Comment by dvt

Comment by dvt 3 months ago

> Is anyone doing it this way?

I'm working on a way of invoking tools mid-tokenizer-stream, which is kind of cool. So for example, the LLM says something like (simplified example) "(lots of thinking)... 1+2=" and then there's a parser (maybe regex, maybe LR, maybe LL(1), etc.) that sees that this is a "math-y thing" and automagically goes to the CALC tool which calculates "3", sticks it in the stream, so the current head is "(lots of thinking)... 1+2=3 " and then the LLM can continue with its thought process.

namaria 3 months ago

Cold winds are blowing when people look at LLMs and think "maybe an expert system on top of that?".

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sanderjd 3 months ago

I don't think it's "on top"? I think it's an expert system where (at least) one of the experts is an LLM, but it doesn't have to be LLMs from bottom to top.

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- namaria 3 months ago
  
  On the side, under, wherever. The point is, this is just re-inventing past failed attempts at AI.
  
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  sanderjd 3 months ago
  
  Except past attempts didn't have the ability to pass on to modern foundation models.
  Look, I dunno if this idea makes sense, it's why I posed it as a question rather than a conviction. But I broadly have a sense that when a new technology hits, people are like "let's use it for everything!", and then as it matures, people find more success in interesting it with current approaches, or even trying older ideas but within the context of the new technology.
  And it just strikes me that this "routing to tools" thing looks a lot like the part of expert systems that did work pretty well. But now we have the capability to make those tools themselves significantly smarter.
  
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sanderjd 3 months ago

Definitely an interesting thought to do this at the tokenizer level!

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