioinformatics. His goal is to combine his expertise in medicine and engineering to apply AI to develop products for advancing biomedical technology. He has led AIC to develop dozens of AI algorithms for clinical use in CMUH.','','https://www.cmuh.cmu.edu.tw/Doctor/DoctorInfo?docId=D35842','China Medical University','School of Medicine/ Assistant Professor','China Medical University Hospital\r','主任',NULL),(31,0,9999,'AI','王俊權','Friedman Wang','friedman-wang','The Current State and Future Prospects of AI-Enabled Financial Services','中文','yes','V','Data Intelligence R&D Division','Executive Vice President','/img/speaker/5adeca1a.jpg',NULL,NULL,NULL,'In today’s seminar, we delved into the profound impact of AI technology on financial services. We elucidated the categories of AI and its current state in the Taiwanese financial sector, highlighting its pivotal role in optimizing business processes and enhancing customer service. Through case analyses, we demonstrated how AI fosters more efficient and secure financial solutions. Looking forward, we foresee AI continually driving innovation and progression in the industry.  在今日的研討會中，我們探討了AI技術對金融服務的深刻影響。我們說明了AI的類型和其在台灣金融業的現況，突顯其在優化業務流程和提升客戶服務中的核心角色。透過案例分析，我們展示了AI如何塑造更有效和安全的金融解決方案。展望未來，我們預見AI將持續推動業界的創新和進步。 ',NULL,'中信金控數據暨科技研發處處長，負責集團數據規劃與 AI 科技研發業務，研發成果於外部得到美國 NIST 機構與國際各大學術機構認證具備領先性與創新性，其整合科技落地金融應用的商轉業務模式也屢得 Gartner、IDC 與 WCIT 等全球創新獎項肯定。內部以 +AI 與 AI+ 之雙策略基調，廣泛落地於金控內各個金融場景，涵蓋個人金融業務、法人金融業務、人壽業務、風險管理業務與 HR 業務等。','',NULL,'','','CTBC Holding\r','資深副總',NULL),(32,0,9999,'AI','胡德民','Peter Hu','peter-hu','Opportunities and Methods for Accelerating Enterprise Digital Transformation through Generative AI\r ','中文','yes','X','FarEasTone Telecom','Information & Digital Transformation Technology Executive Vice President','/img/speaker/022da2ac.png',NULL,NULL,NULL,'In this presentation, we will explore how Generative AI can drive and expedite enterprise digital transformation. Discover the potential opportunities and practical methods that Generative AI offers to reshape business processes, enhance customer experiences, and unlock new avenues for innovation. Join us as we delve into the transformative power of Generative AI in the context of today\'s rapidly evolving digital landscape.',NULL,'In August 2021, Mr. Peter joined Far EasTone Telecommunications as the Executive Vice President and Chief Information Officer of the Information and Digital Transformation Technology Group. Peter\'s role encompasses driving the transformation of information services, spearheading the development of next-generation digital user experiences for 5G, and leading the creation of enterprise solutions and consultancy services in the realms of \"Big Data, Artificial Intelligence, and Internet of Things\" under the Far EasTone brand. Additionally, Peter has taken the lead in establishing the Far EasTone Innovation Accelerator. 2021 年 8 月加入遠傳電信，擔任資訊暨數位轉型科技群執行副總經理及資訊長 負責推動資訊服務轉型、5G的新一代數位用戶體驗發展以及遠傳「大人物（大數據、人工智慧、物聯網）」的企業解決方案與顧問服務，並主導成立遠傳新創加速器。 ','<p>In August 2021, Mr. Peter joined Far EasTone Telecommunications as the Executive Vice President and Chief Information Officer of the Information and Digital Transformation Technology Group. Peter\\\'s role encompasses driving the transformation of information services, spearheading the development of next-generation digital user experiences for 5G, and leading the creation of enterprise solutions and consultancy services in the realms of \\\"Big Data, Artificial Intelligence, and Internet of Things\\\" under the Far EasTone brand. Additionally, Peter has taken the lead in establishing the Far EasTone Innovation Accelerator.</p>\r\n<p>2021 年 8 月加入遠傳電信，擔任資訊暨數位轉型科技群執行副總經理及資訊長</p>\r\n<p>負責推動資訊服務轉型、5G的新一代數位用戶體驗發展以及遠傳「大人物（大數據、人工智慧、物聯網）」的企業解決方案與顧問服務，並主導成立遠傳新創加速器。</p>',NULL,'','','FET Telecommunications\r','執行副總經理',NULL),(33,0,9999,'PANEL','侯宜秀','Isabel Hou','isabel-hou','共創以人為本的 AI 治理框架與路徑','中文','yes','簡報33','Taiwan AI Academy Foundation','Secretary General','/img/speaker/1c6c4dd5.jpg',NULL,NULL,NULL,'',NULL,'Isabel Hou is a seasoned attorney focusing on technological innovation and intellectual property law and has served as a legal counsel for various government programs, prestigious companies, and NGOs in Taiwan since 2000. Isabel serves as a committee member of Taiwan’s Open Parliament Multi-stakeholder Forum from 2019-2022.  律師，專注於創新科技、開放資料、開放政府等數位治理議題及相關法律規範。2012 年以來持續參與 g0v 公民科技社群，從中習得「揪團打怪」技能：多方協作推動社會創新。 2017 年協助設立台灣人工智慧學校基金會，2021 年起擔任秘書長，推動課程轉型及開源 AI 平台「風火輪計畫」。 2020-2022 年擔任立法院開放國會委員會民間委員，推動完成台灣立法院首份「開放國會行動方案」。近來與台灣公民社群夥伴協作推動「數位公民素養」行動計畫作為台灣新世代社會基礎建設。','<p>Isabel Hou is a seasoned attorney focusing on technological innovation and intellectual property law and has served as a legal counsel for various government programs, prestigious companies, and NGOs in Taiwan since 2000. Isabel serves as a committee member of Taiwan’s Open Parliament Multi-stakeholder Forum from 2019-2022.</p>\r\n<br>\r\n<p>律師，專注於創新科技、開放資料、開放政府等數位治理議題及相關法律規範。2012 年以來持續參與 g0v 公民科技社群，從中習得「揪團打怪」技能：多方協作推動社會創新。</p>\r\n<p>2017 年協助設立台灣人工智慧學校基金會，2021 年起擔任秘書長，推動課程轉型及開源 AI 平台「風火輪計畫」。</p>\r\n<p>2020-2022 年擔任立法院開放國會委員會民間委員，推動完成台灣立法院首份「開放國會行動方案」。近來與台灣公民社群夥伴協作推動「數位公民素養」行動計畫作為台灣新世代社會基礎建設。</p>','https://en.aiacademy.tw/key-executives/','','','Taiwan AI Academy','秘書長','陳昇瑋紀念講座專家論壇'),(34,0,9999,'PANEL','唐鳳','TANG Feng (Audrey TANG)','tang-feng-audrey-tang','共創以人為本的 AI 治理框架與路徑','中文','no','簡報34','Ministry of Digital Affairs','Minister','/img/speaker/9dc15c5f.jpg',NULL,NULL,NULL,'',NULL,'Audrey Tang is Taiwan’s digital minister in charge of moda (Ministry of Digital Affairs).  Audrey is known for revitalizing the computer languages Perl and Haskell, as well as building the online spreadsheet system EtherCalc in collaboration with Dan Bricklin.  In the public sector, Audrey served on Taiwan national development council’s open data committee and the 12-year basic education curriculum committee; and led the country’s first e-Rulemaking project.  In the private sector, Audrey worked as a consultant with Apple on computational linguistics, with Oxford University Press on crowd lexicography, and with Socialtext on social interaction design.  In the social sector, Audrey actively contributes to g0v (\"gov zero\"), a vibrant community focusing on creating tools for the civil society, with the call to \"fork the government.\"','','https://moda.gov.tw/en/aboutus/principal-officers/minister-tang/991','','','Ministry of Digital Affairs','部長','陳昇瑋紀念講座專家論壇'),(35,0,9999,'PANEL','蔡志宏','Zsehong Tsai','zsehong-tsai','共創以人為本的 AI 治理框架與路徑','中文','yes','簡報35','National Taiwan University (NTU)','Professor','/img/speaker/1fb46077.jpg',NULL,NULL,NULL,'',NULL,'CURRENT POSITION/INSTITUTION  Chair, Taiwan AI Center of Excellence(AICoE), NSTC  Chair, Science & Technology Policy Advisory Office, NSTC Professor, National Taiwan University(NTU)  EDUCATION  Ph.D. in Electrical Engineering, UCLA  M.S. in Electrical Engineering, UCLA  B.S. in Electrical Engineering, NTU  PROFESSIONAL EXPERIENCE  Executive Secretary, Board of Science and Technology, Executive Yuan Independent Director, Chunghwa Telecomm  Member of Technical Staff, AT&T Bell Laboratories  RESEARCH AREAS  Science and Technology Policy, AI, Broadband & Wireless Networking ','<p><span style=\\\"color:#5d2191;\\\">CURRENT POSITION/INSTITUTION</span><br>\r\nChair, Taiwan AI Center of Excellence(AICoE), NSTC<br>\r\nChair, Science & Technology Policy Advisory Office, NSTC Professor, National Taiwan University(NTU)</p>\r\n\r\n<p><span style=\\\"color:#5d2191;\\\">EDUCATION</span><br> \r\nPh.D. in Electrical Engineering, UCLA<br>\r\nM.S. in Electrical Engineering, UCLA<br>\r\nB.S. in Electrical Engineering, NTU</p>\r\n\r\n<p><span style=\\\"color:#5d2191;\\\">PROFESSIONAL EXPERIENCE</span><br>\r\nExecutive Secretary, Board of Science and Technology, Executive Yuan Independent Director, Chunghwa Telecomm<br>\r\nMember of Technical Staff, AT&T Bell Laboratories</p>\r\n\r\n<p><span style=\\\"color:#5d2191;\\\">RESEARCH AREAS</span><br>\r\nScience and Technology Policy, AI, Broadband & Wireless Networking</p>','https://www.twaicoe.org/zsehong-tsai','Science & Technology Policy Advisory Office, NSTC','','NTU','教授','陳昇瑋紀念講座專家論壇'),(36,0,9999,'PANEL','林明仁','Lin, Ming Jen','ming-jen-lin','共創以人為本的 AI 治理框架與路徑','中文','yes','簡報36','National Taiwan University (NTU)','Distinguished Professor, Department of Economics','/img/speaker/fcf96d44.jpg',NULL,NULL,NULL,'',NULL,'Professor Ming-Jen Lin earned his Ph.D. in Economics from the University of Chicago in 2002. His research interests span various fields, including data science and economics, demography and health, law and economics, and labor economics. He places particular emphasis on interdisciplinary collaboration within the social sciences. Currently, he serves as a Distinguished Professor in the Department of Economics at National Taiwan University and holds the position of Chairman of the Taiwan Economic Association. Additionally, he concurrently serves as the Deputy Executive Secretary at the National Science and Technology Office. Furthermore, he has previously held the role of Director at the Division of Humanities and Social Sciences within the National Science and Technology Development Bureau (formerly the Ministry of Science and Technology), where he was responsible for promoting research and development in the fields of humanities and social sciences. He has also served as the Chair of the Department of Economics at National Taiwan University. During his tenure as Director of the Center for Behavioral and Data Science and the Center for Population and Gender Studies at National Taiwan University, he actively promoted the development of interdisciplinary research. ','<p>Professor Ming-Jen Lin earned his Ph.D. in Economics from the University of Chicago in 2002. His research interests span various fields, including data science and economics, demography and health, law and economics, and labor economics. He places particular emphasis on interdisciplinary collaboration within the social sciences. Currently, he serves as a Distinguished Professor in the Department of Economics at National Taiwan University and holds the position of Chairman of the Taiwan Economic Association. Additionally, he concurrently serves as the Deputy Executive Secretary at the National Science and Technology Office.</p>\r\n<p>Furthermore, he has previously held the role of Director at the Division of Humanities and Social Sciences within the National Science and Technology Development Bureau (formerly the Ministry of Science and Technology), where he was responsible for promoting research and development in the fields of humanities and social sciences. He has also served as the Chair of the Department of Economics at National Taiwan University. During his tenure as Director of the Center for Behavioral and Data Science and the Center for Population and Gender Studies at National Taiwan University, he actively promoted the development of interdisciplinary research.</p>','https://economicsatntu.wixsite.com/ming-jen-lin','National Science and Technology Council','Deputy Executive Director, Office of Science and Technology Policy','NTU','特聘教授','陳昇瑋紀念講座專家論壇'),(37,0,9999,'AIK','陸忠立','Allen Lu','allen-lu','Edge AI Application Evolution – Opportunity and Challenge','中文','yes','X','Mediatek','Senior Director ','/img/speaker/2011f6a4.png',NULL,NULL,NULL,'Over the years, edge AI has made significant strides, transitioning from applications like photo classification and face detection to enhancing video and gaming picture quality. The advent of generative AI has further propelled innovation, revolutionizing our life experiences. However, due to intensive computational and memory requirements, current generative AI applications primarily rely on cloud infrastructure. In this presentation, we aim to explore the emerging trend of shifting from a cloud-centric approach to a collaborative cloud-edge paradigm for generative AI technologies. We will delve into the multitude of opportunities and challenges that lie ahead when supporting generative AI on edge devices. This transformation entails a synergetic blend of technological advancements, enhancements in hardware architecture, and the reduction of computational complexities, ultimately enabling the realization of novel generative AI applications.','<p>Over the years, edge AI has made significant strides, transitioning from applications like photo classification and face detection to enhancing video and gaming picture quality. The advent of generative AI has further propelled innovation, revolutionizing our life experiences. However, due to intensive computational and memory requirements, current generative AI applications primarily rely on cloud infrastructure.</p>\r\n\r\n<p>In this presentation, we aim to explore the emerging trend of shifting from a cloud-centric approach to a collaborative cloud-edge paradigm for generative AI technologies. We will delve into the multitude of opportunities and challenges that lie ahead when supporting generative AI on edge devices. This transformation entails a synergetic blend of technological advancements, enhancements in hardware architecture, and the reduction of computational complexities, ultimately enabling the realization of novel generative AI applications.</p>\r\n','Dr. Allen Lu, Senior Director, MediaTek Inc.  Dr. Lu is the Senior Director of Computing and Artificial intelligence Technology Group at MediaTek. He is responsible for the ML/DL algorithm/tool development for mobile phone, camera, tablet, and TV products.  Prior to MediaTek, Dr. Lu served as the General Manager of Video IoT (iVoT) Business Unit at Novatek. He was responsible for business and technology planning and execution.  Prior to Novatek, Dr. Lu funded Afatek, a fabless company developing RF, digital modulator, and demodulator chips.  