Since the advent of ChatGPT in November 2022, the number of monthly submissions to the arXiv preprint repository has risen by more than 50% and the number of articles rejected each month has risen fivefold to more than 2,400 (see ‘Rejection rates climb’).
If I'm interpreting this right then the growth in the number of rejections is wildly outpacing the growth in submissions, which means not only are we getting a tsunami of slop but that the bad papers are actively chasing away good ones.
diamondoid. None of the derivatives I can come up with sound anywhere near as dumb as the actual word.
In economic terms it's less rent seeking and more rent creation. Like, taking advantage of public sidewalk space may not be a rent in the strictest sense given that the revenue model is still people paying for the service, but the ability to provide that service is absolutely predicated on taking over and monopolizing this public resource to the maximal degree possible.
By historical allegory, harkening back to the original destruction of the Commons, we're looking at Enclosure 2: Frisco Drift.
Let's also not lose sight of the fact that those sidewalks aren't a natural formation, and that it's the city government who ultimately takes on the burden of their construction and maintenance. This kind of neo-enclosure of public resources is then another kind of invisible subsidy.
"even safer" in this case means some combination of two things:
The new organization is more ideologically aligned with the transhumanist doom cult that apparently managed to eat the brains of the people with money to burn.
The new organization, largely as a result of this, is capable of sinking an unending amount of capital into buying compute time and Nvidia chips but due to their commitments to safety is even less inclined to actually deliver anything.
Microsoft is really putting the "git" in GitHub thanks to copilot.
*morgin' timn
I found the comment about models creating very old-fashioned "18th century style" proofs very interesting. Not surprising in retrospect since older proofs are going to be reproduced more across the training data compared to newer ones, but it's still interesting to note and indicative of the reproduction that these things are doing.
I would go so far as to try and find a suitably precocious undergrad to run the test that they themselves are capable of guiding and nudging the model the way OpenAI's team did but not of determining on their own that the conjecture in question is false. OpenAI's results here needed a fair bit of cajoling and guidance, and without that I can only assume it would give the same kind of non-answer regardless of whether the question is in fact solvable.
The point about heavy artillery is actually pretty salient, though a more thorough examination would also note that "Lethal Autonomous Weapons Systems" is a category that includes goddamn land mines. Of course this would serve to ground the discussion in reality and is thus far less interesting to people who start organizations like the Future of Life Institute.
I mean I'd like to think that if someone was going to pull the paid protestor bit that they wouldn't fail quite so embarrassingly, but then I think about our current crop of people in power and how fucking cooked they are and they can absolutely see them thinking "what does a mass protest cost, like $500?"
The grass was literally right there, guys.
Fixed-position office chairs? What goddamn vibe-brained rat-pilled techbro started convincing people to forgo the single best redeeming factor of office chairs?