Remix.run Logo
guywithahat 17 hours ago

> why not do it in C?

A legitimate point, there are lots of performance and fine grain changes you can make, and it's a simple, common language many people use. Perhaps we could realize some of these benefits from a simple, fast language.

> Or hell, why not do it in x86 assembly?

A terrible take imo. This would be impossible to debug and it's complex enough you likely won't see any performance improvements from writing in assembly. It's also not portable, meaning you'd have to rewrite it for every OS you want to compile on.

I think there's an argument that if machines are writing code, they should write for a machine optimized language. But even using this logic I don't want to spend a bunch of time and money writing multiple architectures, or debugging assembly when things go wrong.

thefaux 17 hours ago | parent [-]

If the boosters are correct about the trajectory of llm performance, these objections do not hold.

Debugging machine code is only bad because of poor tooling. Surely if vibe coding to machine code works we should be able to vibe code better debuggers. Portability is a non issue because the llm would have full semantic knowledge of the problem and would generate optimal, or at least nearly optimal, machine code for any known machine. This would be better, faster and cheaper than having the llm target an intermediate language, like c or rust. Moreover, they would have the ability to self-debug and fix their own bugs with minimal to no human intervention.

I don't think there is widespread understanding of how bloated and inefficient most real world compilers (and build systems) are, burning huge amounts of unnecessary energy to translate high level code, written by humans who have their own energy requirements, to machine code. It seems highly plausible to me that better llms could generate better machine code for less total energy expenditure (and in theory cost) than the human + compiler pair.

Of course I do not believe that any of the existing models are capable of doing this today, but I do not have enough expertise to make any claims for or against the possibility that the models can reach this level.