Recall that the Python primitive “sort” corresponds to a long segment of assembly code in the compiler.
This analogy is a bit off because Python isn’t compiled, it’s interpreted at runtime. Also, compilers don’t output assembly language, they output binary machine code (assembly is what you use to write machine code by hand, basically). So it would be better to talk about C and machine code rather than Python and assembly.
Aside from that I thought that was a very interesting post with some potentially powerful ideas. I’m a little skeptical of how practical this kind of prompt-programming could be though because every new LLM (and probably every version of an LLM, fined-tuned or RLHF-ed differently) is like a new CPU architecture and would require a whole new “language/compiler” to be written for it. Perhaps these could be adapted in the same way that C has compilers for various CPU architectures, but it would be a lot of work unless it could be automated. Another issue is that the random nature of LLM evaluation means it wouldn’t be very reliable unless you set temperature=0 which apparently tends to give weak results.
This analogy is a bit off because Python isn’t compiled, it’s interpreted at runtime. Also, compilers don’t output assembly language, they output binary machine code (assembly is what you use to write machine code by hand, basically). So it would be better to talk about C and machine code rather than Python and assembly.
Aside from that I thought that was a very interesting post with some potentially powerful ideas. I’m a little skeptical of how practical this kind of prompt-programming could be though because every new LLM (and probably every version of an LLM, fined-tuned or RLHF-ed differently) is like a new CPU architecture and would require a whole new “language/compiler” to be written for it. Perhaps these could be adapted in the same way that C has compilers for various CPU architectures, but it would be a lot of work unless it could be automated. Another issue is that the random nature of LLM evaluation means it wouldn’t be very reliable unless you set temperature=0 which apparently tends to give weak results.