Oh boy. Someone didn't get the memo that for LLMs, tokens are units of thinking . I.e. whatever feat of computation needs to happen to produce results you seek, it needs to fit in the tokens the LLM produces. Being a finite system, there's only so much computation the LLM internal structure can do per token, so the more you force the model to be concise, the more difficult the task becomes for it - worst case, you ca…
Yeah, I don't think that "I'd be happy to help you with that" or "Sure, let me take a look at that for you" carries much useful signal that can be used for the next tokens.
Caveman: Why use many token when few token do trick
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Re: Caveman: Why use many token when few token do trick
#102Re: Caveman: Why use many token when few token do trick
#103Earlier quoted context omitted.
The burden of proof is on the author to provide at least one type of eval for making that claim.
I notice that the number of people confidently talking about "burden of proof" and whose it allegedly is in the context of AI has gone up sharply. Nobody has to proof anything. It can give your claim credibility. If you don't provide any, an opposing claim without proof does not get any better.
Re: Caveman: Why use many token when few token do trick
#104Re: Caveman: Why use many token when few token do trick
#105Earlier quoted context omitted.
You obviously do not speak other languages. Other cultures have different constrains and different grammar. For example thinking in modern US English generates many thoughts, to keep correct speak at right cultural context (there is only one correct way to say People Of Color, and it changes every year, any typo makes it horribly wrong). Some languages are far more expressive and specialized in logical conditions, co…
>Some languages are far more expressive and specialized in logical conditions, conditionals, recursion and reasoning. Like eskimos have 100 words for snow, but for boolean algebra. This is simply not true.
It is very arrogant to assume, no other language can be more advanced than English.
Re: Caveman: Why use many token when few token do trick
#106Re: Caveman: Why use many token when few token do trick
#107Re: Caveman: Why use many token when few token do trick
#108Re: Caveman: Why use many token when few token do trick
#109Re: Caveman: Why use many token when few token do trick
#110Earlier quoted context omitted.
Yeah, I don't think that "I'd be happy to help you with that" or "Sure, let me take a look at that for you" carries much useful signal that can be used for the next tokens.
There is a study that shows that what the model is doing behind the scenes in those cases is a lot more than just outputting those tokens. For an LLM, tokens are thought. They have no ability to think, by whatever definition of that word you like, without outputting something . The token only represents a tiny fraction of the internal state changes made when a token is output. Clearly there is an optimal for each tas…