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Comment by saiojd | Hacker News Reader

While I agree that the claims are hyperbolic, I think you are approaching this paper from the point of view of someone who knows a lot about sorting. Because of this, its normal that the claims of these guys who probably don't know much about it are grating for you.

But, at its core, this is really a RL paper. The objective is to see how far a generic approach can work while understanding as little as possible about the actual domain. After AlphaGo exceeded expectations, the question becomes: "What else can RL do, and can it do anything actually useful?", and this paper seems to suggest that it can optimize code pretty well! I'm really not sure they are self-aggrandizing in terms of impact. The impact of an approach like this could potentially be very large (although I'm not saying that it actually is, I don't know enough).

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Sorting is not a niche topic. Anybody who majored in CS (which is a ton of people these days) will read the abstract and most of the paper thinking "Wow, I can't believe they discovered something better than O(N log N)" because that's usually what people mean when they say "better sorting algorithm". What they discovered here is effectively a new compiler optimization. They should present it as such instead of calling it a new sorting algorithm.

But ya, discovering a new compiler optimization automatically is kinda cool.

70% better than O(N log N) is still O(N log N).

It's 70% better than O(1). The algorithms it found are for sort3, sort4, and sort5, which were poorly optimized in LLVM's libc++.

It may have also laundered those from open-source code that wanted to optimize sort3, sort4, and sort5.

I see your point. I just went over the abstract again and I totally agree.

> because that's usually what people mean when they say "better sorting algorithm"

Is it really? I've heard of a few "better sorting algorithms" and it's never meant that in my experience.

When people say "sorting algorithm" they mean something like bubble sort or merge sort.

Tbh people who majored in CS are supposed to know that it was proven long ago that better than O(N log N) sorting (in general case) is impossible.

I hope people majoring in CS will not think that, as they learned that n log n is the theorically best complexity for a sort algorithm. They will rather think that they found an algorithm with better constants in front of n log n.

true that

Anyone who does any basic algorithmic CS stuff would have been exposed to sorting algorithms, their variations, sorting networks and so on.

There are already superoptimizers who use genetic algorithms to find the most optimal code sequence for small easily verifiable tasks. That is also a form of reinforcement learning in a way

When one has a big fuck off hammer, everything becomes a nail. Seems to apply to ML too.

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