calf
It is not to say the approach has been wrong (as the author strongly believes in his reframing) but that this clarity does matter for purposes of, ahem, mathematical understanding.
The truth of the matter is somewhere else but if people were actually a bit better rounded philosophically and politically.
In other words, the move to experience and cultural relativist statements about "math culture" is exactly the cynical ideological move that an academic cleric does. It deflects from examination of where these narratives come from and attribute it to e.g. "math history" or "math culture" or just "something specific to math itself" etc, etc.
Neoliberal intellectuals love to attribute toxicity to the Enlightenment. They can't help it.
If you accept that as a premise then obviously you agree with their truth.
If you don't accept toxicity as somehow intrinsic to the subject but rather the structural conditions, say, of post-neoliberalized academia at large, and certain faculties being only a bit more susceptible (if even, or just different, say compare humanities vs STEM reactions in the future), then the whole comment reads as a conflation.
Instead the simpler answer is that academia at large values freedom of inquiry and other Enlightenment notions which are privileged compared to outside of academia. But that is not toxicity, it's just intellectual integrity and the academic autonomy in pursuit of one's interests avocationally. The toxicity comes from the intellectual profession having to function as a modern clerisy for socioeconomic reasons under post-neoliberal capitalism.
People may conflate the two attributions and that is a deep mistake, in my opinion. In fact the conflation due to internalized oppression easily creates and explains this kind of resentful, dismissive tone response that is a distortion of the true situation.
They are great devices but they cost more. So you would not see them "recommend" in those industries you cite. Also it is reductive to accuse Apple of marketing.
What's much more plausible is that despite being a great product it also costs more. Not marketing nor the fact of being a minority.
It's also weird because your argument disingenuously ignores the wealth of HN commentary in the past about how great the M-chip MacBooks are. It's like ignoring actual reasons and doing this kind of armchair technical market analysis to prove one's point. It's a troll intellectual move to attribute success to marketing and failure to "because it is unpopular". Seeing your other replies in this thread suggests a common pattern of bias, not a one-off.
It is true that CS had to make theoretical concessions. Just as Newton did. We don't criticize Newtonian mechanics (or, I don't know, Galileo?) for not being realistic about friction or idealized balls rolling down ramps. Their anti-empiricism was a starting point for physics.
To wit, the mathematical rationale for P-NP was precisely that that under polytime reduction this is still closed in P. That is a very reasonable starting point for a theory. This is also the reason why it is tripping up a large swath of the comment thread with people asking about subexponentials which do not preserve that closure
The opposite narrative is that in science, these idealizations yield profound intuitions and insights.
Furthermore, how far are you willing to go? Do you think Turing machines are invalid, that Turing-equivalent computation is pointless and unrealistic? So we are never allowed use that theory to convey the essential idea of in principle all computers being fundamentally functionally the same and that anything claimed to be more powerful than that had better have some incredible evidence, lest it be appeal to magic. Computability and complexity have a shared foundation so how much of that foundation are you going to reexamine?
Whereas if one wishes to be like a covert finitist/intuitionist, they ought to be open about that instead of accuse asymptotic complexity (or analgously, Turing computability as above) of trying to "cheese" complexity theory as a research programme. Meanwhile, it is true that P vs NP could have large exponents or constants in P, e.g. O(c*n^100...), literally this is the first thing taught in any complexity course or textbook. Students and practitioners remember this admonition well, maybe they just don't talk about it publicly as much.
One can go even further back. Cantor was marginalized for his ideas about infinities.
The difference with people like Lipton, and Knuth, is that the critique is coming from inside the house. In that they know the theory and the importance of it, but also hope/aspire for some new way to address the open question. They are keenly aware that P / NP is a problematic question, but not for lack of trying or stupidity on the part of other scientists. What is more likely is that the 21st/22nd century math to pose the better question does not exist yet (or may never be accessible to humans, another question well on the minds of many today).
Here's something to ponder. It is often observed that despite being NP-complete, many actual human instances are in fact tractable. E.g. routine airline scheduling depending on SAT solvers. But is this evidence that NP-completeness is a wrong theory or evidence that human-sized problems are a special case that becomes tractable (anthropocentrism), or some other more complicated reason?
I'm also confused what you are saying down here. Though I can see how "sub-exponential" is easily misleading terminology.
(Upside of the story is Captain Janeway's trusted crew works together to formulate a trick up their sleeve precisely in case of predicted contingency...)
People can do math alone. They don't have to share it with others. Mochizuki was doing math (with errors). The aliens from Arrival could do math and we wouldn't necessarily be entitled to that. It doesn't make these things not valid math.
The only benefit of defining math through this vulgar social reductivism is to benefit the status quo. So you see some experts and expert-adjacent commentators using these math slogans but never critically justifying those words. Case in point, the above commenter asserts "...math is foremost about communication.", but the very next sentence does not explain why it is foremost, it just uses the sentence as a premise for the following sentence. Guess what, that is exactly how ideologues argue, by question begging fallacy. Ironic that STEM people who ought know better fail to catch this simple rational mistake.
Unfortunately despite the author's indutrious optimism, this is equivalent to one or more open problems in theoretical CS. For example we don't know BPP = P or not. So are random algorithms tractable? We do not know. If you claim to know the answer, you could win a big math prize...
(It should be noted that despite the title, the author's main argument shows that output non-determinism does matter, since their entire effort is toward mitigating the stochastic behavior of LLMs.)
What basic science does is open up new areas and new ideas. And you and I benefit from those foundations.
Dijkstra's proof methods derived from higher math sophistication than most programmers before, and today, have. Like, in one short essay he showed what invariants mean. He made formal theory accessible to mere non-pure-math mortals. You and I today know what invariants are. That's just one example.