name2---->(字串長度:0)---->Edward Wei(字串長度:10)```anchor---->speaker-16(字串長度:10)---->edward-wei(字串長度:10)```talk_title---->Autonomous System Design Considerations(字串長度:39)---->Evolution of Autonomous Systems: Core Architectures and Taiwan’s Unique Advantages(字串長度:84)```talk_title2---->自主系統進化論: 關鍵架構是台灣機會(字串長度:50)---->自主系統進化論：關鍵架構與台灣優勢(字串長度:51)```can_playback---->(字串長度:0)---->X(字串長度:1)```company---->瑞昱半導體(字串長度:15)---->Realtek Semiconductor Corp.(字串長度:27)```position---->資深顧問(字串長度:12)---->Senior Advisor, President Office(字串長度:32)```company2---->(字串長度:0)---->National Science and Technology Council (NSTC)(字串長度:46)```position2---->(字串長度:0)---->Domain Expert,  Science & Technology Policy Research and Information Center (STPI)(字串長度:82)```desc---->(字串長度:0)---->Over eons, synaptic connectivity endowed animals’ carbon-based brains with high-dimensional processing for survival and decision-making. We now approximate the perceive–understand–decide pipeline with ANNs and multimodal models, while modern silicon handles large, high-dimensional data within explicit energy and latency budgets.
Building truly human-like autonomous systems still faces critical bottlenecks, demanding disruptive architectures to maintain consistent performance in dynamic, unpredictable environments on a few-tenths-of-a-watt power budget.
Many autonomous systems still center on a compute-intensive, centralized “System 2,” paired with a low-latency sequence-generation engine (the so-called “System 1”). While fine for labs or simulations, this design makes balanced trade-offs among reliability, size, mass, and energy efficiency nearly impossible; the absence of proprioception impedes long-horizon consistency, robustness, and adaptability.
Shift from centralized compute-first to layered, bottom-up autonomy centered on distributed proprioception: low-latency, low-power perception–action loops (the real System 1) handle immediate responses; a predictive, adaptive brain (System 2) governs strategy. Evolutionary distillation and related methods optimize each subsystem’s energy efficiency, mass, volume, reliability, and safety.
Leveraging strengths in semiconductor manufacturing, advanced packaging, and embedded-system integration, Taiwan is well positioned to drive and define the low-power, high-volume sensing and actuation chiplet markets, building up a complete supply chain of “neural reflex systems” (low-latency, real-time reaction subsystems) for the autonomous systems and robotics industry. This will not only reduce dependence on ultra-high-compute “brains” but also strengthen Taiwan’s position in the global ecosystem ahead of large-scale commercialization of autonomous robots and intelligent systems, and enhance its strategic influence in future end-to-end system competition.

經過漫長的演化，動物的大腦靠突觸把神經細胞連起來，慢慢長出「高維度資訊處理」的能力，才能在複雜環境中存活與決策。對應到今天，我們用人工神經網路（ANNs）與多模態模型，在功能層面近似「感知→理解→決策」的流程；同時，現代矽基硬體也能在明確的能耗與延遲預算內，處理大量高維度資料。
但要做出真正「類人」的自主系統，還卡著關鍵瓶頸：要在動態、難預測的場景裡長時間保持穩定表現，而且功耗只有二十多瓦，必須採用更顛覆的新架構。
目前許多自主系統仍以計算密集、集中式的「System 2」為核心，再配一個低延遲的序列生成引擎（所謂「System 1」）。這在實驗室或模擬環境或許可行，但一到實務現場，就很難同時兼顧可靠性、尺寸、重量與能效；而且欠缺本體感知（proprioception），使得長期一致性、穩健度與適應力都受限。
解法是從「算力集中優先」轉到「由下而上、以分散式本體感知為核心」的分層自主架構：由低延遲、低功耗的感知—動作融合迴路（真正的 System 1）負責即時反應；上層由更會預測、能調適的「大腦」子系統（System 2）負責策略治理。配合演化式蒸餾等方法，各子系統可分別在能效、質量、體積、可靠性與安全性上做到最佳化。
台灣的優勢在這裡特別關鍵：我們結合半導體製造、先進封裝與嵌入式整合，有機會主導低功耗、高出貨量的感測與致動 chiplet（小晶片）市場，建立面向自主系統與機器人產業的「神經反射系統」（低延遲、即時反應子系統）完整供應鏈。這不只減少對超高算力「大腦」的依賴，也能在大規模商用化之前，強化台灣在全球生態系的地位，並提升未來端到端系統競爭中的戰略影響力。
(字串長度:4007)```me_desc---->(字串長度:0)---->Edward has 20+ years of leadership in technology development, organic growth hacking, fabless IC design, and computer networking. He advances Realtek’s autonomous systems and robotics research, helps plan its medical-device business, coordinates the CVC task force, co-chairs AITA’s Emerging AI Processor SIG, advises the NSTC’s S&T Policy Adviser Office, and has served for 15 years as senior adviser to Realtek’s Office of the President. He also advises startups pro bono on building sustainable growth.

Before 2000, he founded or co-founded several companies, then joined Realtek, contributing to SoC technology and the internetworking business. His expertise spans semiconductor physics, hardware/software co-design, organic growth hacking, viral marketing, AI, and medical devices. Outside work, he gardens and farms—especially roses and fruit trees—and enjoys country music as an amateur banjo player and singer.

He holds an M.S. in Electrical Engineering from USC, where he received the Academic Achievement Award. In 1991, he developed the first markup-language network content-presentation technology using SNMP/MIB (before html), and in 2000 he invented the first MCU-based network controller to connect “everything” to the Internet (now called IoT). He founded four community/social-service initiatives, has mentored 10+ startups, authored 30+ articles, and holds 20+ patents.(字串長度:1405)```talkfile_link---->(字串長度:0)---->X(字串長度:1)```website---->(字串長度:0)---->https://www.linkedin.com/in/edwei-ai/(字串長度:37)