Sorting a finite number of elements in a sequence, is a very narrow application of AI, akin to playing chess. Usually very simple approaches like RL work totally fine for problems like these, but auto-regression/diffusion models have to take steps that are not well defined at all, and the next step towards solving the problem is not obvious.
As an example, imagine a robot trying to grab a tomato from a table. It's arm extends across 1 meter maximum, and the tomato is placed 0.98 meters away. Is it able to grab the tomato from the point it stands, or it needs to move closer, and only then try to grab the tomato?
That computation should better be calculated deterministically. Deterministic computation is faster, cheaper and more secure. It has to prove that: $tomato_distance + $tomato_size < $arm_length. If this constraint is not satisfied, then: move_closer(); Calculate again:$tomato_distance + $tomato_size < $arm_length.
From the paper:
> Our system employs a custom interpreter that parses "LLM-Thoughts" (represented as DSL code snippets) to generate First Order Logic programs, which are then verified by a Z3 theorem prover.
I don't understand your claim about 'Deterministic computation is faster, cheaper and more secure.' That's not true at all.
In fact, for many problems the fastest and simplest known solutions are non-deterministic. And in eg cryptography you _need_ non-determinism to get any security at all.
Couldn't disagree more.
Sorting a finite number of elements in a sequence, is a very narrow application of AI, akin to playing chess. Usually very simple approaches like RL work totally fine for problems like these, but auto-regression/diffusion models have to take steps that are not well defined at all, and the next step towards solving the problem is not obvious.
As an example, imagine a robot trying to grab a tomato from a table. It's arm extends across 1 meter maximum, and the tomato is placed 0.98 meters away. Is it able to grab the tomato from the point it stands, or it needs to move closer, and only then try to grab the tomato?
That computation should better be calculated deterministically. Deterministic computation is faster, cheaper and more secure. It has to prove that: $tomato_distance + $tomato_size < $arm_length. If this constraint is not satisfied, then: move_closer(); Calculate again:$tomato_distance + $tomato_size < $arm_length.
From the paper:
> Our system employs a custom interpreter that parses "LLM-Thoughts" (represented as DSL code snippets) to generate First Order Logic programs, which are then verified by a Z3 theorem prover.
> Sorting a finite number of elements in a sequence, is a very narrow application of AI, [...]
Sorry, I did not suggest you should use AI to sort numbers. I was solely replying to this:
> Small steps of nondeterministic computation, checked thoroughly with deterministic computation every so often, and the sky is the limit.
You don't necessarily need your checks to be deterministic.
In fact, it's often better for them to be not deterministic.
See also https://fsharpforfunandprofit.com/series/property-based-test...
I don't understand your claim about 'Deterministic computation is faster, cheaper and more secure.' That's not true at all.
In fact, for many problems the fastest and simplest known solutions are non-deterministic. And in eg cryptography you _need_ non-determinism to get any security at all.