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Why are we so caught up on LLMs as the means of a self-healing program though? In fact why has all popular ML conversation lately been reduced down to just LLMs
by Solvency 3y ago
Why are we so caught up on LLMs as the means of a self-healing program though? In fact why has all popular ML conversation lately been reduced down to just LLMs? It just seems like there are so many other wild potential implementations that could be derived from the core math/theory but most of the world typically just waits for something to latch onto (like LLMs), rather than seek to produce something entirely new.
There was just a post about convex optimization on HN. I don't understand why researchers aren't creating mathematical/statistical models of programming languages (hell, even Lisp) and creating radically avant-garde self-optimizing processes that run on emergent/generative sandboxed code subsets, which can optimize over time, which then literally be woven back into the operating codebase itself. Hell you could even have it build procedurally generated internal tests and heuristics for itself.
- graypegg 3y ago100%. Based on the headline, I was imagining some kind of jacked-up refactoring tools. Most implementations of Rename Symbol will catch references in strings as well, but will it get a name of a factory method that spits out that object? Or maybe changing the type signature for a method implies that some contant in your ENV should actually be a int and not a string now. I assure you that teams at Jetbrains or Microsoft or wherever are working away on how to integrate more deep learning into their tools. This is just… deploys with added dice rolls.