Afatek was acquired by iTE in 2008. Dr. Lu worked in Silicon Valley from 1997-2002. He joined the Excess Bandwidth Corp. specializing in signal processing.  Excess Bandwidth Corp. was acquired by Virata Corp (now Conexant) in 2000.  Dr. Lu was a member of technical staff at Hewlett Packard prior to Excess Bandwidth.       Dr. Lu received his M.S. and Ph.D. in Electrical Engineering from Stanford University.  ','<p>Dr. Allen Lu, Senior Director, MediaTek Inc. </p>\r\n<p>Dr. Lu is the Senior Director of Computing and Artificial intelligence Technology Group at MediaTek. He is responsible for the ML/DL algorithm/tool development for mobile phone, camera, tablet, and TV products.  Prior to MediaTek, Dr. Lu served as the General Manager of Video IoT (iVoT) Business Unit at Novatek. He was responsible for business and technology planning and execution.  Prior to Novatek, Dr. Lu funded Afatek, a fabless company developing RF, digital modulator, and demodulator chips.  Afatek was acquired by iTE in 2008.</p>\r\n<p>Dr. Lu worked in Silicon Valley from 1997-2002. He joined the Excess Bandwidth Corp. specializing in signal processing.  Excess Bandwidth Corp. was acquired by Virata Corp (now Conexant) in 2000.  Dr. Lu was a member of technical staff at Hewlett Packard prior to Excess Bandwidth.      </p>\r\n<p>Dr. Lu received his M.S. and Ph.D. in Electrical Engineering from Stanford University. </p>',NULL,'Compute and Artificial Intelligence Department ','','MediaTek','資深處長','KEYNOTE '),(38,0,9999,'AI','郭秉宸','Benjamin Kuo ','benjamin-kuo-ai','寓兵於農：百工百業加速 AI 化的策略','中文','yes','V','Taiwan AI Academy','Vice President for Industry-Academia Collaboration','/img/speaker/bd7ef620.jpg',NULL,NULL,NULL,'',NULL,'Benjamin Kuo is currently the Vice President for Industry-Academia Collaboration and has over 25 years of industry experience and consulting expertise. He focuses on building an AI-centric innovation ecosystem that connects and synergizes industry, venture capital, academia, and research institute. He aims to advance Taiwan’s AI excellence and accelerate the development and strength of Taiwan’s industries with AI.   Benjamin was a Senior Director at KPMG Taiwan, and leading the smart manufacturing team, serving many medium and large customers, and long-term involvement in the three major markets of industrial industry, family business management, and start-up & innovation services.  Benjamin is also a Ph.D candidate in the Interdisciplinary International Doctoral Program at National Tsing Hua University. He already holds dual master’s degrees in materials science and technology innovation management.  郭秉宸現為台灣人工智慧學校產學長，並且為清華大學跨域國際博士學程博士候選人，擁有材料科學與科技管理雙碩士，25 年以上的產業經驗與管顧專長。 聚焦於建構以 AI 為中心的產學研創生態系，鏈結能量並且促動產生綜效，推進台灣 AI 的卓越進展，讓台灣的產業因為有 AI 而加速發展並且強大。  曾任：KPMG 臺灣所顧問部 企業績效與創新科技協理，長期投入在工業產業、家族事業經營、新創與創新服務三大市場。 工研院企劃與研發處專案副組長，擔任院長室高級幕僚 新創企業經營企劃經理  專長：產業 AI 化策略與行動方案擬定、智慧製造、項目組合管理 (Portfolio management)、產品開發管理 (Product development management)、企業營運管理 (Business operation)、企業對企業行銷與商機開發 (B2B marketing & BD)、建立企業生態系與策略聯盟 (Ecosystem & Strategic alliance)、新事業發展、經營管理策略制定、智慧製造策略架構、數位決策分析與管理、企業營運模式校準、企業二代傳承接班。','<p>Benjamin Kuo is currently the Vice President for Industry-Academia Collaboration and has over 25 years of industry experience and consulting expertise. He focuses on building an AI-centric innovation ecosystem that connects and synergizes industry, venture capital, academia, and research institute. He aims to advance Taiwan’s AI excellence and accelerate the development and strength of Taiwan’s industries with AI. </p>\r\n\r\n<p>Benjamin was a Senior Director at KPMG Taiwan, and leading the smart manufacturing team, serving many medium and large customers, and long-term involvement in the three major markets of industrial industry, family business management, and start-up & innovation services.</p>\r\n\r\n<p>Benjamin is also a Ph.D candidate in the Interdisciplinary International Doctoral Program at National Tsing Hua University. He already holds dual master’s degrees in materials science and technology innovation management.</p>\r\n\r\n<p>郭秉宸現為台灣人工智慧學校產學長，並且為清華大學跨域國際博士學程博士候選人，擁有材料科學與科技管理雙碩士，25 年以上的產業經驗與管顧專長。 聚焦於建構以 AI 為中心的產學研創生態系，鏈結能量並且促動產生綜效，推進台灣 AI 的卓越進展，讓台灣的產業因為有 AI 而加速發展並且強大。</p>\r\n\r\n<p>曾任：KPMG 臺灣所顧問部 企業績效與創新科技協理，長期投入在工業產業、家族事業經營、新創與創新服務三大市場。 工研院企劃與研發處專案副組長，擔任院長室高級幕僚 新創企業經營企劃經理</p>\r\n\r\n<p>專長：產業 AI 化策略與行動方案擬定、智慧製造、項目組合管理 (Portfolio management)、產品開發管理 (Product development management)、企業營運管理 (Business operation)、企業對企業行銷與商機開發 (B2B marketing & BD)、建立企業生態系與策略聯盟 (Ecosystem & Strategic alliance)、新事業發展、經營管理策略制定、智慧製造策略架構、數位決策分析與管理、企業營運模式校準、企業二代傳承接班。</p>',NULL,'','','Taiwan AI Academy\r','產學長',NULL),(39,0,9999,'AI','李宏毅','Hung-yi Lee','hung-yi-lee','Towards a Speech Version of ChatGPT','中文','yes','V','National Taiwan University (NTU)','Associate Professor, Department of Electrical Engineering','/img/speaker/9ed5ae74.jpg',NULL,NULL,NULL,'Over the past few months, the capabilities of large language models (LLM) like ChatGPT have sparked widespread discussion. They possess a general processing ability, and they can often accomplish the desired tasks with the right instructions. Speech, teeming with rich and hierarchical information, offers different needs for diverse tasks. How far are we from the speech version of ChatGPT? What are we still missing for the birth of the speech ChatGPT? In this talk, I will share a series of the latest research findings in speech LM that could potentially lead us to the speech version of ChatGPT and discuss current challenges and potential solutions.',NULL,'Hung-yi Lee (李宏毅) is a professor of the Department of Electrical Engineering of National Taiwan University (NTU), with a joint appointment at the Department of Computer Science & Information Engineering of the university. His recent research focuses on developing technology that can reduce the requirement of annotated data for speech processing and natural language processing. He won Salesforce Research Deep Learning Grant in 2019, AWS ML Research Award in 2020, Outstanding Young Engineer Award from The Chinese Institute of Electrical Engineering in 2018, Young Scholar Innovation Award from Foundation for the Advancement of Outstanding Scholarship in 2019, Ta-You Wu Memorial Award from Ministry of Science and Technology of Taiwan in 2019, and The 59th Ten Outstanding Young Person Award in Science and Technology Research & Development of Taiwan. He owns a YouTube channel teaching deep learning in Mandarin with about 160k Subscribers.','','https://www.ee.ntu.edu.tw/profile1.php?teacher_id=901182&p=3','','','National Taiwan University\r','副教授',NULL),(40,0,9999,'AI','楊佳玲','Chia-Lin Yang','chia-lin-yang','Memory-Centric Computing in AI Era','中文','no','X','National Taiwan University (NTU)','Dept. of Computer Science and Information Engineering, Professor','/img/speaker/1171d3d9.jpg',NULL,NULL,NULL,'Deep learning techniques have demonstrated great success in many application domains such as computer vision, speech recognition, and natural language processing. It has been shown that the memory subsystem is the main bottleneck in executing DNN applications, including the capacity and bandwidth walls.  This talk covers recent researches for tackling the memory wall challenges.  ',NULL,'Chia-Lin Yang received the Ph.D. degree from Duke University in 2001. Dr. Yang joined the Department of Computer Science and Information Engineering at NTU (National Taiwan University) in 2001. She joined the Department of Computer Science and Information Engineering at National Taiwan University at 2001. She is currently the Deputy Executive Director of Office of Science and Technology Policy at NSTC (National Science and Technology Policy). She was the Director of the Delta-NTU Joint Research Center at NTU from 2020 to 2023 and the Director of Graduate Institute of Networking and Multimedia at NTU from 2016 to 2019. Dr. Yang’s research focus is in the area of the system-level design methodology and computer architecture, with emphasis on the low-power system and memory hierarchy/SSD storage. Dr. Yang is currently serving as the Editor-in-Chief for IEEE Computer Architecture Letters, and the Program Co-chair for DAC 2024. ','','https://www.csie.ntu.edu.tw/~yangc/','','','National Taiwan University','教授',NULL),(41,0,9999,'AI','陳佩君','Trista Chen','trista-chen','On Wings of AI with Copilot','中文','yes','X','Microsoft','Director, AI Research Center','/img/speaker/c92f0e65.jpg',NULL,NULL,NULL,'Wings are a symbol of freedom, exploration, and discovery. They enable us to fly above the clouds, travel across vast distances, and reach new horizons. Artificial intelligence (AI) is like a pair of wings that frees us from mundane tasks and enables us to achieve things we never imagined possible. It changes the way we work, learn, and create. In this talk, we will unveil the secret behind the recent AI breakthroughs and how they are just the dawn of AI’s fusion into every facet of life. We will discuss the prospects and challenges of this new generative AI era that aims to unleash our creativity and potential.',NULL,'Trista is an AI scientist and tech executive. As the Director of the AI Research Center at Microsoft, her research focuses on computer vision, multimodal large language models, and health AI. Trista has published over 30 top-tier journals and conference publications and holds/filed 110 patents. Her research is internationally recognized, including winning the world championship in the USAID Intelligent Forecasting Competition for advancing the health of people in the Ivory Coast and receiving the CVPR workshop best paper award. Prior to joining Microsoft, Trista held leadership positions at Inventec, Intel, and Nvidia and successfully led two startups from incubation to acquisition. As the Chief AI Officer at Inventec, she led the team to obtain one of Taiwan’s first ISO-13485-based QMS for a novel AI Software as a Medical Device (SaMD) based on her original medical research. She also helped Inventec develop the industry’s first computer vision inspection system and innovate its supply chain with USAID world championship technology. At Intel, Trista facilitated the development of OpenCV - the world’s most widely adopted computer vision software with over 18 million downloads as of 2021. At Nvidia, she architected Nvidia\'s first video processor. Trista holds a Ph.D. from Carnegie Mellon University and an M.S. and B.S. from National Tsing-Hua University.','','https://tw.linkedin.com/in/tristachen?original_referer=https%3A%2F%2Fwww.google.com%2F','','','Microsoft\r','人工智慧研發中心技術長',NULL),(42,0,9999,'AI','簡宏偉','Howard Jyan','howard-jyan','Establish of Trustworthy AI: Opportunities and Challengs','中文','yes','V','Deloitte & Touche','Partner, Risk Advisory','/img/speaker/2e054e3b.jpg',NULL,NULL,NULL,'In this session, we will focus on the risk of AI, share the framework of trustworthy of AI, especially for the usage of enterprise point of view.  AI has become one of hottest topics in the enterprises, what are the risks and how to use to improve services to clients.  We will discuss some of risks both from internal and external of an enterprise, and propose suggestions to help enterprise to balance of information protection and better services.  Finally, we will share the framework of trustworthy AI, the elements of this framework, and the future development.',NULL,'Howard Jyan is the Partner of Risk Advisory Services at Deloitte. He specialized in Cyber security, network security, ISMS audits, regulation of cyber security, information security governance, workflow transformation, and organizational transformation. He also has extensive experience in public sector information practices and cross-agency coordination. ','',NULL,'','','Deloitte\r','執行副總經理',NULL),(43,0,9999,'AI','劉嘉凱','Chia-Kai Liu','chia-kai-liu','Building Trustworthy Digital Twins of Organizations: A Process-Oriented Experiment','中文','no','X','DSP, Inc.','CEO','/img/speaker/bf62f577.png',NULL,NULL,NULL,'Digital twins of organizations (DTOs) can be used to model, simulate, and analyze various scenarios, enabling organizations to identify bottlenecks, inefficiencies, and opportunities for improvement. However, building trustworthy DTOs is challenging, as they must be reliable, robust, fair, ethical, transparent, and explainable.   This presentation will discuss the challenges and opportunities of building trustworthy DTOs. We will present the early results of a life-critical use case experiment, in which we created a digital twin prototype, with the objectives of being not only accurate but also dependable. We will discuss how this innovation can be used to transforms decision-making, risk assessment, and predictive modeling in crucial contexts. ','<p>Digital twins of organizations (DTOs) can be used to model, simulate, and analyze various scenarios, enabling organizations to identify bottlenecks, inefficiencies, and opportunities for improvement. However, building trustworthy DTOs is challenging, as they must be reliable, robust, fair, ethical, transparent, and explainable. </p><p>This presentation will discuss the challenges and opportunities of building trustworthy DTOs. We will present the early results of a life-critical use case experiment, in which we created a digital twin prototype, with the objectives of being not only accurate but also dependable. We will discuss how this innovation can be used to transforms decision-making, risk assessment, and predictive modeling in crucial contexts. </p>','Chia-Kai Liu is the CEO of DSP, Inc.,  a consulting firm specializing in leveraging artificial intelligence to transform business and public sector operations. He is also the co-founder of Data for Social Good, a philanthropic platform fostering collaboration among governmental bodies, non-profits, and data experts to accelerate social innovation. Mr. Liu is a strong advocate for data-driven decision-making, advancing the cause of sustainable development objectives.','',NULL,'','','DSP\r','執行長',NULL),(44,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(45,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(46,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(47,0,9999,'AI','趙佑錫','Erick Chao','erick-chao','The Evolution of AI in Chip Design','中文','yes','X','Cadence Design Systems','Sr Software Architect ','/img/speaker/b76473bf.jpg',NULL,NULL,NULL,'Generative AI has emerged as an outstanding and versatile solution. Its rapid advancements and deep impacts have exceeded many other technological breakthroughs, delivering substantial benefits to numerous industries. Within the semiconductor industry, generative AI integrated into EDA tools has solidified its position by offering unparalleled optimization capabilities.