TL;DR version: 1. Current LLM (Layered Modeling) is the result of brute force in engineering, with fundamental flaws in the underlying model, such as a lack of logic and native memory. 2. The previously insurmountable gaps in skills and experience between individuals are being rapidly bridged by AI. 3. In an era where powerful tools are cheap and readily available, the ability to invoke and drive AI's capabilities is more decisive than years of hard-earned fundamental skills. 4. The core competency is Context Engineering. When AI becomes a universal digital prosthetic, the winner will be determined by who can perform "context engineering" more accurately. Managing memory, filtering information, and synchronizing cognitive gaps across different sessions will be key to effectively utilizing AI in the future.
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Benson Sun
@BensonTWN
02-21
2023 年,Meta 首席 AI 科學家楊立昆給當時的 LLM 熱潮潑了一盆冷水。
他指出 LLM 有根本性的缺陷:沒有持久記憶、無法從單一經驗學習、缺乏對物理世界的理解。本質上,它只是在做「下一個 token 的預測」。
從學術的角度看,他說得完全正確。
直到今天,LLM
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