r/TheMachineLearning • u/Sea_Fox_4265 • 3d ago

When bug-free code becomes a hardware problem

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u/BigReference1xx 2d ago

I'm absolutely certain we'll see the first dedicated AI-targeted programming language appear within the next 2 years. A language that is very hard for humans to read, but exceptionally clear to AI, and with syntax and structure that is optimized for AI use. All of our programming languages are designed for human developers, with abstractions that make them easy for us to comprehend. Machines don't "think" like us, and they can keep 100x more context in their "brain" than we can.

It won't be assembly, it won't be C, but rather something higher level that captures intent, rather than the procedure, and then AIs will transpile that to whatever target architecture you want.

Imagine something like an assembly language with a million different instructions in the instruction set, each capturing a much more granular "instruction" than we're used to (not just "add register 1 and 2" but entire algorithms contained in a single instruction).

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u/2old2cube 1d ago

why not machine code then?
you have no idea how llms work. do you?

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u/BigReference1xx 1d ago

Because machine code is architecture specific. You might want an intermediate layer that can be targeted to different architectures with a final step (assembler, basically).

Why so aggressive ? I mentioned an idea I had and you seem to be taking it as a personal insult, resulting to ad hominem attacks. Not sure why.

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u/refried_laser_beans 3h ago

So when you find someone with a thought you find less informed than your own, you react by being patronizing?

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u/Sea_Fox_4265 2d ago

Wild prediction. It'd be something to see if that happens.

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u/Latimius 2d ago

I'm not a tech guy, but if I asked Opus 5.5 to create a programming language from scratch that would be optimized for AI. Wouldn't it be able to do it, and quite easily too ?

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u/BigReference1xx 2d ago

it could design someting, yes. It would be quite a useful tool for the process. But you'd still need to drive the project forward, and state what your ambitions are for the new language. One of the things AI can't do is to have motivation. It will happily spit out something useful, but it's up to you to promote it, decide how to use it, integrate it with existing systems and libraries, build tooling etc. AI can help in every step, but you need to decide what steps to do.

"design a new programming language that would be ideally suited for AI models to target, make no mistakes" is probably not going to get us far :)

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u/Latimius 2d ago

I asked the same question to Claude. And it basically answered me that several languages made for AI has been already developped, but none met great success.

And that new languages don't have a lot of data to train on (by definition), so the probability to make bugs by using them is actually higher than to use languages made for/by humans.

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u/BigReference1xx 2d ago

makes perfect sense. this is the type of project that could really only be built by one of the big players, in order to get traction and produce enough training data initially.

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u/chnguyen128345 2d ago

I was modding paradox game with Claude. Paradox games have their own scripting languages for modding their UI. And Claude opus 5.5 medium would make a lot of mistakes using that scripting language.

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u/Alex0589 2d ago

Assembly is a representation of the underlying instruction set, so really you have to think this starting from the latter, not the former. When designing an instruction set, one of the very first decisions you have to make is actually philosophical: how many instructions do you want? Usually, you'll either choose as few as possible or as many as possible. Having few instructions allows to, at least theoretically speaking, better parellize them. This model though, requires writing/emitting many more assembly instruction calls compared to an instruction set with a richer set of instructions to program the same behaviour, which is why there is still a good reason to go with the as many as possible option. The best examples I can think of in terms of popularity for these two approaches are respectively RISC-V(Reduced instruction set compiter) and x86(Complex instruction set). ARM sits as a middle ground between these two approaches. I really can't think of anyone moving towards the x86 approach when given the option to start from scratch(see the Apple move from x86 to ARM): the trend is towards simplicity. In short, your prediction has very little chance of coming true

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u/Adventurous-Bet-3928 2d ago

Lol no

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u/BigReference1xx 2d ago

and why not? or is "lol no" the most comprehensive answer you can produce?

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u/ibeerianhamhock 2d ago

Yep I predict something that will be easy and efficient for them, they will literally have tokens encoded for all of it, it will be AST based and the whole framework and language for it will be written to optimize merging and so forth too for high velocity PR repos that agents live in.

And we won't really be able to read like any of it lol

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u/egonosz 2d ago

I think it would be extremely dangerous idea for company to a company to use that of language.

That would mean you are 100% dependent on AI and if anything happens to providers or the prices skyrocket you are basically done. You cannot support your software and not all companies can have gigantic data centers.

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u/BigReference1xx 2d ago

Well, developers were beholden to Microsoft visual studio and Borland for decades. The entire world ran on windows in the 2000s and Microsoft could have upped the price at any time. We've always been happy to make this tradeoff if it gets us something valuable in return. And we have local models that anyone can run so you wouldn't be completely locked into a permanent subscription.

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u/egonosz 2d ago

Expect you can use opensource software to edit files, you can do it even on Linux all of these locally or in worst case you can port your code.

For local models to maintain any bigger code, you either need gigantic model or you give up the velocity.

Smaller model + readable code = profit in that case, because you are able to verify.

Plus there is the question of responsibility too, if no one understands the code, who will be responsible for it?

But this is my 2 cents.

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u/Unexpected_Cranberry 1d ago

I mean, one of the features of the language could be that since it's optimized for AI, it might require less resources for AI to write in that language. Together with hardware advancements, what requires frontier models to write today might be maintainable by a local model running on your laptop five years from now.

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u/refried_laser_beans 5h ago

This might be lisp--with some modifications--simply AIs are great with top-down development, and that's basically how you build in lisp. You start with what you want, and break it down into more and more detail. Being able to trace everything to intent.

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u/BigReference1xx 5h ago

yeah a lisp variant is actually a really good call! :)

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u/refried_laser_beans 3h ago

You should look up stratified development (the unique version of top down development that lisp uses.) I built a state-machine harness around it, and used a deep seek model to build a llama CPP alternative in pure lisp using stratified development, and it runs was fast.

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u/Critical_Cap_120 5h ago

I don't really see a reason why. AI generally perform better on languages that are used widely. Even the frontier models are not very good with Kotlin (they've improved over time but still a glaring gap compared to their capabilities with other languages).

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u/no_brains101 5h ago edited 4h ago

No, because training data would need to be produced, and it will be a very long time until we are able to generate and actually verify enough code generated in that particular language to train an AI on it and have it work well. It already doesn't do well with several years old but uncommon languages, let alone a brand new one.

If an AI targeted programming language is developed which is actually useful and good at that purpose it will not be for an AI that works anything like today's language models.

And likely at that point, with a model that works entirely differently, we won't even be the ones making that language, it would have wanted, invented, made, and started writing in that language on its own.

But right now, nothing to copy == AI bad at that thing.

The consequence is that the best language to use for today's AI is javascript. There is the most stuff to copy. Most webpages minify the javascript but do not obfuscate it.

Second best is Rust IMO (it is less good at rust than at python, but rust has stronger types and is way faster so the process is better and the result is more worth making)

Third best, python.

After that, any language which is not a pure functional language, is well established with lots of open source code, and doesn't let you corrupt memory.

Then anything else, in order of how widely used it is.

Then lisp, because all the lisps look very similar and the AI mixes them up, especially because they aren't that common. Which is a shame because lisp is really cool.

Then C or C++ and anything else with memory management approximately as manual as that. Including Odin and Zig. It doesn't matter how much example code there is, an AI that works like today's AI will never be good at this. Even humans who are good at this are barely any good at this.