The author is attacking the field of theoretical algorithm design broadly as being useless. If we take the author's logic to its conclusion, many algorithms we learn about in a standard Algorithm Design course such as "median of medians" (finding the median in a list in O(n) worst-case time) is useless because it is not used in practice. Even the original 2019 Harvey–van der Hoeven result, showing integration multiplication can be done in O(n log n), has a galactic overhead and no applications.

> theory gets so unmoored from the original question that an “open problem” becomes nothing more than an academic status puzzle...The theory of computer science has become a form of mathematics that doesn’t concern itself with computers, and it offers little reward for impact outside those mathematical pursuits

I thought it is common knowledge (and a common warning from profs to first-year CS students) that computer science has very little to do with computers. The very concept of Turing machines and decidability are mathematical in nature, far removed from how computers these days are run. The undecidability of Wang tiling, for example, is definitely a notable CS result, but it has nothing to do with computers." It is essentially a branch of mathematics. "Computer Science Is Not About Computers, Any More Than Astronomy Is About Telescopes" is a famous quote attributed to Dikstra. There is even famous MIT Open Courseware clip: https://youtu.be/2Op3QLzMgSY?t=30

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eldenring an hour ago | parent | next [-]

I don't think that is necessarily true, the post is making a stronger point than what you describe

> Indeed, the algorithm requires you to multiply complex numbers whose magnitudes grow superpolynomially with n. If you stored these numbers as bits, the memory requirement would effectively be exponential in the input length. It assumes you can multiply such arbitrarily large complex numbers together in a single operation.

Another way to think about what the author said, imagine you had access to an oracle which could execute arbitrary precision arithmetic expressions in constant time. You could encode a wide range of computations in these and execute impossible algorithms.

	▲	yorwba 4 minutes ago \| parent \| next [-]
		Replace the complex numbers with a finite field and O(1) arithmetic stops being an unrealistic assumption, as you can actually perform the required operations in constant time on a real computer. You can't do that for infinitely-precise complex numbers, but you'll never be able to provide an infinitely-precise complex number as the input anyway. If you start with finite-precision numbers (e.g. 64-bit floats) you can do all operations in a finite-field representation (e.g. the Ozaki scheme II is an actually practical implementation of that idea for matrix multiplication https://arxiv.org/abs/2504.08009 ) and the magnitude of intermediate values is no longer a problem.
	▲	skew-aberration an hour ago \| parent \| prev \| next [-]
		This reminds me of 'O(1)' hash maps, but far more egregious.
	▲	eldenring an hour ago \| parent \| prev [-]
		actually thinking about it more I think my oracle model is more powerful than the computer used in openai's fft but maybe its a good way to think about it.

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calf an hour ago | parent | prev | next [-]

The irony being Dijkstra had lots of deep ideas about how programming ought to be done (from a basic science approach as informed by CS) and that the industry is still in the stone/bronze ages in terms of putting advanced ideas into practice.

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wredcoll an hour ago | parent | prev [-]

A lovely theory, and yet the field is called "computer science".

Also, while I am not an expert, I suspect it is frequently useful to understand how telescopes actually work when you're trying to do astronomy with them.

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calebkaiser an hour ago | parent | next [-]

The history of the term is actually really interesting. There has been debate about whether or not its the correct name basically since the advent of computer science departments in the 60s.

I don't think the author is "wrong" about the gap between theoretical discussions computation and the actual design constraints of building usable computers. I don't know if that's really a general refutation of proving new things mathematically though. The word "computer" doesn't appear once in the paper OpenAI released, nor do they make any claims specifically about "computer science": https://github.com/openai/math/blob/main/preprints/An-explic...

It's a novel bit of math. Whether or not it means anything in the context of writing software realistically is an interesting conversation, but it doesn't have much bearing on the substance of the result itself. OpenAI is pretty explicit that they view these as research results in the domain of mathematics.

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jltsiren an hour ago | parent | prev | next [-]

The field has a lot of names. Computer science is the most common, but you can also find other names such as computing, informatics, datalogy, and data processing science (or their foreign equivalents).

Within computer science, there is a clear mathematical tradition, an engineering tradition, and a social science tradition. There are also plenty of applied computer scientists who use computer science to study topics in other fields.

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heddhunter an hour ago | parent | prev [-]

yes and I'd like to sue whoever named that field for false advertising. when I went to school (Precambrian era - no internet) I thought computer science would be great because I wanted to learn how to program. I dropped it after the 2nd year when I realized it was more about calculus than programming. (and I sucked at calculus. well, the teachers who were supposed to teach me about calculus sucked, but the end result was the same.)

	▲	globular-toast an hour ago \| parent [-]
		It is a misnomer because it's not really about computers, nor is it science (although machine learning has always been much more scientific IMO). But it is about programming. It's just from first principles. It's like learning to build furniture: you first have to learn about wood. Sure, most people will just put something together from IKEA, and that might be satisfying. But they don't really know how to build furniture.