i dont think theres anything that makes it essentiall that llms are non-deterministic though
if you rewrote the math to be all fixed point precision on big ints, i think you would still get the useful LLM results?
if somebody really wanted to make a compiler in an LLM, i dont think that nondetermism is problem
id really imagine an llm compiler being a set of specs, dependency versions, and test definitions to use though, and you'd introduce essential nondetermism by changing a version number, even if the only change was the version name from "experimental" to "lts"
Unfortunately not. Various implementation details like attention are usually non-deterministic. This is one of the better blog posts I'm aware of:
https://thinkingmachines.ai/blog/defeating-nondeterminism-in...
i dont think theres anything that makes it essentiall that llms are non-deterministic though
if you rewrote the math to be all fixed point precision on big ints, i think you would still get the useful LLM results?
if somebody really wanted to make a compiler in an LLM, i dont think that nondetermism is problem
id really imagine an llm compiler being a set of specs, dependency versions, and test definitions to use though, and you'd introduce essential nondetermism by changing a version number, even if the only change was the version name from "experimental" to "lts"
They're not inherently non-deterministic, correct. And floating point is deterministic enough, as that blog post is demonstrating.
When they run on the deterministic hardware, yes. When they run on some large, parallel, varying-unpredictable-load-dependent-latency hardware, no.