凡人小北· @frxiaobei · X·· 12 小时前AI 评分54
AI 导读
Karpathy 估算约 75% 的人几乎没接触过 LLM,约 20% 偶尔用免费级 ChatGPT 类产品,约 0.2% 的数学与代码专业者用前沿 Agent 完成过去需数周数月的项目,另有极少数内部用户接触前沿系统。作者小北引述称,争论双方体验到的根本不是同一种东西,只试过免费聊天机器人容易把正在发生的变化误判为炒作。
正文
大家对 AI 的争论,可能是在讨论三种完全不同的产品。
Karpathy 粗略估算:
大多数人几乎没接触过 LLM;
约 20% 的人偶尔用免费聊天机器人;
真正用前沿 Agent 完成大型专业任务的,大约只有 0.2%。
所以有人觉得 AI 只是更好用的搜索框,有人却已经看到过去几个月的工作被压到几天。他们并不是观点不同,而是体验到的根本不是同一种东西。
这很危险。如果只试过免费聊天机器人,就很容易把正在发生的变化判断成炒作。
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. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. 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.在 X 查看被引用的帖子
来源:凡人小北 · x.com