Doc Octagon

[Doc Octagon @DocOctagonical]

@AcerFur @Creative_Math_ This is a good example since every piece of math in the Adam paper is wrong; see Reddi, Kale, and Kumar (2018) and David Martínez Rubio's 2017 master's thesis at Oxford. My takeaway is that the math in most of these ML papers is just completely irrelevant

[Doc Octagon @DocOctagonical]

@TaliaRinger Not a huge issue but it's very weird to me that they keep talking about "textbooks" but they only mean lecture notes

[Doc Octagon @DocOctagonical]

@BjarturTomas "Scott Aaronson finds [X] to have literary significance" is a useful signal of anything for you?

[Doc Octagon @DocOctagonical]

@lyndalovon @AndyMasley @dearmadisonblue Completely agreed. I've seen it for years espoused as an article of faith by certain kinds of 'rationalists.' I might have even believed some form of it when I was younger, but then I got degrees in math and physics!

[Doc Octagon @DocOctagonical]

@arnal_charles @AIatMeta I'm a bit confused - when you refer to "textbooks" you exclusively mean lecture notes on https://t.co/dlMPwk4oRS?

[Doc Octagon @DocOctagonical]

@AndyMasley @dearmadisonblue "Literally everything in the universe can be described by mathematical formulas."

What are you basing this on?

[Doc Octagon @DocOctagonical]

@littmath Of course, there are many broader dangers as well, e.g. adoption of certain tools also promotes certain companies & thereby certain individuals, e.g. environmental dangers (which I don't understand well)... the balance of benefit and cost is not at all clear to me

[Doc Octagon @DocOctagonical]

@scottnarmstrong @datbrownnigga Interesting, I thought you would have meant the kind of stuff Gomez-Serrano has been talking about.

[Doc Octagon @DocOctagonical]

@scottnarmstrong @datbrownnigga But surely the AI use you have in mind with this (PINNs, numerical solvers) has pretty much no overlap with 'ask GPT to solve it for you / help you solve it'?

[Doc Octagon @DocOctagonical]

@scottnarmstrong e.g. the unit distance problem was a central problem in its field AND the proof is two pages long AND (at least as per @tonylfeng) doesn't contain any conceptual breakthrough. Reductive to only single out part of it

[Doc Octagon @DocOctagonical]

@scottnarmstrong Sure, but even if you prompt it with an idea, it's not presently able to generate 100 pages to flesh it out and apply it... my point is just that there are obvious limits to present capabilities, beyond the domain-specific

[Doc Octagon @DocOctagonical]

@wtgowers If they solved 9 of 353 attempts and each cost that much, don't you think it's more accurate to say it's several thousand dollars per problem? On the slot machines at the casino you wouldn't only consider your profit on the winning rounds ...

[Doc Octagon @DocOctagonical]

@scottnarmstrong It also seems much closer to the interests of the mathematicians who have been employed at OpenAI, designing the systems. Not obvious to me whether this is a coincidence ...

[Doc Octagon @DocOctagonical]

@ChrSzegedy What are you basing that on?

[Doc Octagon @DocOctagonical]

@WKCosmo But "things like this" have themselves been evolving. The early results claimed as breakthroughs *were* actually low-hanging fruit or problems nobody cared about!

[Doc Octagon @DocOctagonical]

@peligrietzer It's a common take, not just among algebraic topologists... I'm one of several who don't care about a single Erdos problem (though unlike some others, I just view it as personal taste)

[Doc Octagon @DocOctagonical]

@DmitryRybin1 @kareem_carr What are you basing the inference cost on?

[Doc Octagon @DocOctagonical]

@littmath @EAgony580 @yacineMTB Curious what you're basing this on, is anything really publicly known about costs? If they're so low, I don't understand why all the companies are so cagey about it, e.g. deleting labels from x-axes and so on ...