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Devin's Law: every defense of AI which rests on "it will get better, trust me" is in many ways indistinguishable from 2010s crypto hype or "level 5 self driving is right around the corner"

by usrnm1 hours ago|

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1) Predicting the future is hard, but so far everyone who was saying that it would get better turned out to be right. It is getting better 2) Waymo exists

by devin1 hours ago|

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3) That doesn't mean flying cars will within your lifetime

I don't think anyone is saying it can't or won't get better, but the question is how much better, on what timescale, and are there fundamental parts of the problem which will remain extraordinarily difficult to improve?

The comment I was responding to suggested a guarantee of an "order of magnitude" jump right around the corner. There is no guarantee of this, and if you view doomers as fools for having doubts, then we ought to look upon the folks who are sure of this sort of progress in the same way.

by kulahan54 minutes ago|

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Your original comment was about self-driving cars, not flying ones. If you wanted unattainable goalposts you should’ve started with that, not ended with it.

by devin52 minutes ago|

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Waymo does not claim level 5 self-driving, and you don't have a level 4 in your driveway, so there was no moving of goalposts.

by kulahan14 minutes ago|

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Then say that, instead of bringing up flying cars, which is moving them, explicitly.

by Kotlopou1 hours ago|

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In that case, one would expect to see some progress in this direction, but AFAICT that hasn't shown up yet? If anything, it's getting worse, though that could just be the increasing scale and decreasing cleanup efforts.

Already the unit distance proof was substantially human-edited (per Thomas Bloom). Then with the ten problems from Astra you started getting the citation issues. Then Navier-Stokes was a rushed 160 pages with barely any citations, and some of the related papers were called (by their "authors") the ugliest mess they've ever seen.

And now here we are. At least it seems that mathematical ability and communication with a mathematical audience are independent skills, and progress in the first does not imply the second.

This doesn't surprise me much, given two analogies: 1) many smart people are nonetheless horrible lecturers. (You can't quite get the opposite extreme, since to explain math well you have to be able to do it.) 2) AI writing in general hasn't improved. The models have annoying verbal tics ("honestly") and have no sense of which part of what they say is obvious and which is relevant.

by auggierose1 hours ago|

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You can get the opposite extreme quite often as well, I'd think. How many really good lecturers have never proven a new important result?

by Kotlopou1 hours ago|

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I'm thinking of somebody like Grant Sanderson (3blue1brown), doing pure exposition extremely well. For that you at least need to be able to work through examples, or to present why an intuitive approach might fail, and these things can be little theorems themselves. It doesn't have to be publishable in the current culture of novel results, but you do need a lot of competence with the tools.