Is this written in jest? Because it's very likely where the future of computing is heading. See <a href="https://www.youtube.com/watch?v=kZRE7HIO3vk" rel="nofollow">https://www.youtube.com/watch?v=kZRE7HIO3vk; a lot of people were nagging on Casey because he implied that software was more efficient back when everyone "wrote their own kernel" and how "impossible it would be today". He even mentions how awesome it could be if every game came with it's own bootable USB. Now back then it truly was unthinkable, but today we're edging ever closer to that reality.
For instance, I have a working microkernel written in a Lisp dialect for embedded devices. Compiled to native machine code. 100% LLM generated. ~70k loc. In benchmarks it outperforms most other embedded kernel projects by a significant margin. And it only took around ~$1500 in tokens (API costs all included).
When AI proves theorems, it uses divide-and-conquer approach just as humans - it breaks a big theorem into lemmas and tackles lemmas one by one.
An alternative approach where it is just one big-ass logical expression is just not better.
Same thing with code, I think - you need some intermediate results like a calling convention, helper subroutines, etc.
A sufficiently powerful AI can do compilation "mentally" - i.e. producing machine code conforming to a specific calling convention. It can also decompile machine code. But you, obviously, don't gain anything doing it this way, if there's one-to-one correspondence between high-level code and machine code. You might as well just write high-level code.
I really hope that software becomes more efficient. But I don't think that it can only be done by generating machine code directly.
comboy · · focus · HN ↗
rfgplk · · focus · HN ↗
For instance, I have a working microkernel written in a Lisp dialect for embedded devices. Compiled to native machine code. 100% LLM generated. ~70k loc. In benchmarks it outperforms most other embedded kernel projects by a significant margin. And it only took around ~$1500 in tokens (API costs all included).
killerstorm · · focus · HN ↗
An alternative approach where it is just one big-ass logical expression is just not better.
Same thing with code, I think - you need some intermediate results like a calling convention, helper subroutines, etc.
A sufficiently powerful AI can do compilation "mentally" - i.e. producing machine code conforming to a specific calling convention. It can also decompile machine code. But you, obviously, don't gain anything doing it this way, if there's one-to-one correspondence between high-level code and machine code. You might as well just write high-level code.
I really hope that software becomes more efficient. But I don't think that it can only be done by generating machine code directly.