\r \r Indeed, these cutting-edge tools have demonstrated the capacity to change the rules of the game, enabling teams engaged in chip and system development to significantly enhance performance. Furthermore, they play a critical role in boosting engineering productivity and simplifying complex design convergence processes. In this presentation, we will introduce how EDA’s evolution through AI and how to leverage this transformative power into chip design and implementation.',NULL,'With 23 years of extensive experience in IC design, implementation, and EDA development, I have a profound understanding of user requirements and software development in Electronic Design Automation (EDA). My journey in AI/ML began with graduation from the 1st Hsinchu manager class at Taiwan AI Academy (AIA). At the same time, I assumed a role as a ML architect within a top number 1 IC fabless company in Taiwan. Transitioning to Cadence Design Systems, I took the role of leading RD team in both Hsinchu and Shanghai. My perspective is all-encompassing, spanning from that of an adept end-user to that of a contributor to EDA solution development empowered by AI/ML technologies. At present, I am entrusted with the leadership of one of Cerebrus RD teams, a division responsible for the AI-driven production within Cadence Design Systems.','',NULL,'ML INFRA','','Cadence\r','資深架構師',NULL),(48,0,9999,'AI','唐文力','Luba Tang','luba-tang','Neural-network Processing Unit Hardware-software Co-design IP ','中文','yes','V','Skymizer','CEO','/img/speaker/6bf47417.jpg',NULL,NULL,NULL,'Large language models (LLMs) have become an increasingly prominent feature in various computing platforms, such as data centers, smartphones, and microcontrollers. As such, their potential applications in both human-to-machine interfaces (HMIs) and machine-to-machine interfaces (M2MI) have been extensively studied and discussed. However, implementing hyper-scale LLMs on heterogeneous multicore System-on-Chips (SoCs) poses significant challenges. In this talk, we will discuss the key challenges, including issues related to hardware/software interfaces, verification, and SoC architecture exploration. At the end of this talk, we will propose a practical workflow and corresponding solutions we’ve applied in many cases. And see how our standard tool - ONNC - is used in the workflow.  大型語言模型（LLM）已成為各種計算平台（例如資料中心、智慧型手機和微控制器）中日益突出的功能。因此，它們在人機介面（HMI）和機器對機器介面（M2MI）中的潛在應用已被廣泛研究和討論。然而，在異質多核晶片上系統（SoC）上實現大型語言模型（LLM）面臨著重大挑戰。在本次演講中，我們將討論關鍵挑戰，包括與硬體/軟體介面、驗證和SoC架構探索相關的問題。在本次演講的最後，我們將提出一個實用的架構以及我們在許多案例中應用的解決方案。並了解我們的標準工具 - ONNC - 如何在架構中使用。','<p>Large language models (LLMs) have become an increasingly prominent feature in various computing platforms, such as data centers, smartphones, and microcontrollers. As such, their potential applications in both human-to-machine interfaces (HMIs) and machine-to-machine interfaces (M2MI) have been extensively studied and discussed. However, implementing hyper-scale LLMs on heterogeneous multicore System-on-Chips (SoCs) poses significant challenges. In this talk, we will discuss the key challenges, including issues related to hardware/software interfaces, verification, and SoC architecture exploration. At the end of this talk, we will propose a practical workflow and corresponding solutions we’ve applied in many cases. And see how our standard tool - ONNC - is used in the workflow.</p>\r\n\r\n<p>大型語言模型（LLM）已成為各種計算平台（例如資料中心、智慧型手機和微控制器）中日益突出的功能。因此，它們在人機介面（HMI）和機器對機器介面（M2MI）中的潛在應用已被廣泛研究和討論。然而，在異質多核晶片上系統（SoC）上實現大型語言模型（LLM）面臨著重大挑戰。在本次演講中，我們將討論關鍵挑戰，包括與硬體/軟體介面、驗證和SoC架構探索相關的問題。在本次演講的最後，我們將提出一個實用的架構以及我們在許多案例中應用的解決方案。並了解我們的標準工具 - ONNC - 如何在架構中使用。</p>','Luba Tang is the founder and CEO of Skymizer Taiwan Inc., which is in the business of providing system software to IC design teams. Skymizer’s system software solutions enable AI-on-Chip design houses to automate AI application development, improve system performance, and optimize inference accuracy. Luba Tang’s research interests include electronic system level (ESL) design, system software, and neural networks. He had focused on iterative compilers, ahead-of-time compilers, link-time optimization, neural network compilation, and neural network optimization. His most recent work focuses on exploiting various types of parallelism from different accelerators in a hyper-scale system-on-chip. ','',NULL,'','','Skymizer\r','創辦人',NULL),(49,0,9999,'AI','邱銘彰','Jeremy Chiu','jeremy-chiu','Unleashing the Cyber Magic: The Future of Blue Team Defense ','中文','yes','X','CyCraft','Founder','/img/speaker/2aceecb0.png',NULL,NULL,NULL,'As a blue team on the defense side, we approach cybersecurity with different perspectives compared to the red team. Our considerations go beyond accuracy in handling large-scale data; we also prioritize compliance with government cybersecurity regulations, response time, and cost-effectiveness. Throughout our journey, our team has extensively researched using Machine Learning automation in the investigation of large-scale cybersecurity incidents. We have integrated AI into various analytical aspects, from endpoint event correlation and Cmdline analysis using CmdGPT to an AI virtual analyst that automatically generates forensic reports.  Starting last year, we introduced a new generation of large-scale language models into our blue team AI assistant, enabling automated cybersecurity incident handling and case management. In this presentation, we will share our practical experiences and exclusive insights on how cybersecurity teams can leverage AI effectively, along with showcasing real-life case studies.  作為防禦方的藍隊有許多與紅隊切入角度不同的思維，不但需要考慮到大規模資料量下的準確度，為了符合政府的資安規範，也更加注重反應時間與成本。一直以來，我們團隊對於大規模的資安事件，在調查中使用 Machine learning 自動化方法做了許多研究，將 AI 導入到各個分析面向，從端點事件關聯、分析 Cmdline 的 CmdGPT，以及 AI 虛擬分析師自動產生鑑識報告，而到去年開始，我們為藍隊 AI 助手導入了新一代的大型語言模型，以進行自動資安事件處理與自動案件管理。這場演講中，將透過我們的實務經驗，獨家分享資安團隊該如何正確使用 AI，並分享實際的案例。','<p>As a blue team on the defense side, we approach cybersecurity with different perspectives compared to the red team. Our considerations go beyond accuracy in handling large-scale data; we also prioritize compliance with government cybersecurity regulations, response time, and cost-effectiveness. Throughout our journey, our team has extensively researched using Machine Learning automation in the investigation of large-scale cybersecurity incidents. We have integrated AI into various analytical aspects, from endpoint event correlation and Cmdline analysis using CmdGPT to an AI virtual analyst that automatically generates forensic reports.</p>\r\n<p>Starting last year, we introduced a new generation of large-scale language models into our blue team AI assistant, enabling automated cybersecurity incident handling and case management. In this presentation, we will share our practical experiences and exclusive insights on how cybersecurity teams can leverage AI effectively, along with showcasing real-life case studies.</p>\r\n<p>作為防禦方的藍隊有許多與紅隊切入角度不同的思維，不但需要考慮到大規模資料量下的準確度，為了符合政府的資安規範，也更加注重反應時間與成本。一直以來，我們團隊對於大規模的資安事件，在調查中使用 Machine learning 自動化方法做了許多研究，將 AI 導入到各個分析面向，從端點事件關聯、分析 Cmdline 的 CmdGPT，以及 AI 虛擬分析師自動產生鑑識報告，而到去年開始，我們為藍隊 AI 助手導入了新一代的大型語言模型，以進行自動資安事件處理與自動案件管理。這場演講中，將透過我們的實務經驗，獨家分享資安團隊該如何正確使用 AI，並分享實際的案例。</p>','Founder of CyCraft, with over 15 years of expertise in cybersecurity research, actively engaged in Taiwan\'s cybersecurity technology community. Specializing in developing automated analysis systems, hacker activity analysis, malicious program analysis, and machine learning algorithms. Has presented professional cybersecurity research at various internationally renowned conferences such as Black Hat, DEFCON, SyScan, HITCON, FIRST, AVTokyo, HTICA, OWASP Asia, and iThome CYBERSEC. Proficient in delivering humorous and lively speeches to impart cybersecurity knowledge.  As a prominent serial entrepreneur in Taiwan\'s cybersecurity industry, co-founded the first startup dedicated to developing APT defense products in 2011 with Wu Ming-wei (Benson). In 2014, the company received recognition and acquisition from an Israeli cybersecurity company listed on the NASDAQ. Currently, the CyCraft team focuses on the integration of artificial intelligence and cybersecurity technology.  CyCraft 創辦人，超過 15 年的資安技術研究專家，活耀於台灣的資安技術社群，以開發自動化分析系統、駭客活動分析、惡意程式分析、機器學習演算法為主要研究範疇，多次在國際知名研討會發表專業的資安技術研究，如 Black Hat、DEFCON、SyScan、HITCON、FIRST、AVTokyo、HTICA、OWASP Asia 與 iThome CYBERSEC 等，擅長透過詼諧生動的演講傳授資安知識。而身為臺灣資安界著名的連續創業者，曾於 2011 年與吳明蔚 (Benson) 共同創立臺灣第一家專門研發 APT 防禦產品的新創公司，並在 2014 年受到美國 NASDAQ 的以色列資安公司肯定與併購。目前創辦的 CyCraft 團隊則專注在人工智慧與資安科技領域的結合上。','<p>Founder of CyCraft, with over 15 years of expertise in cybersecurity research, actively engaged in Taiwan\\\'s cybersecurity technology community. Specializing in developing automated analysis systems, hacker activity analysis, malicious program analysis, and machine learning algorithms. Has presented professional cybersecurity research at various internationally renowned conferences such as Black Hat, DEFCON, SyScan, HITCON, FIRST, AVTokyo, HTICA, OWASP Asia, and iThome CYBERSEC. Proficient in delivering humorous and lively speeches to impart cybersecurity knowledge.</p>\r\n\r\n<p>As a prominent serial entrepreneur in Taiwan\\\'s cybersecurity industry, co-founded the first startup dedicated to developing APT defense products in 2011 with Wu Ming-wei (Benson). In 2014, the company received recognition and acquisition from an Israeli cybersecurity company listed on the NASDAQ. Currently, the CyCraft team focuses on the integration of artificial intelligence and cybersecurity technology.</p>\r\n\r\n<p>CyCraft 創辦人，超過 15 年的資安技術研究專家，活耀於台灣的資安技術社群，以開發自動化分析系統、駭客活動分析、惡意程式分析、機器學習演算法為主要研究範疇，多次在國際知名研討會發表專業的資安技術研究，如 Black Hat、DEFCON、SyScan、HITCON、FIRST、AVTokyo、HTICA、OWASP Asia 與 iThome CYBERSEC 等，擅長透過詼諧生動的演講傳授資安知識。而身為臺灣資安界著名的連續創業者，曾於 2011 年與吳明蔚 (Benson) 共同創立臺灣第一家專門研發 APT 防禦產品的新創公司，並在 2014 年受到美國 NASDAQ 的以色列資安公司肯定與併購。目前創辦的 CyCraft 團隊則專注在人工智慧與資安科技領域的結合上。</p>','https://cyber.ithome.com.tw/2023/speaker-page/101','','','CyCraft Technology','創辦人',NULL),(50,0,9999,'AI','黃俊穎','Chun-Ying Huang','chun-ying-huang','Generative AI: Challenges and Opportunities for System Security','中文','yes','X','National Yang Ming Chiao Tung University','Institute of Network Engineering / Director','/img/speaker/096012a8.png',NULL,NULL,'','In recent years, generative AI technology has shown impressive performance in various fields such as images, videos, speech, and text. With the maturation of these technologies, many industries have begun adopting generative AI techniques to reduce the human resource costs required for technical development. This includes tasks related to software development and security analysis. In this presentation, we will introduce how generative AI technology is utilized to assist in applications related to software development and security analysis. We will also discuss the risks and challenges that may arise from the integration of AI. 近年來生成式AI技術在影像、視訊、語音、文字等領域都有讓人驚豔的表現。而隨著技術發展的成熟，許多產業也開始導入生成式AI的技術，以降低技術開發所需的人力成本，這也包括軟體開發和安全分析相關工作。在這個分享裡，我們將介紹軟體開發和軟體安全分析相關應用如何運用AI技術進行輔助，以及導入AI可能會遇到的風險和挑戰。','<p>In recent years, generative AI technology has shown impressive performance in various fields such as images, videos, speech, and text. With the maturation of these technologies, many industries have begun adopting generative AI techniques to reduce the human resource costs required for technical development. This includes tasks related to software development and security analysis. In this presentation, we will introduce how generative AI technology is utilized to assist in applications related to software development and security analysis. We will also discuss the risks and challenges that may arise from the integration of AI.</p>\r\n<p>近年來生成式AI技術在影像、視訊、語音、文字等領域都有讓人驚豔的表現。而隨著技術發展的成熟，許多產業也開始導入生成式AI的技術，以降低技術開發所需的人力成本，這也包括軟體開發和安全分析相關工作。在這個分享裡，我們將介紹軟體開發和軟體安全分析相關應用如何運用AI技術進行輔助，以及導入AI可能會遇到的風險和挑戰。</p>','Dr. Chun-Ying Huang is a Professor at the Department of Computer Science, National Yang Ming Chiao Tung University (NYCU). Dr. Huang\'s research interests fall in the areas of system security and multimedia networking. He also served as PIs or co-PIs of several teaching, research, and industrial projects in network and system security areas, including the information security incubation program (ISIP and AIS3) from the Ministry of Education (MoE) and Taiwan information security center program (TWISC) at NYCU from the Ministry of Science and Technology (MOST). Dr. Huang received ACM Taipei/Taiwan Chapter K. T. Li Young Researcher Award in 2014, MOST Excellent Young Scholar Grants in 2021, and NCTU/NYCU excellent teaching awards in 2020 and 2021. He currently serves as the Director of the Institute of Network Engineering at National Yang Ming Chiao Tung University.','','https://people.cs.nycu.edu.tw/~chuang/','','','NYCU\r','教授',NULL),(51,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(52,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(53,0,9999,'AI','李彥樞','YAN LEE','yan-lee','Investment Trends in Generative AI','中文','yes','V','HIVE VENTURES','Founder and Managing Partner','/img/speaker/252152f5.jpg',NULL,NULL,NULL,'In this rapidly evolving era of the AI and Generative Content Industry (AIGC), we will explore investment trends and opportunities in the Gen AI market from a venture capital perspective. We will examine global VC investment trends, market potential, and value within the Gen AI industry chain and its components worldwide. Additionally, we will uncover the areas of investment focus and highlights in the development trends of enterprises adopting Generative AI, with the aim of collectively discussing the future of this industry.',NULL,'Yan Lee is the Founder and Managing Partner at Hive Ventures - a Taiwan-focused global seed to early stage venture capital firm, with a focus on artificial intelligence (AI) and Internet of Things (IoT) and its applications. He brings his strong past experience as an entrepreneur in the fields of Big Data and AI to offer strategic support to Hive Ventures’ portfolio companies. Yan is a passionate venture builder and aims to support top talents in Taiwan to foster its next wave of unicorn technopreneurs.  