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Karpathy:LLM 能力认知鸿沟扩大为漏斗

X:Andrej Karpathy (@karpathy) 2026-10-12 04:53 复制原文 已复制
Andrej Karpathy 重发并扩展其 4 月的观点,认为外界对 LLM 能力的共识差距正从“两群人各说各话”变成一个急剧收窄的漏斗。

Andrej Karpathy 重发并扩展其 4 月的观点,认为外界对 LLM 能力的共识差距正从“两群人各说各话”变成一个急剧收窄的漏斗。

另有 1 家信源报道正文Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.

The funnel is driven by a combination of factors:1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.3. Access. Free-tier, paid-tier, internal.

So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

来源:Andrej Karpathy · x.com