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    11comments
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Chat-based Large Language Models replicate the mechanisms of a psychic's con

23 pointsby 1h agosoftwarecrisis.dev
11 comments
29m agoHN ↗

Man I remember back when a psychic conned me by solving the Navier-Stokes problem.

Also >July 4th, 2023

24m agoHN ↗

Did an AI do that on its own though? I heard it was human mathematicians using a sophisticated machine as a tool.

19m agoHN ↗

It sounds like LLMs were pretty useful to them…

8m agoHN ↗

All of the latest big proofs were driven by professional human mathematicians steering and priming the models, yes.

All of the best AI-made software projects are also driven by experienced human software developers steering and priming the models. Does that mean the projects "aren't made by AI"?

No, it just means AI is not quite good enough yet to fully replace humans, and, so, unsurprisingly, the best results will be obtained from people who are already great at a field and who take the time to squeeze as much force multiplication out of LLMs as possible. The AI is still doing well over 95% of the significant work.

11m agoHN ↗

But were you successfully conned into believing an AI had solved the Navier-Stokes problem?

27m agoHN ↗

All of this is accurate (and useful). But yeah, psychics do not prove theorems from frontier math and build working complex software.

21m agoHN ↗

This is a strange newsletter post. It’s harping against AI but seems AI-written itself.

Its ultimate conclusion:

“I’ve come to the conclusion that a language model is almost always the wrong tool for the job.

I strongly advise against integrating an LLM or chatbot into your product, website, or organisational processes.”

Seems so obviously biased that I can only understand it with the context that the writer is trying to sell their book for €35

12m agoHN ↗

The post makes sense for 2023. Today, not so much.

Also, definitely not AI written if the date is accurate.

12m agoHN ↗

Just realized this was written in 2023. Can’t believe how wrong we were about AI back then.

8m agoHN ↗

Can't believe how right we were, too.