Yan was the Founder and CEO of Buzzinate, a leading Big Data platform and service provider in China that merged with iClick in 2014. He played a central role in Buzzinate’s success, which led him to be included in Forbes’ “30 under 30 Entrepreneurs of China\'\' in 2012 as well as Campaign Asia’s “40 under 40” in 2018. Yan went on to become the Chief Product Officer and Head of International Business of iClick Interactive (Nasdaq: ICLK), where he spearheaded product innovations and drove business growth globally.  Yan holds an MBA from the China Europe International Business School (CEIBS) in Shanghai. He is also an alumnus of the London Business School (LBS) and National Chengchi University (NCCU) in Taiwan.','<p>Yan Lee is the Founder and Managing Partner at Hive Ventures - a Taiwan-focused global seed to early stage venture capital firm, with a focus on artificial intelligence (AI) and Internet of Things (IoT) and its applications. He brings his strong past experience as an entrepreneur in the fields of Big Data and AI to offer strategic support to Hive Ventures’ portfolio companies. Yan is a passionate venture builder and aims to support top talents in Taiwan to foster its next wave of unicorn technopreneurs.</p>\r\n\r\n<p>Yan was the Founder and CEO of Buzzinate, a leading Big Data platform and service provider in China that merged with iClick in 2014. He played a central role in Buzzinate’s success, which led him to be included in Forbes’ “30 under 30 Entrepreneurs of China\\\'\\\' in 2012 as well as Campaign Asia’s “40 under 40” in 2018. Yan went on to become the Chief Product Officer and Head of International Business of iClick Interactive (Nasdaq: ICLK), where he spearheaded product innovations and drove business growth globally.</p>\r\n\r\n<p>Yan holds an MBA from the China Europe International Business School (CEIBS) in Shanghai. He is also an alumnus of the London Business School (LBS) and National Chengchi University (NCCU) in Taiwan.</p>',NULL,'','','Hive Ventures\r','創辦人',NULL),(54,0,9999,'AI','張榮貴','James Chang','james-chang','Redefining Customer Service in the Generative AI Era','中文','yes','V','AI3 Co.','Chaiman','/img/speaker/fca5db70.jpg',NULL,NULL,NULL,'數位轉型下的客戶服務 Digital Transformation and Its Impact on Customer Service  整合GPT的智能機器人 Chatbot Empowered by GPT Integration  對話式知識管理是最佳服務助理 Conversational KM is the Best Service Assistant','<p>數位轉型下的客戶服務<br>\r\nDigital Transformation and Its Impact on Customer Service</p>\r\n\r\n<p>整合GPT的智能機器人<br>\r\nChatbot Empowered by GPT Integration</p>\r\n\r\n<p>對話式知識管理是最佳服務助理<br>\r\nConversational KM is the Best Service Assistant</p>','PRESENT JOB ●Chairman, Ai3 Co. ●Chairman, Gemfor Tech Co., Ltd. ●Co-founder, Chainsea Information Integration Co., Ltd.  SUCCESS AND ACHIEVEMENT Over 30 years of software development experience, 30 years of CTI/CRM technical integration application development practice. Key achievements include CRM, Contact Center development, call center system integrated development, Chatbot development, big data analysis, etc. Specialized in integrating IT with CRM service processes and structures to offer comprehensive intelligent service processes and information structures. In recent years, has focused on big data and AI technologies, applying them to CRM and customer service domains, developing natural language processing (NLP) technology, creating Chatbot, sentiment analysis systems, conversational commerce, legal compliance systems, etc.   EXPERTISE CRM, Big Data, Chatbot Design and Application, NLP, Sentiment Analysis System, Intelligent Customer Service Planning and Design, Customer Service Center Operation Management, Conversational Commerce, Software Engineering, Project Management, Corporate Management.  30幾年軟體開發經驗、30年CTI/CRM技術整合應用發展實務經驗，主要成就有CRM、Contact Center產品開發、電話服務中心系統整合開發、AI服務機器人開發、輿情分析系統、服務大數據分析…等。專精於CRM服務流程與服務架構之資訊技術整合，為企業服務提出完整智慧服務流程與資訊架構。     近年專注於大數據與人工智慧技術，應用於CRM與客戶服務領域，發展自然語言處理技術(NLP)，開發AI服務機器人、輿情分析系統、服務數據分析、對話式商務、法遵系統…等智慧應用。2017年至今擔任中華軟協AI大數據智慧應用促進會會長，推動產業AI智慧應用發展，促使產業AI化、AI產業化。2022年擔任中華軟協元宇宙發展促進會，持續推動新興科技與產業融合，發展新應用。','<p><span class=\"purple\">PRESENT JOB</span><br>\r\n●Chairman, Ai3 Co.<br>\r\n●Chairman, Gemfor Tech Co., Ltd.<br>\r\n●Co-founder, Chainsea Information Integration Co., Ltd.\r\n</p>\r\n<p>\r\n<span class=\"purple\">SUCCESS AND ACHIEVEMENT</span><br>\r\nOver 30 years of software development experience, 30 years of CTI/CRM technical integration application development practice. Key achievements include CRM, Contact Center development, call center system integrated development, Chatbot development, big data analysis, etc. Specialized in integrating IT with CRM service processes and structures to offer comprehensive intelligent service processes and information structures.\r\nIn recent years, has focused on big data and AI technologies, applying them to CRM and customer service domains, developing natural language processing (NLP) technology, creating Chatbot, sentiment analysis systems, conversational commerce, legal compliance systems, etc. \r\n</p>\r\n<p>\r\n<span class=\"purple\">EXPERTISE</span><br>\r\nCRM, Big Data, Chatbot Design and Application, NLP, Sentiment Analysis System, Intelligent Customer Service Planning and Design, Customer Service Center Operation Management, Conversational Commerce, Software Engineering, Project Management, Corporate Management.\r\n</p>\r\n<p>\r\n30幾年軟體開發經驗、30年CTI/CRM技術整合應用發展實務經驗，主要成就有CRM、Contact Center產品開發、電話服務中心系統整合開發、AI服務機器人開發、輿情分析系統、服務大數據分析…等。專精於CRM服務流程與服務架構之資訊技術整合，為企業服務提出完整智慧服務流程與資訊架構。<br>\r\n    近年專注於大數據與人工智慧技術，應用於CRM與客戶服務領域，發展自然語言處理技術(NLP)，開發AI服務機器人、輿情分析系統、服務數據分析、對話式商務、法遵系統…等智慧應用。2017年至今擔任中華軟協AI大數據智慧應用促進會會長，推動產業AI智慧應用發展，促使產業AI化、AI產業化。2022年擔任中華軟協元宇宙發展促進會，持續推動新興科技與產業融合，發展新應用。</p>\r\n<style>.purple{color:#5d2191}</style>',NULL,'','','Ai3\r','董事長',NULL),(55,0,9999,'AI','何建幟','Ernie Ho','ernie-ho','The Rise of AI Agents: A Virtual Workforce Available 24/7','中文','yes','V','HelperAI & Chainsight','Cofounder & CEO','/img/speaker/c3aa12c3.jpg',NULL,NULL,NULL,' Learn how AI agents revolutionize efficiency across industries. We\'ll dissect the components that make them work: Planning, Memory, Tool Use. Real-world case studies from HelperAI will demonstrate impact on customer service, logistics, and more. Whether you\'re an academic, a business leader, or just curious, this talk offers actionable insights into AI’s transformative power.',NULL,'Ernie Ho, an alumnus of Carnegie Mellon University and MIT, is the co-founder and CEO of HelperAI & Chainsight, with a focus on AI applications and innovation. He formerly worked as an AI engineer at Uber’s Self-Driving Center. In 2020, he cofounded Chainsight, an AI-powered platform for blockchain transaction risk analysis, which has been recognized by G20, BIS, governments of US-Japan-Singapore, and Trend Micro. In 2022, he established HelperAI, creating AI agents for major corporations - an 24/7 virtual team that automates customer service and sales processes to boost business productivity. His firm has been invested by Y Combinator, Franklin Templeton, and Samsung.  何建幟（Ernie Ho），美國卡內基美隆大學及麻省理工學院校友，HelperAI & Chainsight共同創辦人兼CEO，專注於AI應用與創新，曾任職Uber自動駕駛中心。2020年成立Chainsight，利用AI模型打造區塊鏈交易風險分析平台，榮獲G20、國際清算銀行、美日星政府與趨勢科技等認證。2022年成立HelperAI，為多家大型企業打造AI代理人 - 全年無休的虛擬團隊，自動化客服與銷售流程，加速提升企業生產力，目前已獲矽谷頂尖加速器Y Combinator、美國富蘭克林、三星集團等國際知名機構投資。','<p>Ernie Ho, an alumnus of Carnegie Mellon University and MIT, is the co-founder and CEO of HelperAI & Chainsight, with a focus on AI applications and innovation. He formerly worked as an AI engineer at Uber’s Self-Driving Center. In 2020, he cofounded Chainsight, an AI-powered platform for blockchain transaction risk analysis, which has been recognized by G20, BIS, governments of US-Japan-Singapore, and Trend Micro. In 2022, he established HelperAI, creating AI agents for major corporations - an 24/7 virtual team that automates customer service and sales processes to boost business productivity. His firm has been invested by Y Combinator, Franklin Templeton, and Samsung.</p>\r\n\r\n<p>何建幟（Ernie Ho），美國卡內基美隆大學及麻省理工學院校友，HelperAI & Chainsight共同創辦人兼CEO，專注於AI應用與創新，曾任職Uber自動駕駛中心。2020年成立Chainsight，利用AI模型打造區塊鏈交易風險分析平台，榮獲G20、國際清算銀行、美日星政府與趨勢科技等認證。2022年成立HelperAI，為多家大型企業打造AI代理人 - 全年無休的虛擬團隊，自動化客服與銷售流程，加速提升企業生產力，目前已獲矽谷頂尖加速器Y Combinator、美國富蘭克林、三星集團等國際知名機構投資。</p>','https://helperai.ai/','','','Chainsight ＆ HelperAI\r','創辦人',NULL),(56,0,9999,'AI','郭昶甫','Kuo,Chang-Fu','kuo-chang-fu','The Role of Artificial Intelligence in Clinical Decision-making','中文','yes','x','Chang Gung Memorial Hospital, Linkou','Center for Artificial Intelligence in Medicine,Director','/img/speaker/c61766fb.jpg',NULL,NULL,NULL,'9/14 下午給',NULL,'Dr. Chang-Fu Kuo, a distinguished rheumatologist, and physician-scientist, has been committed to research in rheumatology, epidemiology, genetic epidemiology, and health policy. A previous recipient of the 2019 Ministry of Science and Technology\'s Outstanding Research Award, Dr. Kuo has continuously pursued breakthroughs in healthcare, particularly exploring artificial intelligence applications, bolstered by clinical trials and Taiwan Food and Drug Administration (TFDA) accreditation. Dr. Kuo uses an interdisciplinary approach to address complex clinical and epidemiological issues affecting vast populations. His published research, often referenced in international guidelines, covers wide-ranging aspects of rheumatic diseases. Dr. Kuo\'s research, consistently published in high-impact academic journals, increasingly highlights societal impacts, real-world clinical applications, and potential commercialization. His collaborations with globally recognized research groups further attest to his influence in the field. The University of Nottingham has repeatedly honored him as an \'Honorary Associate Professor\' for his exceptional contributions, and Chang Gung University honored him as Extinguished Alumni.','',NULL,'','','Chang Gung Memorial Hospital\r','人工智能核心實驗室主任',NULL),(57,0,9999,'AI','張詠淳','Yung-Chun Chang','yung-chun-chang','The Future is Here - Unlocking the Potential of Clinical Data with NLP','中文','yes','V','Graduate Institute of Data Science, Taipei Medical University','Associate Professor','/img/speaker/f4824411.jpg',NULL,NULL,NULL,'In this talk, we will delve into the remarkable advancements in Natural Language Processing (NLP) and their transformative potential in the realm of clinical data analysis. The field of medical imaging has seen tremendous growth, and one of the key challenges lies in translating radiomics features into actionable insights. Firstly, we will explore a groundbreaking approach that addresses this challenge by automatically generating Lung-RADS reports from low-dose lung CT scans. By leveraging the power of deep learning to construct a multi-objective framework, we have advanced the extraction of essential information to aid in the accurate diagnosis of lung abnormalities. Moving beyond medical imaging, pathology reports play a crucial role in guiding treatment decisions, particularly in lung cancer cases. We will investigate how Generative Pre-trained Transformers (GPT) can extract vital features from pathology reports, enabling the identification of key indicators for effective lung cancer treatment. By harnessing the capabilities of GPT, we unlock a wealth of information buried within textual data, enhancing the precision of personalized therapies.  Moreover, advanced lung cancer requires comprehensive decision support systems. Deep learning-based techniques offer immense potential in this domain by automating the extraction of key features from pathology reports. By integrating these extracted features into a decision support system, we empower clinicians with valuable insights, aiding in the development of tailored treatment plans and ultimately improving patient outcomes. Throughout this presentation, we will witness how NLP, combined with deep learning methodologies, revolutionizes the analysis of clinical data. By bridging the gap between unstructured text and actionable knowledge, we unlock the full potential of clinical data and propel us into an era where diagnoses are more accurate, treatments are more personalized, and patient care is optimized.  