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by Eddy_Viscosity2
2 days ago
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When I see these sorts of debates about LLMs thinking, its rarely a disagreement about what LLMs do. Its almost always over how 'thinking' is defined and the two sides use different definitions but don't actually communicate to each other what those definitions are because they assume the other side is using the same one. The loosest definition of thinking is along the lines of anything that can process information in a useful way. Basic calculators can therefore think about adding two numbers. The strictest definitions tend to on the side that it is linked to the nebulous concept of consciousness and therefore cannot ever be machine generated. In that we don't even really understand how humans think, so how could we possibly know if machines can do it. |
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There is a common misconception that LLM are simply a "statistical process" that doesn't feature any abstract conception of the tokens it is predicting. There are studies that show that such features do exist - that there is discernible structure built into the weights - and that the process of inference is a very rich one.
The statistical process exists but it is the substrate in which the model is implemented - or more accurately - grown.
If you can predict Magnus Carlsen's next move then you are just as good at chess as Magnus - and being that good absolutely does require reasoning.
If you can predict the solution to an open Erdos problem that stumped hundreds of people for decades...