Will a prompt that enables GPT-4 to solve easy Sudoku puzzles be found?

The title is funny to me. We should consider a new computation complexity class for LLMs. Let&#x27;s call the ones that can be solved with a prompt, Promptable. For the problems that we cannot reliably solve with a single prompt yet, let&#x27;s call them non-deterministic promptable, or NP.<p>Question is, for most of these hard problems, is there a prompt that can solve them? Better yet, is there a prompt good enough that we collapse all of the hardest problems in NP with a single prompt?<p>Will we ever know if NP can be reduced to P???

An LLM is a tool. It is a very versatile tool. It can be used in many situations. It does not therefore follow that it should be used in all situations. Even if you wanted to use an AI to solve sudoku, there is no particular reason to begin with a model trained for language modeling instead of a model better suited to the task.

Austin from Manifold here - cool to see this trending! I thought the structure of this prediction market was especially cool, as it forms a collaborative, crowdsourced puzzle challenge to generate the perfect prompt.<p>(I&#x27;ve personally bet yes, but not sure if that prediction is holding up...)

&gt; Easy-rated Sudoku puzzle means a puzzle classified as easy by any reputable Sudoku site or puzzle generator. This market plans to use the LA Times(Sudoku - Free daily Sudoku games from the Los Angeles Times (latimes.com)) for judging, but I maintain the option to use a different Sudoku generator.<p>Is there any theoretical reason why an attention based llm could or couldn&#x27;t generate an answer to an NP hard problem? As I understand, attention is N^2, but it&#x27;s not obvious if that&#x27;s relevant to the complexity of problems that can be solved. It&#x27;s obviously not relevant to answers that are regurgitated, which may be all answers?<p>It would be better if &quot;easy&quot; had a mathematical definition.

A relevant PR:<p><a href="https:&#x2F;&#x2F;github.com&#x2F;ggerganov&#x2F;llama.cpp&#x2F;pull&#x2F;1773">https:&#x2F;&#x2F;github.com&#x2F;ggerganov&#x2F;llama.cpp&#x2F;pull&#x2F;1773</a>

I haven&#x27;t seen prediction contacts that can be resolved at 50% before. It seems like that throws off the interpretation of the probability.

For most sudoku puzzles solving each cell is a logic puzzle that can be expressed in words just as current solvers have it in code. It can try to solve each vacant cell in turn using each of its rules until it finds a solution for that cell. And then it can be told to keep trying to solve another cell until it finishes the puzzle. Brute force with a core of logic.

Unlikely, for reasons explained in this video: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;bEovhfxJsM4?t=2339" rel="nofollow noreferrer">https:&#x2F;&#x2F;youtu.be&#x2F;bEovhfxJsM4?t=2339</a><p>However, apparently it can write a program using the Z3 SAT solver to find a solution.

Unlikely, for reasons explained in this video: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;bEovhfxJsM4?t=2339" rel="nofollow noreferrer">https:&#x2F;&#x2F;youtu.be&#x2F;bEovhfxJsM4?t=2339</a><p>However, it apparently can write a program using the Z3 SAT solver to find a solution.

Will a prompt that enables a prompt that enables GPT-4 to solve easy Sudoku puzzles be found ?<p>I don&#x27;t know how much meta-prompting have been explored. Maybe it&#x27;s where The Singularity is at ?

Can we use this technology to find a recognizable pattern in any complex blob of data? Is that how this works?<p>How about, &quot;Given 100000 readings from a person&#x27;s body&#x2F;brain, determine whether they are lying&quot;. Can we do that?

Seeing this thread makes me want to bust out some Prolog.

Only allowing 50 generations makes this very hard.