Together, let us embark on a journey that demonstrates how NLP is shaping the future of healthcare, forging a path towards a world where the integration of technology and medicine empowers us to extend the potential of clinical data like never before. The future is indeed here, and it is through the fusion of NLP and clinical data that we shall explore its boundless possibilities.','<p>In this talk, we will delve into the remarkable advancements in Natural Language Processing (NLP) and their transformative potential in the realm of clinical data analysis. The field of medical imaging has seen tremendous growth, and one of the key challenges lies in translating radiomics features into actionable insights. Firstly, we will explore a groundbreaking approach that addresses this challenge by automatically generating Lung-RADS reports from low-dose lung CT scans. By leveraging the power of deep learning to construct a multi-objective framework, we have advanced the extraction of essential information to aid in the accurate diagnosis of lung abnormalities. Moving beyond medical imaging, pathology reports play a crucial role in guiding treatment decisions, particularly in lung cancer cases. We will investigate how Generative Pre-trained Transformers (GPT) can extract vital features from pathology reports, enabling the identification of key indicators for effective lung cancer treatment. By harnessing the capabilities of GPT, we unlock a wealth of information buried within textual data, enhancing the precision of personalized therapies.</p>\r\n\r\n<p>Moreover, advanced lung cancer requires comprehensive decision support systems. Deep learning-based techniques offer immense potential in this domain by automating the extraction of key features from pathology reports. By integrating these extracted features into a decision support system, we empower clinicians with valuable insights, aiding in the development of tailored treatment plans and ultimately improving patient outcomes. Throughout this presentation, we will witness how NLP, combined with deep learning methodologies, revolutionizes the analysis of clinical data. By bridging the gap between unstructured text and actionable knowledge, we unlock the full potential of clinical data and propel us into an era where diagnoses are more accurate, treatments are more personalized, and patient care is optimized.</p>\r\n\r\n<p>Together, let us embark on a journey that demonstrates how NLP is shaping the future of healthcare, forging a path towards a world where the integration of technology and medicine empowers us to extend the potential of clinical data like never before. The future is indeed here, and it is through the fusion of NLP and clinical data that we shall explore its boundless possibilities.</p>','Dr. Yung-Chun Chang is a renowned expert in the fields of text mining, natural language processing (NLP), and the associated technologies of machine learning and linguistic recognition. He excels in harnessing these technologies to address challenges across diverse domains, with a primary focus on intelligent healthcare, bioinformatics, business intelligence, and language comprehension. In 2016, Dr. Chang received accolades for his exceptional contributions to research, notably the Outstanding Postdoctoral Research Award from Academia Sinica and the Doctoral Dissertation Award from the Computational Linguistics Society. In 2017, he joined the faculty of Taipei Medical University, where he has since published numerous papers in top-tier international journals and conferences, such as ACL and TKDE.    Passionate about pedagogy, Professor Chang has repeatedly been recognized for his teaching excellence, earning both campus-wide Outstanding Teacher and Distinguished New Faculty awards. Furthermore, he is deeply committed to student mentorship and guidance. His students have achieved commendable results in various international competitions. Noteworthy accolades include a first-place finish in the 2023 NTCIR International Information Retrieval Competition, a second-place finish in the 2022 BioCreative International Biomedical Literature Automated Mining Competition, and a gold award at the Taiwan AI EXPO.   張詠淳博士專精於文字探勘與自然語言處理以及相關的機器學習與語言辨識技術，擅長將這些技術應用於解決不同領域的問題，主要研究領域為智慧醫療、生物資訊、商業智慧以及語言理解。張教授在2016年曾榮獲中研院博士後傑出研究獎以及計算語言學會博士論文獎。於2017年至臺北醫學大學從事教職，近年發表多篇國際頂尖期刊與會議論文。張教授熱愛教學，不僅屢獲校級優良教師、新進優良教師等教學獎項，更致力於學生的培育和指導。在多項國際競賽中獲得優異成績，包括2023年NTCIR國際資料檢索競賽第一名、2022年BioCreative國際生醫文獻自動探勘競賽第二名，以及Taiwan AI EXPO大賽金獎等。','<p>Dr. Yung-Chun Chang is a renowned expert in the fields of text mining, natural language processing (NLP), and the associated technologies of machine learning and linguistic recognition. He excels in harnessing these technologies to address challenges across diverse domains, with a primary focus on intelligent healthcare, bioinformatics, business intelligence, and language comprehension. In 2016, Dr. Chang received accolades for his exceptional contributions to research, notably the Outstanding Postdoctoral Research Award from Academia Sinica and the Doctoral Dissertation Award from the Computational Linguistics Society. In 2017, he joined the faculty of Taipei Medical University, where he has since published numerous papers in top-tier international journals and conferences, such as ACL and TKDE.</p>\r\n<p>Passionate about pedagogy, Professor Chang has repeatedly been recognized for his teaching excellence, earning both campus-wide Outstanding Teacher and Distinguished New Faculty awards. Furthermore, he is deeply committed to student mentorship and guidance. His students have achieved commendable results in various international competitions. Noteworthy accolades include a first-place finish in the 2023 NTCIR International Information Retrieval Competition, a second-place finish in the 2022 BioCreative International Biomedical Literature Automated Mining Competition, and a gold award at the Taiwan AI EXPO.</p>\r\n\r\n\r\n<p>張詠淳博士專精於文字探勘與自然語言處理以及相關的機器學習與語言辨識技術，擅長將這些技術應用於解決不同領域的問題，主要研究領域為智慧醫療、生物資訊、商業智慧以及語言理解。張教授在2016年曾榮獲中研院博士後傑出研究獎以及計算語言學會博士論文獎。於2017年至臺北醫學大學從事教職，近年發表多篇國際頂尖期刊與會議論文。張教授熱愛教學，不僅屢獲校級優良教師、新進優良教師等教學獎項，更致力於學生的培育和指導。在多項國際競賽中獲得優異成績，包括2023年NTCIR國際資料檢索競賽第一名、2022年BioCreative國際生醫文獻自動探勘競賽第二名，以及Taiwan AI EXPO大賽金獎等。</p>','http://nlp.tmu.edu.tw/','Office of Data Science, Taipei Medical University','Deputy Chief Data Officer','Taipei Medical University\r','副教授',NULL),(58,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(59,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(60,0,9999,'AI','林穎俊','LIN YING-CHUN','lin-ying-chun','Being a Better Learner with ChatGPT','中文','yes','V','Jhong Shan Elementary School of Yilan County','Section Chief of Information Technology','/img/speaker/75582d74.png',NULL,NULL,NULL,'How can students become a better learners through ChatGPT? This presentation outlines the implementation of ChatGPT in primary education to facilitate deepening learning. It delves into the application of six evidence-based learning strategies, each coupled with corresponding prompts 如何透過ChatGPT成為更好的學習者，分享內容在於在小學的教學中使用ChatGPT以促進學生更深度的學習進而到依據Evidence-based learning strategies提出的六個學學策略跟對應的prompts以幫助學生成為更好的學習者','<p>How can students become a better learners through ChatGPT? This presentation outlines the implementation of ChatGPT in primary education to facilitate deepening learning. It delves into the application of six evidence-based learning strategies, each coupled with corresponding prompts</p>\r\n<p>如何透過ChatGPT成為更好的學習者，分享內容在於在小學的教學中使用ChatGPT以促進學生更深度的學習進而到依據Evidence-based learning strategies提出的六個學學策略跟對應的prompts以幫助學生成為更好的學習者</p>','林穎俊擔任宜蘭縣中山國小的教師與資訊組長，對於學習與教學充滿熱情。他熱愛與孩子們互動，認為擔任老師是全世界最具意義且充實的職業。他堅信數位學習能夠有效地培養孩子們的協作、溝通、創意以及批判性思考能力，同時為孩子們提供成功自學的契機。','','https://www.facebook.com/gatelynch','','','Jhongshan Elementary School\r','老師',NULL),(61,0,9999,'AI','李海碩','Lee Haishuo','lee-haishuo','Future-Proofing Humanity: Strategies for Thriving in an AI-Dominated Epoch','中文','yes','V','Wagor International School','Superintendent','/img/speaker/ba1ae392.jpg',NULL,NULL,NULL,'In the rapidly advancing age of Artificial Intelligence, esteemed global institutions have underscored the urgent need for reskilling and upskilling. As we find ourselves at the crossroads of technology and tradition, it becomes crucial to identify sustainable avenues for concerted effort and investment. Synthesizing insights from leading research entities, Haishuo will demystify the essential competencies set to define the AI-centric world. Delve deep as Haishuo showcases cutting-edge AI applications in educational landscapes worldwide and articulates spheres where the human touch remains irreplaceable.The presentation strives to offer an integrative exploration of present-day research, forward-looking perspectives, and the age-old human strengths that promise to endure. Come to the talk for a humble presentation of the intertwining destinies of AI and human resilience - an enlightening engagement, offering tools to chart our course in an AI-augmented future.  在人工智慧急速發展的時代，世界各大知名機構都強調了重新學習和提升技能的迫切需要。當我們處於技術和傳統的交叉路口，確定可永續投入的方向已變得至關重要。綜整全球各研究機構的洞見，海碩將向您稟報AI為中心世界的核心素養，深入探索全球教育風景中的尖端AI應用，並強調人類知能無可取代的領域。此演講旨在提供現今研究、前瞻性視角和人類亙古知能的綜合探索，期能在變動的時代提供永續發展的力量。請蒞臨本次演講，聆聽AI和人類韌性相互交織的命運的淺見，期能拋磚引玉，共同探討引領在AI增強未來道路上可用的工具。 ','<p>In the rapidly advancing age of Artificial Intelligence, esteemed global institutions have underscored the urgent need for reskilling and upskilling. As we find ourselves at the crossroads of technology and tradition, it becomes crucial to identify sustainable avenues for concerted effort and investment. Synthesizing insights from leading research entities, Haishuo will demystify the essential competencies set to define the AI-centric world. Delve deep as Haishuo showcases cutting-edge AI applications in educational landscapes worldwide and articulates spheres where the human touch remains irreplaceable.The presentation strives to offer an integrative exploration of present-day research, forward-looking perspectives, and the age-old human strengths that promise to endure. Come to the talk for a humble presentation of the intertwining destinies of AI and human resilience - an enlightening engagement, offering tools to chart our course in an AI-augmented future.</p>\r\n\r\n<p>在人工智慧急速發展的時代，世界各大知名機構都強調了重新學習和提升技能的迫切需要。當我們處於技術和傳統的交叉路口，確定可永續投入的方向已變得至關重要。綜整全球各研究機構的洞見，海碩將向您稟報AI為中心世界的核心素養，深入探索全球教育風景中的尖端AI應用，並強調人類知能無可取代的領域。此演講旨在提供現今研究、前瞻性視角和人類亙古知能的綜合探索，期能在變動的時代提供永續發展的力量。請蒞臨本次演講，聆聽AI和人類韌性相互交織的命運的淺見，期能拋磚引玉，共同探討引領在AI增強未來道路上可用的工具。</p>','李海碩長期專注在國際教育、語言教育、與科技教育與創新領域。目前擔任葳格國際學校的總校長與1111生成式AI創新學院的執行長，致力推廣AIGC相關應用。他擁有全民英檢和TOEIC的全數滿分，並且是台灣僅有的五位多益官方講師之一。海碩畢業於國立交通大學教育研究所數位學習組，並正就讀於密涅瓦大學的決策分析碩士(MDA)。在國際演講會曾獲九個台灣全國冠軍和一個亞洲區即席演講冠軍的榮銜，並是台灣首開風氣之先的ChatGPT免費線上課程教師，可彰顯其推動創新和人工智慧教育的決心。  With a sustained focus on international, language, and technological education and innovation, Haishuo Lee serves as the Superintendent of Wagor International School and the CEO of 1111 AIGC Innovation Academy. He is devoted to promoting the application of AIGC. A holder of full scores in GEPT and TOEIC, he is also one of the only five TOEIC Propell Trainers in Taiwan. He graduated from the Digital Learning Division, Institute of Education, National Chiao Tung University and is currently pursuing a Master of Decision Analysis at Minerva University. As a member in Toastmasters International, he has clinched nine national championships in Taiwan and one impromptu speech championship in Asia. He pioneered the first-ever free online ChatGPT course in Taiwan, underscoring his commitment to driving innovation and AI education.','<p>李海碩長期專注在國際教育、語言教育、與科技教育與創新領域。目前擔任葳格國際學校的總校長與1111生成式AI創新學院的執行長，致力推廣AIGC相關應用。他擁有全民英檢和TOEIC的全數滿分，並且是台灣僅有的五位多益官方講師之一。海碩畢業於國立交通大學教育研究所數位學習組，並正就讀於密涅瓦大學的決策分析碩士(MDA)。在國際演講會曾獲九個台灣全國冠軍和一個亞洲區即席演講冠軍的榮銜，並是台灣首開風氣之先的ChatGPT免費線上課程教師，可彰顯其推動創新和人工智慧教育的決心。</p>\r\n\r\n<p>With a sustained focus on international, language, and technological education and innovation, Haishuo Lee serves as the Superintendent of Wagor International School and the CEO of 1111 AIGC Innovation Academy. He is devoted to promoting the application of AIGC. A holder of full scores in GEPT and TOEIC, he is also one of the only five TOEIC Propell Trainers in Taiwan. He graduated from the Digital Learning Division, Institute of Education, National Chiao Tung University and is currently pursuing a Master of Decision Analysis at Minerva University. As a member in Toastmasters International, he has clinched nine national championships in Taiwan and one impromptu speech championship in Asia. He pioneered the first-ever free online ChatGPT course in Taiwan, underscoring his commitment to driving innovation and AI education.</p>','https://www.meethaishuolee.com/','1111 AIGC Innovative Academy','CEO','Wagor International School\r','總校長',NULL),(62,0,9999,'AI','巫勇賢','Yung-Hsien Wu','yung-hsien-wu','Impact of Generative Artificial Intelligence on Higher Education','中文','yes','X','National Tsing Hua University','Office of Academic Affairs/Vice President for Academic Affairs','/img/speaker/f38cf0e1.jpg',NULL,NULL,NULL,'With the rise of ChatGPT, Generative Artificial Intelligence (Generative AI) has gradually garnered attention from various fields. Many professors both domestically and internationally have attempted to utilize ChatGPT to answer university exam questions and have been pleasantly surprised by the promising results achieved. According to a recent report from EDUCASE, approximately thirty percent of university professors hold a pessimistic attitude towards Artificial Intelligence in General (AIGC), with over half of them being unaware of how students use AI. What impacts might Generative AI have on higher education? What roles could AIGC play in admissions, teaching, and research within higher education, and what potential disruptions might occur? ',NULL,'Dr. Wu received the BS degree in electrical engineering from National Tsing Hua University (NTHU) in 1996, and the PhD degree in electronics engineering from National Chiao Tung University (NCTU) in 2000, both in Taiwan. During 2000-2005, he was with ProMOS Technologies (茂德科技, DRAM manufacturers) where he was engaged in advanced process development and earned the individual IP award in 2002 and 2003 for the contribution in patent proposal.  