坦白說，生成式AI的發展並不如預期順利
本文認為，生成式AI，特別是大型語言模型（LLMs），正遭遇重大挑戰。文章指出其在可信度、過度依賴記憶而非真正理解、缺乏可量化價值，以及擴大規模無法解決根本問題等方面均面臨困境。
Marcus on AI
Let’s be honest, Generative AI isn’t going all that well
A sampling of recent news
Some recent news, all long anticipated by this newsletter:
LLMs can still cannot be trusted:
A large fraction of what LLMs do is mostly just memorization (and Hinton was on the wrong side of this argument):
They still aren’t adding a lot of quantifiable value to the world:
Update: This is consistent with the finding of the Remote Labor Index that AI could only do about 2.5% of jobs, reported recently by the Washington Post.
Scaling isn’t going all that well, anymore, and probably won’t cure these problems.
Trying to orient our economy and geopolitical policy around such shoddy technology — particularly on the unproven hopes that it will dramatically improve– is a mistake.
dang I knew i had seen something else recently that i meant to include. now added as an update on #3.
The fundamental problem with generative AI is that the creators overpromised. The underlying technology itself is fine. There is a real business here.
It is just not what the creators are saying it is. It is substantially smaller and less significant.
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