[qsera]

>No, it's not equivalent to nested if statements.

It is. If you control the randomness involved, the output of a model is completely deterministic. Which means that it can be represented by a huge lookup table.

Anything that can be represented by a lookup table can be expressed as an `if then else` statement.

[fc417fc802]

By that logic sin(x) is equivalent to a lookup table. Yeah, you can approximate it that way. But doing so at any reasonable level of precision will quickly become an exercise in the absurd. Neural networks are far worse, consisting of stacks of massive linear combinations fed into nonlinear functions.

Regardless, it remains irrelevant to the subject at hand. You're going off on a tangent rather than admit your initial claim was wrong.

[qsera]

>By that logic sin(x) is equivalent to a lookup table

NO!

`sin(x)` is continuous, so the domain is infinite.

But an LLM model is not a continuous function, and thus the domain of a LLM model is finite (set of all possible tokens). So using a lookup table for a model behavior would be exact and not an approximation. So it can indeed be represented by an if statement of finite size.

Hence proved!

If you don't understand something in what I wrote, I can clarify if you tell me where you have trouble following.

[basch]

That’s not true in practice thought https://sulbhajain.medium.com/why-llms-arent-truly-determini...

[fc417fc802]

Even if it were true he would still be wrong. I wish HN had some mechanic to evict these sorts of troll accounts that attempt to score rhetorical points rather than honestly learning about a subject. The usual vote and flag mechanics don't work here because there's no singular and overt violation of the guidelines taking place.

[qsera]

that is why I said

>If you control the randomness involved