In 2005, he joined NTHU as an Assistant Professor. He was promoted to Associate Professor and Professor in 2009 and 2012 respectively. He received many awards including the “Young Faculty Research Award (新進人員研究獎)”, “Excellent Teaching Award (傑出教學獎)” and “Outstanding Mentor Award (傑出導師獎)” granted by NTHU. In 2015, he was conferred with the title of “NTHU Distinguished Professor (清華特聘教授)” for his outstanding contribution in teaching and mentoring young talents. He was awarded \"Outstanding Young Scholar Research Grant\" twice by National Science and Technology Council (NSTC) in 2012 and 2019 (2次國科會優秀年輕學者計畫). He was also bestowed “Lifetime Achievement Award (國際傑出發明家發明終身成就獎)” by Taiwan International Invention Award Winners Association in 2016. He was the recipient of “Excellent Electrical Engineer Professor Award (中國電機工程學會傑出電機工程教授獎)” in 2021 by Chinese Institute of Electrical Engineering. In addition, he was bestowed “Excellent Project Award (優良計畫獎)” by Atomic Energy Council (原子能委員會) in 2022 and 2023. Currently, he is an IET Fellow (Institution of Engineering and Technology, 國際工程技術學會會士) and IEEE Senior member (Institute of Electrical and Electronics Engineers). He is committed to exploring the boundaries of next-generation ferroelectric memory devices and VLSI technologies by developing novel materials and innovative structures. He has published 65 SCI papers, several prestigious conference papers including IEDM and Symp. VLI Technology in the past 10 years (the 2nd highest-ranked team in Taiwan in terms of publishing papers in renowned IEEE Electron Device Letters). He also holds 42 patents (Taiwan, US, German, Korea, China) and has authored 1 book chapter. Furthermore, the students he mentored have won many national-wide research-based awards including “Technology Scholarship (中技社科技獎學金) ” from China Technical Consultants Inc. (CTCI) Foundation in consecutive 5 years (2018-2022), “Semiconductor Award (台灣半導體產業協會半導體獎)” from Taiwan Semiconductor Industry Association (TSIA) in 2019/2020/2023, “College Student Research Creativity Award (國科會大專學生研究創作獎)” from NSTC in 2019, “TSMC PhD student fellowship (台積電獎學金)” and “Scholarship for Outstanding PhD Students (國科會優秀博士生獎學金)” from NSTC (one of highest student scholarships provided by the government and industry in Taiwan), both in 2020.        In addition, he has held some administrative positions at Office of Academic Affairs in NTHU including Division Chief of Center for Teaching and Learning Development, Director of Chinese Language Center, Director of Center for Continuing Education during 2010-2016. From 2015- 2021, he served as the Chairman of Interdisciplinary Program (undergraduate department) of College of Nuclear Science, Associate Vice President for Student Affairs, Chairman of Department of Engineering and System Science. From 2020-2022, he also served as the Associate Vice President for Academic Affairs. Since 2022, he has been the Vice President for Academic Affairs of NTHU.','<p>Dr. Wu received the BS degree in electrical engineering from National Tsing Hua University (NTHU) in 1996, and the PhD degree in electronics engineering from National Chiao Tung University (NCTU) in 2000, both in Taiwan. During 2000-2005, he was with ProMOS Technologies (茂德科技, DRAM manufacturers) where he was engaged in advanced process development and earned the individual IP award in 2002 and 2003 for the contribution in patent proposal. </p>\r\n<p>In 2005, he joined NTHU as an Assistant Professor. He was promoted to Associate Professor and Professor in 2009 and 2012 respectively. He received many awards including the “Young Faculty Research Award (新進人員研究獎)”, “Excellent Teaching Award (傑出教學獎)” and “Outstanding Mentor Award (傑出導師獎)” granted by NTHU. In 2015, he was conferred with the title of “NTHU Distinguished Professor (清華特聘教授)” for his outstanding contribution in teaching and mentoring young talents. He was awarded \\\"Outstanding Young Scholar Research Grant\\\" twice by National Science and Technology Council (NSTC) in 2012 and 2019 (2次國科會優秀年輕學者計畫). He was also bestowed “Lifetime Achievement Award (國際傑出發明家發明終身成就獎)” by Taiwan International Invention Award Winners Association in 2016. He was the recipient of “Excellent Electrical Engineer Professor Award (中國電機工程學會傑出電機工程教授獎)” in 2021 by Chinese Institute of Electrical Engineering. In addition, he was bestowed “Excellent Project Award (優良計畫獎)” by Atomic Energy Council (原子能委員會) in 2022 and 2023. Currently, he is an IET Fellow (Institution of Engineering and Technology, 國際工程技術學會會士) and IEEE Senior member (Institute of Electrical and Electronics Engineers).</p>\r\n<p>He is committed to exploring the boundaries of next-generation ferroelectric memory devices and VLSI technologies by developing novel materials and innovative structures. He has published 65 SCI papers, several prestigious conference papers including IEDM and Symp. VLI Technology in the past 10 years (the 2nd highest-ranked team in Taiwan in terms of publishing papers in renowned IEEE Electron Device Letters). He also holds 42 patents (Taiwan, US, German, Korea, China) and has authored 1 book chapter. Furthermore, the students he mentored have won many national-wide research-based awards including “Technology Scholarship (中技社科技獎學金) ” from China Technical Consultants Inc. (CTCI) Foundation in consecutive 5 years (2018-2022), “Semiconductor Award (台灣半導體產業協會半導體獎)” from Taiwan Semiconductor Industry Association (TSIA) in 2019/2020/2023, “College Student Research Creativity Award (國科會大專學生研究創作獎)” from NSTC in 2019, “TSMC PhD student fellowship (台積電獎學金)” and “Scholarship for Outstanding PhD Students (國科會優秀博士生獎學金)” from NSTC (one of highest student scholarships provided by the government and industry in Taiwan), both in 2020.</p>\r\n<p>In addition, he has held some administrative positions at Office of Academic Affairs in NTHU including Division Chief of Center for Teaching and Learning Development, Director of Chinese Language Center, Director of Center for Continuing Education during 2010-2016. From 2015- 2021, he served as the Chairman of Interdisciplinary Program (undergraduate department) of College of Nuclear Science, Associate Vice President for Student Affairs, Chairman of Department of Engineering and System Science. From 2020-2022, he also served as the Associate Vice President for Academic Affairs. Since 2022, he has been the Vice President for Academic Affairs of NTHU.</p>','https://greenelectronics.wixsite.com/yung-hsien-wu/about1','','','National Tsing Hua University\r','教務長',NULL),(63,0,9999,'AI','林勤富','Ching-Fu Lin','ching-fu-lin','Forms, Substances, and Challenges of the Transparency Principle in Algorithmic Governance ','中文','yes','X','National Tsing Hua University','Professor, Institute of Law for Science and Technology','/img/speaker/3e6ca0c1.jpg',NULL,NULL,NULL,'With the emergence of big data analytics, computational power, and breakthroughs of algorithmic models, artificial intelligence (AI) has been developing rapidly. Among others, the “algorithmization” of government functions holds the potential to improve overall efficiency, but at the same time, it also poses adverse impact on fundamental rights due to inadequate data protection, systematic bias and discrimination, algorithmic opacity, and infringement on fairness and due process rights. As a result, the AI ethics principles, government or corporate AI policies, and other instruments in recent years have highlighted “transparency” as one of the core governance principles. Yet what is transparency? Do we require different levels of transparency for different types of decision-making and power wielding? What does the so-called transparency principle entail in legal and policy terms? This talk aims to explore together the definition, types, levels, and normative substance of transparency in broader contexts of algorithmic governance, which have been lacking clear and full understanding or discourse.  By examining and articulating the normative functions, typology, values, and limits of the transparency principle, this talk will endeavors to point out the blind spots of the existing discourse, how to address them, and the way forward.',NULL,'Ching-Fu Lin is Professor at Institute of Law for Science and Technology and Director of Interdisciplinary Program of Mangement and Technology, National Tsing Hua University (NTHU), where he teaches international law and global governance, law and technology, and artificial intelligence law and policy.  Professor Lin received his LL.M. and S.J.D. from Harvard Law School, with the honor of John Gallup Laylin Memorial Prize and Yong K. Kim Memorial Prize.    He also holds a double degree in law (LL.B.) and chemical engineering (B.S.) from National Taiwan University.  Professor Lin has served as Visiting Researcher at Berkman Klein Center for Internet and Society at Harvard University, Visiting Scholar at the Allens Hub for Technology, Law and Innovation at UNSW Sydney, as well as Visiting Fellow at Graduate Institute of International and Development Studies in Geneva.  In 2019, Professor Lin was appointed to serve on the Board of Trustees of the Academy of Food Law and Policy, United States.  In 2023, he was elected to serve as Vice Chair of the International Law and Technology Interest Group (ILTechIG) of the American Society of International Law.  Active in legal academia, Professor Lin has been invited to talk in many academic/practical settings, and his legal scholarship has appeared in leading journals and edited collections.  Professor Lin has received the Junior Research Award, Outstanding Research Award of Hou De Association, and CTM Research Award from NTHU as well as the Ta-You Memorial Award from Taiwan’s Ministry of Science and Technology. ','<p>Ching-Fu Lin is Professor at Institute of Law for Science and Technology and Director of Interdisciplinary Program of Mangement and Technology, National Tsing Hua University (NTHU), where he teaches international law and global governance, law and technology, and artificial intelligence law and policy.  Professor Lin received his LL.M. and S.J.D. from Harvard Law School, with the honor of John Gallup Laylin Memorial Prize and Yong K. Kim Memorial Prize.  </p>\r\n\r\n<p>He also holds a double degree in law (LL.B.) and chemical engineering (B.S.) from National Taiwan University.  Professor Lin has served as Visiting Researcher at Berkman Klein Center for Internet and Society at Harvard University, Visiting Scholar at the Allens Hub for Technology, Law and Innovation at UNSW Sydney, as well as Visiting Fellow at Graduate Institute of International and Development Studies in Geneva.  In 2019, Professor Lin was appointed to serve on the Board of Trustees of the Academy of Food Law and Policy, United States.  In 2023, he was elected to serve as Vice Chair of the International Law and Technology Interest Group (ILTechIG) of the American Society of International Law.</p>\r\n\r\n<p>Active in legal academia, Professor Lin has been invited to talk in many academic/practical settings, and his legal scholarship has appeared in leading journals and edited collections.  Professor Lin has received the Junior Research Award, Outstanding Research Award of Hou De Association, and CTM Research Award from NTHU as well as the Ta-You Memorial Award from Taiwan’s Ministry of Science and Technology.</p>','https://chingfulin.net/','National Tsing Hua University','Director, Interdisciplinary Program of Management and Technology','National Tsing Hua University','教授',NULL),(64,0,9999,'AI','陳舜伶','Shun-Ling Chen','shun-ling-chen','Government Data Management - Lessons from the US Evidence Act and Beyond','中文','no','X','Academia Sinica','Institutum Iurisprudentiae','/img/speaker/d6db2682.jpeg',NULL,NULL,NULL,'Governments worldwide are actively promoting the transition towards data-driven governance while also endorsing the release of government data to foster research and innovation. However, a critical first step is to establish effective government data governance framework and practices. In Taiwan, we are still in the early stages of developing such initiatives. In this presentation, I will introduce the Evidence Act (Foundations for Evidence-Based Policy-Making Act) of the United States, including the data governance framework it promotes. While this legislation serving as just one example, it can offer valuable insights to help us assess the challenges and shortcomings of our current regulatory framework in Taiwan.',NULL,'Shun-Ling Chen is a associate research professor at Institutum Iurisprudentiae Academia Sinica (IIAS). She also co-directs the Information Law Center at IIAS. Her fields of research include: copyright, privacy, internet governance, online collaboration, community governance, citizen science and data governance.','','https://www.iias.sinica.edu.tw/en/member_post/16?class=12','','','Academia Sinica\r','副研究員',NULL),(65,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(66,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(67,0,9999,'AIK','張嘉淵','Ted Chang','ted-chang-aik','Prompting The Future: Transforming Medicine through Generative AI','中文','yes','X','Quanta Computer','CTO','/img/speaker/e2bb31df.jpg',NULL,NULL,NULL,'Medicine, a discipline rooted in centuries of knowledge and practice, is  now at the brink of one of its most transformative phases, spurred by the  rise of generative AI. This speech delves into this impending revolution,  shedding light on how artificial intelligence is poised to reshape our  healthcare paradigms from the perspective of Quanta Computer, a  leading AI platform provider for smart medicine and digital health. From  AI-driven diagnostics that predict with unprecedented accuracy to  personalized treatments tailored to individual genetic imprints, we are  witnessing the dawn of a new era. This discourse not only celebrates the  remarkable innovations that AI promises but also engages in a critical  examination of the challenges and ethical dilemmas it presents. As we  navigate this uncharted territory, the speech emphasizes the need for  synergy between human insight and machine intelligence, ensuring that  the future of medicine is not just technologically advanced but also',NULL,'Dr. Ted Chang is a highly accomplished Chief Technology Officer, Vice President and General Manager of Quanta Computer, which is the world’s largest computer ODM and laptop computer maker. He has more than 20 years of experience in leading global corporations and has been instrumental in driving corporate technology strategy and global research partnership. In addition, Dr. Chang is responsible for overseeing the Quanta Research Institute (QRI) for advanced research and BU12, a business unit dedicated to integration of AI, IoT and cloud computing as a platform solution for smart transformation of Heathcare, Medicine and Agriculture. Dr. Chang has been appointed as representatives of Taiwan for APEC Business Advisory Council (ABAC) since 2019. Academically, Dr. Chang holds various guest professorships in the EECS colleges of National Taiwan University (NTU), National Cheng-Kung University (NCKU), Asia University (AU) and the AI college of National Yang-Ming Chao-Tung University (NYCU). He serves as a member of the board for several educational and research foundations, including the Epoch Foundation, Spring Foundation, Quanta Culture and Education Foundation (QCEF), Chinese Medical Advancement Foundation, and Ming Dao Culture and Education Foundation. Among many honors, Dr. Chang recently received the Japan Good Design Best 100 award in 2022, five REDDOT Design Awards on Smart Medicine (2021 and 2022), and IF Design Award on Smart Agriculture in 2021. He was also awarded distinguished alumni awards from both NCKU and Chia-Yi High School in 2021. He led the Quanta-NCTU Joint AI Center to win the CES Innovation Award and WITSA in 2020 Award. He was the chief advisor to the Taiwan Pavilion “Swingphony” at London Design Biennale 2020. Dr. Chang is a prolific inventor with over 220 patents granted globally by Oct. 2022. His invention in 2001, \"\"A Network Object Delivery System for Personal Computing Device,\"\" defined the \"\"Application Module Store.