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Comment by jacobsenscott | Hacker News Reader

Nice. While there may be some impracticalities to actually doing this for twitter, 99% of the software out there could run on a fraction of a single commodity server. People complain about the carbon burn of crypto, and they are right, but I bet it is dwarfed by the carbon burn of all the shitty over-provisioned and over-architected CRUD apps running interpreted languages. Unfortunately with universities teaching python of all things we'll have (or maybe already do have) a whole generation of developers that actually have no idea how powerful a modern computer is.

I suppose there's a chance AI will get to the point where we can feed it a ruby/python/js/whatever code base and it can emit the functionally equivalent machine code as a single binary (even a microservices mess).

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I've been experimenting with GPT3 as a "compiler" and it's always amazing when it works. Extrapolating from here, I think this is right on the nose -- we feed in any high level language and get reasonably efficient assembly out the other end, furthermore, the assembly is more human-like than a compiler would give you.

There's some big problems with this approach today, namely, it's not always right, and it may sometimes be half right (miss edge cases).

But think of where this AI technology is headed -- it stands to reason it will eventually work pretty much perfect.

And then I think we'll see another very strong trend -- large AI models replacing other forms of software. Why write a compiler when GPT3 can compile C to asm? Why write an interpreter when GPT3 can "compile" python to C?

The AI model is hilariously less-efficient than traditional software, but it will be far far cheaper and faster to create than the traditional equivalent.

What other types of software will be replaced by AI models?

I think people overestimate how much CPU time a typical CRUD app spends on actual business logic, even with an interpreted language like Ruby or Python. What I’ve seen is the bottleneck is largely memory, such that you can pack a ton of these apps on a machine with a few cores and a lot of RAM.

The stuff that actually is CPU-bound often ends up being written in an appropriate language, or uses C extensions (e.g. ML and data science libraries for Python).

Sometimes. But in a rails app, and probably any app using an orm, transforming database rows to activerecord objects makes the cpu go brrr. And thats all ruby code. A port of AR to rust would be amazing, but idk how feasible given all the metaprogramming.

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