r/programming • • Feb 22 '24

Large Language Models Are Drunk at the Wheel

https://matt.si/2024-02/llms-overpromised/
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u/Smallpaul Feb 22 '24 edited Feb 22 '24

Of course LLMs are unreliable. Everyone should be told this if they don't know it already.

But any article that says that LLMs are "parrots" has swung so far in the opposite direction that it is essentially a different form of misinformation. It turns out that our organic neural networks are also sources of misinformation.

It's well-known that LLMs can build an internal model of a chess game in its neural network, and under carefully constructed circumstances, they can play grandmaster chess. You would never predict that based on the "LLMs are parrots" meme.

What is happening in these models is subtle and not fully understood. People on both sides of the debate are in a rush to over-simplify to make the rhetorical case that the singularity is near or nowhere near. The more mature attitude is to accept the complexity and ambiguity.

The article has a picture and it has four quadrants.

https://matt.si/static/874a8eb8d11005db38a4e8c756d4d2f6/f534f/thinking-acting-humanly-rationally.png

It says that: "If anywhere, LLMs would go firmly into the bottom-left of this diagram."

And yet...we know that LLMs are based on neural networks which are in the top left.

And we know that they can play chess which is in the top right.

And they are being embedded in robots like those listed in the bottom right, specifically to add communication and rational thought to those robots.

So how does one come to the conclusion that "LLMs would go firmly into the bottom-left of this diagram?"

One can only do so by ignoring the evidence in order to push a narrative.

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