\"\" Dr. Chang joined Quanta in 2000, promoted as VP in 2009 and promoted as the first CTO in Quanta history in 2010. Since 2004, Dr. Chang has led the strategic research collaboration on future computing with MIT Computer Science and Artificial Lab (CSAIL) to support the transformation of Quanta. The partnership started with TParty project on Human Centric Computing, Qmulus Project on Cloud Computing and now on AIM project with focus on AI medicine and computational health. Dr. Chang\'s past projects, One Laptop Per Child (OLPC) and the QRI research model, were published as business cases by Harvard Business School.','<p>Dr. Ted Chang is a highly accomplished Chief Technology Officer, Vice President and General Manager of Quanta Computer, which is the world’s largest computer ODM and laptop computer maker. He has more than 20 years of experience in leading global corporations and has been instrumental in driving corporate technology strategy and global research partnership. In addition, Dr. Chang is responsible for overseeing the Quanta Research Institute (QRI) for advanced research and BU12, a business unit dedicated to integration of AI, IoT and cloud computing as a platform solution for smart transformation of Heathcare, Medicine and Agriculture.</p>\r\n<p>Dr. Chang has been appointed as representatives of Taiwan for APEC Business Advisory Council (ABAC) since 2019. Academically, Dr. Chang holds various guest professorships in the EECS colleges of National Taiwan University (NTU), National Cheng-Kung University (NCKU), Asia University (AU) and the AI college of National Yang-Ming Chao-Tung University (NYCU). He serves as a member of the board for several educational and research foundations, including the Epoch Foundation, Spring Foundation, Quanta Culture and Education Foundation (QCEF), Chinese Medical Advancement Foundation, and Ming Dao Culture and Education Foundation.</p>\r\n<p>Among many honors, Dr. Chang recently received the Japan Good Design Best 100 award in 2022, five REDDOT Design Awards on Smart Medicine (2021 and 2022), and IF Design Award on Smart Agriculture in 2021. He was also awarded distinguished alumni awards from both NCKU and Chia-Yi High School in 2021. He led the Quanta-NCTU Joint AI Center to win the CES Innovation Award and WITSA in 2020 Award. He was the chief advisor to the Taiwan Pavilion “Swingphony” at London Design Biennale 2020.</p>\r\n<p>Dr. Chang is a prolific inventor with over 220 patents granted globally by Oct. 2022. His invention in 2001, \\\"\\\"A Network Object Delivery System for Personal Computing Device,\\\"\\\" defined the \\\"\\\"Application Module Store.\\\"\\\" Dr. Chang joined Quanta in 2000, promoted as VP in 2009 and promoted as the first CTO in Quanta history in 2010. Since 2004, Dr. Chang has led the strategic research collaboration on future computing with MIT Computer Science and Artificial Lab (CSAIL) to support the transformation of Quanta. The partnership started with TParty project on Human Centric Computing, Qmulus Project on Cloud Computing and now on AIM project with focus on AI medicine and computational health. Dr. Chang\\\'s past projects, One Laptop Per Child (OLPC) and the QRI research model, were published as business cases by Harvard Business School.</p>',NULL,'','','Quanta\r','技術長',NULL),(68,0,9999,'AI','蔡明順','Richie Tsai','richie-tsai','人才破繭生成未來：AIA人才能力認證計畫','中文','yes','V','Taiwan AI Academy','Provost','/img/speaker/8a66be76.jpg',NULL,NULL,NULL,'',NULL,'Richie Tsai is the provost of Taiwan AI Academy and takes overall responsibility for the academy\'s AI talent training, strategy on developing consulting services, startup coaching, technology promotion, community management, industry-university bridging, and career development. Prior to joining Taiwan AI Academy, Richie was Senior Director at SAP Greater China, ever worked for Oracle and Teradata where he helped leading enterprises to navigate their digital transformation. He graduated from Fu Jen Catholic University in 1996 and received his MBA degree from San Diego State Univeristy in 2003. He is pursuitng PhD degree in National Tsing Huwa University.  學歷：清華大學跨院國際博士班 - 智慧製造與數位決策 現職：台灣人工智慧學校 校務長 / 國科會 TAIWAN AICoE 策略委員會委員 / 台灣氣候聯盟 - 綠色與數位科技委員會召集人 專長：AI, Big Data, 數位轉型, SaaS 經歷：20 多年經驗在資訊工程、產品管理、營運、市場 行銷、生態系統培育 • SAP 德商思愛普 大中華區資深副總經理 • Oracle 美商甲骨文 應用軟體部副總經理 • Teradata 美商天睿資訊系統 資深協理','<p>Richie Tsai is the provost of Taiwan AI Academy and takes overall responsibility for the academy\'s AI talent traini資深協理ng, strategy on developing consulting services, startup coaching, technology promotion, community management, industry-university bridging, and career development. Prior to joining Taiwan AI Academy, Richie was Senior Director at SAP Greater China, ever worked for Oracle and Teradata where he helped leading enterprises to navigate their digital transformation. He graduated from Fu Jen Catholic University in 1996 and received his MBA degree from San Diego State Univeristy in 2003. He is pursuitng PhD degree in National Tsing Huwa University.</p>\r\n\r\n<p>學歷：清華大學跨院國際博士班 - 智慧製造與數位決策</p>\r\n<p>現職：台灣人工智慧學校 校務長 / 國科會 TAIWAN AICoE 策略委員會委員 / 台灣氣候聯盟 - 綠色與數位科技委員會召集人</p>\r\n<p>專長：AI, Big Data, 數位轉型, SaaS</p>\r\n<p>經歷：20 多年經驗在資訊工程、產品管理、營運、市場 行銷、生態系統培育</p>\r\n<ul>\r\n<li style=\"list-style-type:disc\"> SAP 德商思愛普 大中華區資深副總經理</li>\r\n<li style=\"list-style-type:disc\"> Oracle 美商甲骨文 應用軟體部副總經理</li>\r\n<li style=\"list-style-type:disc\"> Teradata 美商天睿資訊系統 資深協理</li>\r\n</ul>','https://en.aiacademy.tw/key-executives/','','','Taiwan AI Academy\r','校務長',NULL),(69,0,9999,'AIK','Lawrence Lessig','','lester-lawrence-lessig','AI and the Law','英文','yes','X','Harvard University','Law School','/img/speaker/74940cbe.jpg',NULL,NULL,NULL,'AI will change law fundamentally. The only question is whether it will change it in ways we like. There is no doubt that the technology will radically alter how we make and practice law. Through code, those changes will enhance the rule of law. But they will also  make urgent the need to better govern the values that law embeds and makes real. In principle, AI could make law orders of magnitude better. In practice, we have yet to demonstrate — at least we in America — the capacity to govern that this new technology demands.',NULL,'Lawrence Lessig is the Roy L. Furman Professor of Law and Leadership at Harvard Law School. (The Roy Furman chair is in honor of this extraordinary alumnus.)  Prior to rejoining the Harvard faculty, where he was the Berkman Professor of Law until 2000, Lessig was a professor at Stanford Law School, where he founded the school’s Center for Internet and Society, and at the University of Chicago.  Lessig clerked for Judge Richard Posner on the 7th Circuit Court of Appeals and Justice Antonin Scalia on the United States Supreme Court. He serves on the Board of the AXA Research Fund, and is an Emeritus member of the board at Creative Commons.  Lessig is a Member of the American Academy of Arts and Sciences, and the American Philosophical Association, and has received numerous awards, including the Free Software Foundation’s Freedom Award, Fastcase 50 Award.  In 2002, he was named one of Scientific American’s Top 50 Visionaries.  Lessig holds a BA in economics and a BS in management from the University of Pennsylvania, an MA in philosophy from Cambridge, and a JD from Yale.  ▍現任：哈佛大學法學院教授 ▍學歷：耶魯大學法學博士、劍橋大學哲學碩士、賓州大學經濟與管理雙學士 ▍經歷：史丹佛大學法學院教授並創設學網路與社會中心、芝加哥大學法學院教授、Equal Citizens 創辦人、Creative Commons 創始董事會成員、AXA 研究基金科學委員會、美國藝術與科學院、美國哲學會等成員 ▍研究：憲法學者，著有 13 本專書、9 篇書籍專章等 89 篇著作，其中論述科技 vs.法律的著作共 44 篇 ▍榮譽：獲 The New Yorker 評為網路世代最重要的智財思想家 (2002)、獲 Webby 獎、科學美國人 50 獎、Fastcase 50 獎等','<p>Lawrence Lessig is the Roy L. Furman Professor of Law and Leadership at Harvard Law School. (The Roy Furman chair is in honor of this extraordinary alumnus.)</p>\r\n\r\n<p>Prior to rejoining the Harvard faculty, where he was the Berkman Professor of Law until 2000, Lessig was a professor at Stanford Law School, where he founded the school’s Center for Internet and Society, and at the University of Chicago.</p>\r\n\r\n<p>Lessig clerked for Judge Richard Posner on the 7th Circuit Court of Appeals and Justice Antonin Scalia on the United States Supreme Court. He serves on the Board of the AXA Research Fund, and is an Emeritus member of the board at Creative Commons.</p>\r\n\r\n<p>Lessig is a Member of the American Academy of Arts and Sciences, and the American Philosophical Association, and has received numerous awards, including the Free Software Foundation’s Freedom Award, Fastcase 50 Award.  In 2002, he was named one of Scientific American’s Top 50 Visionaries.</p>\r\n\r\n<p>Lessig holds a BA in economics and a BS in management from the University of Pennsylvania, an MA in philosophy from Cambridge, and a JD from Yale.</p>\r\n\r\n<ul>\r\n<li>▍現任：哈佛大學法學院教授</li>\r\n<li>▍學歷：耶魯大學法學博士、劍橋大學哲學碩士、賓州大學經濟與管理雙學士</li>\r\n<li>▍經歷：史丹佛大學法學院教授並創設學網路與社會中心、芝加哥大學法學院教授、Equal Citizens 創辦人、Creative Commons 創始董事會成員、AXA 研究基金科學委員會、美國藝術與科學院、美國哲學會等成員</li>\r\n<li>▍研究：憲法學者，著有 13 本專書、9 篇書籍專章等 89 篇著作，其中論述科技 vs.法律的著作共 44 篇</li>\r\n<li>▍榮譽：獲 The New Yorker 評為網路世代最重要的智財思想家 (2002)、獲 Webby 獎、科學美國人 50 獎、Fastcase 50 獎等</li>\r\n</ul>\r\n<style>.me_desc li {\r\n    margin-left: 4em;\r\n    text-indent: -4em;\r\n}</style>','https://lessig.org','','','Harvard University','Furman Professor of Law and Leadership','KEYNOTE '),(70,1,9999,'HOST','蔡宗翰','Richard Tzong-Han Tsai','richard-tzong-han-tsai','','中文','no','簡報70','Academia Sinica','Research Fellow (Professor)','/img/speaker/f05a3a64.png',NULL,NULL,NULL,'',NULL,'','',NULL,'蔡宗翰 研究員 (Academia Sinica)','','Academia Sinica\r','研究員',NULL),(71,1,9999,'HOST','張順教','Shun-Chiao Chang','shun-chiao-chang','','中文','no','簡報71','National Taiwan University of Science and Technology','Professor, Dept. of Business Administration','/img/speaker/8439704f.jpg',NULL,NULL,NULL,'',NULL,'','',NULL,'張順教 教授 (Taiwan Tech University)','','Taiwan Tech University\r','教授',NULL),(72,1,9999,'HOST','楊朝棟','Chao-Tung Yang','chao-tung-yang','','中文','no','簡報72','Tunghai University','Lifetime Distinguished Professor, Dept. of Computer Science','/img/speaker/322c2a28.jpeg',NULL,NULL,NULL,'',NULL,'','',NULL,'楊朝棟 終身特聘教授 (Tunghai University)','','Tunghai University','終身特聘教授',NULL),(73,1,9999,'HOST','邱銘傳','Chiu, Ming-Chuan','chiu-ming-chuan','','中文','no','簡報73','National Tsing Hua University','Professor, Dept. Industrial Engineering and Engineering Management','/img/speaker/ca4a35df.jpg',NULL,NULL,NULL,'',NULL,'','',NULL,'邱銘傳 教授 (National Tsing Hua University)','','National Tsing Hua University\r','教授',NULL),(74,1,9999,'HOST','李家岩','Chia-Yen Lee','chia-yen-lee','','中文','no','簡報74','National Taiwan University (NTU)','Professor, Dept. of Information Management','/img/speaker/2f548973.jpg',NULL,NULL,NULL,'',NULL,'','',NULL,'李家岩 教授 (National Taiwan University)','','National Taiwan University\r','教授',NULL),(75,1,9999,'HOST','翁紹仁 ','Shao-Jen Weng','shao-jen-weng','','中文','no','簡報75','Tunghai University','Professor, Dept. of Industrial Engineering and Enterprise Informatio','/img/speaker/9db2065d.jpg',NULL,NULL,NULL,'',NULL,'','',NULL,'翁紹仁 教授 (Tunghai University)','','Tunghai University\r','教授',NULL),(76,1,9999,'HOST','許嘉裕','Chia-Yu, Hsu','chia-yu-hsu','','中文','no','簡報76','National Taiwan University of Science and Technology','Professor, Dept. of Industrial Management','/img/speaker/1ef16e79.jpg',NULL,NULL,NULL,'',NULL,'','',NULL,'許嘉裕 教授 (Taiwan Tech University)','','Taiwan Tech University\r','教授',NULL),(77,1,9999,'HOST','郭秉宸','Benjamin Kuo ','benjamin-kuo','','中文','no','X','Taiwan AI Academy','Vice President for Industry-Academia Collaboration','/img/speaker/cc0fea7b.jpg',NULL,NULL,NULL,'',NULL,'','',NULL,'郭秉宸 產學長 (Taiwan AI Academy)','','Taiwan AI Academy\r','產學長',NULL),(78,0,9999,'AI','胡瑛敏','Amy Hu','amy-hu','Generative AI on Intel® architecture','中文','yes','X','Intel','Taiwan Site Manager, Habana Labs','/img/speaker/2e6f0078.jpg',NULL,NULL,NULL,'Generative AI is causing impacts across various industries worldwide. For Taiwan\'s industries, it represents a significant challenge, but also a rare opportunity. Currently, there are numerous open-source generative AI pre-trained models, platforms services and resources available. The ability to optimize open-source pre-trained models and tools will be crucial for unique competitive advantages.  Intel AI Everywhere can accelerate innovation throughout the entire AI product development cycle. It allows you to maximize the value of your products and services, and enables easy deployment on both the cloud and edge, while maintaining information security and regulatory compliance. Through examples of popular applications like Stable Diffusion and Llama2 in generative AI, we will explore how the advantages of Intel\'s software and hardware architecture empower everyone to grasp the opportunities of generative AI.  生成式AI正在對全球各個產業帶來衝擊，對臺灣產業是巨大挑戰，更是難得的機遇. 目前有許多 open source 的生成式AI 預訓練模型跟平台服務與資源，擁有優化開源預訓練模型與工具的能力將會是產生獨特競爭力的關鍵.  Intel AI Everywhere可以加速整個AI產品開發週期的創新,讓你的產品與服務價值最大化,並且可以方便的在受到資安保護且符合法規的條件下布署到cloud以及edge. 透過最熱門的stable diffusion 以及llama2等生成式AI應用實例的方享, 探討Intel 軟硬體架構的優勢如何讓大家掌握生成式AI的機遇.','<p>Generative AI is causing impacts across various industries worldwide. For Taiwan\'s industries, it represents a significant challenge, but also a rare opportunity. Currently, there are numerous open-source generative AI pre-trained models, platforms services and resources available. The ability to optimize open-source pre-trained models and tools will be crucial for unique competitive advantages.</p>\r\n\r\n<p>Intel AI Everywhere can accelerate innovation throughout the entire AI product development cycle. It allows you to maximize the value of your products and services, and enables easy deployment on both the cloud and edge, while maintaining information security and regulatory compliance. Through examples of popular applications like Stable Diffusion and Llama2 in generative AI, we will explore how the advantages of Intel\'s software and hardware architecture empower everyone to grasp the opportunities of generative AI.</p>\r\n\r\n<p>生成式AI正在對全球各個產業帶來衝擊，對臺灣產業是巨大挑戰，更是難得的機遇. 目前有許多 open source 的生成式AI 預訓練模型跟平台服務與資源，擁有優化開源預訓練模型與工具的能力將會是產生獨特競爭力的關鍵.</p>\r\n\r\n<p>Intel AI Everywhere可以加速整個AI產品開發週期的創新,讓你的產品與服務價值最大化,並且可以方便的在受到資安保護且符合法規的條件下布署到cloud以及edge. 透過最熱門的stable diffusion 以及llama2等生成式AI應用實例的方享, 探討Intel 軟硬體架構的優勢如何讓大家掌握生成式AI的機遇。</p>','美商英特爾公司 DCAI 部門, Habana Labs 台灣區總經理, 負責製造及支援平台的客戶。  ','',NULL,'','','Intel\r','Habana Lab總經理',NULL),(79,1,9999,'	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	','	',NULL,NULL,NULL),(80,0,9999,'AI','黃彥男','Yennun Huang','huang-yennun','Academia Sinica Service LLM Wisdom: Knowing What it Actually Don\'t Know','中文','yes','X','Academia Sinica','Research Center for Information Technology Innovation,  Director','/img/speaker/fe12e592.png',NULL,NULL,NULL,'With the rise of large language models, many companies and organizations have attempted to leverage this powerful tool to manage their proprietary data. At Academia Sinica, we are also focused on developing a useful LLM service system, SinicaWisdom, to facilitate administrative work. Generally, large language models provide responses based on the information they have encountered in the training data. However, when faced with questions they cannot answer, large language models tend to provide incorrect responses rather than admitting they don\'t know. This behavior necessitates a significant amount of effort in terms of re-inspection or re-examination.  Furthermore, to restrict the information used by large language models for proprietary data, an information retrieval system is typically employed as the front-end system to initially gather documents relevant to the question. This practice limits the knowledge that LLMs can access and exacerbates this issue. In this presentation, we will discuss how we have enabled SinicaWisdom to \"acknowledge what it does not know\" and provide additional helpful information instead of simply stating \"I cannot answer.\"','<p>With the rise of large language models, many companies and organizations have attempted to leverage this powerful tool to manage their proprietary data. At Academia Sinica, we are also focused on developing a useful LLM service system, SinicaWisdom, to facilitate administrative work. Generally, large language models provide responses based on the information they have encountered in the training data. However, when faced with questions they cannot answer, large language models tend to provide incorrect responses rather than admitting they don\'t know. This behavior necessitates a significant amount of effort in terms of re-inspection or re-examination.</p>\r\n\r\n<p>Furthermore, to restrict the information used by large language models for proprietary data, an information retrieval system is typically employed as the front-end system to initially gather documents relevant to the question. This practice limits the knowledge that LLMs can access and exacerbates this issue. In this presentation, we will discuss how we have enabled SinicaWisdom to \"acknowledge what it does not know\" and provide additional helpful information instead of simply stating \"I cannot answer.\"</p>','Dr Huang is the Director for Research Center for Information Technology Innovation (CITI), Academia Sinica, Taiwan. He is also a Board Member, of TRADE-VAN, a Joint Professor of IoT Research Center, Natiaon Taiwan university, a Joint Professor of College of AI, National Yan Ming Chiao Tung University and a Supervisor of Taiwan AI Academy. Dr. Huang received his PhD in Computer Science from University of Maryland. He Joined AT&T Bell Labs in 1989. His work on Software Implemented Fault Tolerance (SwiFT) tools was applied to tens of telecommunication systems in AT&T and was named one of the ten major technology breakthroughs in Bell Laboratories in 1992. He became a Distinguished Member of Technical Staff of Bell Labs in 1996. He started the Dependable Computing Research Department in AT&T in 1999 and was the department head to ensure the high dependability of all AT&T services. In 2004, Dr. Huang became the Executive Director of Dependable Distributed Computing and Communication Research Department to lead AT&T dependability research programs. In 2007, Dr. Huang became the Executive Vice President of Institute for Information Industry of Taiwan. Dr. Huang has more than 20 US patents and 150 papers published in well-known journals and conferences. His Software rejuvenation paper was awarded Jean-Claude Laprie Award in 2019. Dr. Huang was also the Deputy Executive Secretary of Science and Technology Advisory Group of Executive Yuan, helping Taiwan Government on the Information and Communication Technology development policy and funding allocation between 2010 and 2015. Dr. Huang is an IEEE Fellow.','','https://www.citi.sinica.edu.tw/pages/yennunhuang/contact_en.html','','','Academia Sinica','特聘研究員',NULL),(81,0,9999,'AI','古倫維',' Lun-Wei Ku','lun-wei-ku','Academia Sinica Service LLM Wisdom: Knowing What it Actually Don\'t Know','中文','yes','X','Academia Sinica','Institute of Information Science, Research Fellow','/img/speaker/77d2d0b7.jpg',NULL,NULL,NULL,'With the rise of large language models, many companies and organizations have attempted to leverage this powerful tool to manage their proprietary data. At Academia Sinica, we are also focused on developing a useful LLM service system, SinicaWisdom, to facilitate administrative work. Generally, large language models provide responses based on the information they have encountered in the training data. However, when faced with questions they cannot answer, large language models tend to provide incorrect responses rather than admitting they don\'t know. This behavior necessitates a significant amount of effort in terms of re-inspection or re-examination.  Furthermore, to restrict the information used by large language models for proprietary data, an information retrieval system is typically employed as the front-end system to initially gather documents relevant to the question. This practice limits the knowledge that LLMs can access and exacerbates this issue. In this presentation, we will discuss how we have enabled SinicaWisdom to \"acknowledge what it does not know\" and provide additional helpful information instead of simply stating \"I cannot answer.\"','<p>With the rise of large language models, many companies and organizations have attempted to leverage this powerful tool to manage their proprietary data. At Academia Sinica, we are also focused on developing a useful LLM service system, SinicaWisdom, to facilitate administrative work. Generally, large language models provide responses based on the information they have encountered in the training data. However, when faced with questions they cannot answer, large language models tend to provide incorrect responses rather than admitting they don\'t know. This behavior necessitates a significant amount of effort in terms of re-inspection or re-examination.</p>\r\n<p>Furthermore, to restrict the information used by large language models for proprietary data, an information retrieval system is typically employed as the front-end system to initially gather documents relevant to the question. This practice limits the knowledge that LLMs can access and exacerbates this issue. In this presentation, we will discuss how we have enabled SinicaWisdom to \"acknowledge what it does not know\" and provide additional helpful information instead of simply stating \"I cannot answer.\"</p>','received her Ph.D. degree in Computer Science and Information Engineering from National Taiwan University, Taipei, Taiwan, in 2009. She joined the Institute of Information Science, Academia Sinica as an assistant research fellow in Aug., 2012, and was promoted to be an associate research fellow in Aug., 2018.  Her research expertise lies in natural language processing and information retrieval, especially in sentiment analysis and opinion mining. She often publishes papers in top conferences including ACL, AAAI, SIGIR, WWW, NAACL, and EMNLP. She is very active in the research community, and the international professional activities she involves include the general chair and the program chair of StarSem 2021, StarSem 2019 and AIRS 2019, and the area chair of ACL, NjAACL 2021, ACL, EMNLP, COLING 2020, EMNLP 2019, ACL 2017, CCL 2016, NLPCC 2016, ACL-IJCNLP and EMNLP 2015. Her research is internationally recognized and has been served as the AFNLP Member-at-Large and ACL SIGHAN Asia Information Officer.  She is very experienced in academic and industrial collaborations. Her research collaborators come from US, Singapore, Sweden and Israel, and she is currently working with data companies and banks. Her current research topics focus on recommendation, visual storytelling, sensational text generation, fake news intervention, knowledge-based question answering, lie detection and social media analysis.','<p>received her Ph.D. degree in Computer Science and Information Engineering from National Taiwan University, Taipei, Taiwan, in 2009. She joined the Institute of Information Science, Academia Sinica as an assistant research fellow in Aug., 2012, and was promoted to be an associate research fellow in Aug., 2018.</p>\r\n\r\n<p>Her research expertise lies in natural language processing and information retrieval, especially in sentiment analysis and opinion mining. She often publishes papers in top conferences including ACL, AAAI, SIGIR, WWW, NAACL, and EMNLP. She is very active in the research community, and the international professional activities she involves include the general chair and the program chair of StarSem 2021, StarSem 2019 and AIRS 2019, and the area chair of ACL, NjAACL 2021, ACL, EMNLP, COLING 2020, EMNLP 2019, ACL 2017, CCL 2016, NLPCC 2016, ACL-IJCNLP and EMNLP 2015. Her research is internationally recognized and has been served as the AFNLP Member-at-Large and ACL SIGHAN Asia Information Officer.</p>\r\n\r\n<p>She is very experienced in academic and industrial collaborations. Her research collaborators come from US, Singapore, Sweden and Israel, and she is currently working with data companies and banks. Her current research topics focus on recommendation, visual storytelling, sensational text generation, fake news intervention, knowledge-based question answering, lie detection and social media analysis.</p>','https://homepage.iis.sinica.edu.tw/pages/lwku/contact_en.html','','','Academia Sinica\r','研究員',NULL),(82,0,9999,'AI','尹維作','Steven Yin','steven-yin','Welcome to SysMoore Era - What can AI/ML EDA Tools to Unleash the Moore Law?','中文','yes','X','Synopsys','Sr. Sales Director','/img/speaker/f6fe926e.png',NULL,NULL,NULL,'In the SysMoore era, we are facing a lot of challenges. This talk will cover “The Five Overarching Themes” in the current IC design, including (i) PPA push, (ii) First Tapeout works, (iii) Multi-die/3D systems, (iv) Safe, secure, resilience silicon, and (v) Productivity. How Synopsys EDA uses AI/ML to cope with those challenges. ',NULL,'  Steven Yin is currently the senior sales director at Synopsys Taiwan, leading a team focused on managing relationships with major foundries and IC design companies. He joined Synopsys Taiwan in 2003, following successful roles as sales leader in Agilent Technologies and Taiwan local start-up IC design company. Steven is with extensive experience of semiconductor industry, including manufacturing processes, IC design methodology, and application market trend.',NULL,NULL,'','','Synopsys','業務副總經理',NULL),(83,1,9999,'致詞嘉賓','賴清德','Lai Ching-teTaiwan','lai-ching-te','','中文','no','簡報83','R.O.C.','Vice President','/img/speaker/1d383a4d.jpg',NULL,NULL,NULL,'',NULL,'',NULL,NULL,'','','R.O.C.','副總統',NULL);

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