well it seems advantageous to be able to say "your honour, we're being unfairly singled out here; at the time of the incident this lawsuit concerns, none of our competitors had resolved this problem either" and have receipts.
(and also know whether the safeguards they're trying to implement/improve towards have been achieved or are theoretical)
also just as importantly (or moreso for cases of individual rooms used for social/hobbyist clubs like this) would be 'empty building taxes' to prevent the eventuality of landlords preferring to rent out fewer properties over reducing the cost of vacant ones because
* housing is necessary for survival so people cannot afford to baulk at the prices of artificial scarcity, making the optimal price effectively arbitrarily high without regulation
* landlords are generally not infinitesimal entities in a vacuum, and generally stand to lose existing customers who are still on the expensive contracts if they cheapen their unoccupied offerings
although such a solution would just move the problem one layer further up (stop building properties to have them be vacant) and the solution is land tax
I think it becomes somewhat more defensible when considering that the alternative was operatiny Google's policy (before the advent of competition) of "these models would bring unknown dangers in the hands of the public, we shouldn't release them until we better understand the implications" (or perhaps more selfishly "these effectively nullify all our detectors of generated text, if released they would instantly lose us the war on SEO").
(recall that OpenAI thought GPT-2 was too powerful to release for approximately tantamount reasons)
it is still O(n) weight to transport, so O(n^2) amortised; if you liken having a stronger hand that can carry more spaghetti to parallelisation, it's beaten by O(log^2 n) sorting algorithms on parallelised classical computers.
this is explained by the symbolic method (https://en.wikipedia.org/wiki/Symbolic_method); in the language of exppnential generating functions, we say that bell(n) = A000110(n) = [x^n/n!] exp(exp(x)-1), since exp() means "sets of ()," exp()-1 means "nonempty sets of ()" and x means "singletons" (it can be read as "bell(n) is the # of partitions of [n] into sets of nonempty sets").
see the asymptotic formulae by Vaclav Kotesovec and Natalia L. Skirrow (me!) on https://oeis.org/A000110; the former (together with Stirling's approximation) says bell(n)/n! ~ exp(n/W(n) - nlog(W(n)) - 1) / √(τ(1+W(n))), and the latter says that the average number of subsets in a partition on [n] counted by the Bell number is ~ n/log(n), while for a permutation it's ~ log(n).
(using W(n) ~ log(n), although it's more precisely log(n) - log(log(n)) + o(1); its appearance here comes from solving for the radius from the origin at which |exp(exp(z)-1) / z^(n+1)| has a saddle point in the complex plane, which lets you pretend your contour integral from Cauchy's formula is a Gaussian and approximate it in terms of the generating function's logarithmic second derivative)
another cool adjacent result that comes out of saddlepointery on e.g.f.s is that (# of sets of lists on [n], A000262(n))/(# of sets of cycles on [n], n!) ~ exp(2√n - 1/2)/(2√π * n^(3/4)); this is also the expected number of preimages under the surjection A000262(n) -> n! from closing lists into cycles, or equivalently the expected product of cycle lengths in a random permutation ∈ Sₙ, and is my favourite example of a function whose growth is between polynomial and exponential
this is not necessarily the case; the coursework could have been produced by a different person from the teacher (although generally at my alma mater the 'module organiser' fulfils both roles).
> done already in the 1990s
by human-written programs that iterated through the finite casework that human thought had reduced the theorems to (four-colour theorem, FLT, etc.), which recent developments (eg. LLMs autonomously resolving Erdős problems) seem meaningfully distinct from.
> human effort to make the results cleanly understandable
well, perhaps loops of "derive proof through reasoning in English, formalise in Lean, use AST size of formal proof as a metric to optimise (via an LLM-guided search), translate back into English" could improve this? a lot of resources are being spent to make frontier LLMs more resistant to hallucinations via Lean, perhaps cogency will increase as a byproduct.
from the "DeepSeek is a ploy to undermine usamerican models' duopoly" theory's perspective, "now everyone has this" helps them achieve this goal more efficiently.
especially if it's something that the major companies had already stumbled upon (something equivalent to) and regarded as a trade secret.
yes, that is pretty much what he disclosed in the article
> He turned to Google’s Gemini AI for advice and decided to create a “hot girl” crafted specifically for the “MAGA/conservative niche,” after the software told him that “the conservative audience (especially older men in the US) often has higher disposable income and is more loyal,” according to Wired.
age doesn't inherently make math less useful, and the parts it does affect it does non-uniformly.
i have undergone an undergrad differential equations module that taught exclusively ad-hoc methods for certain families of equation that no working mathematician needs to know since they were all subsumed into and superseded by computer algebra systems, but the subject i would enjoy replacing it with (generating functions) is similarly old in origin (perhaps even earlier, since Euler used most of the techniques that an undergrad class would cover before diffeqs were considered an object of study) but has happened to become more useful with the advent of CASes instead of less.
well inflation is equivalent to a flat wealth tax that doesn't consider insoluble assets, and is entirely in the hands of the government that imposes the UBI.
"cause increased prices for consumer/essential goods" is what you meant (since buying power is moved to people who are reliant on buying them), but this is a one-time transition to a new equilibrium (so is mitigable by increasing the UBI to account for it), not a constant ever-looming devaluator.
the point is that each question is something that a specialist in a field would be able to do, but deems challenging enough that the ability to solve it would imply significant general usefulness in that domain
i've seen a a where three barbershops were a stone's throw away from each other, with a few houses between them on a street in an (only moderately dense) residential area with no carparks anywhere nearby, and wondered how that could possibly have arisen (since they'd detract each other's customers, and laundering operations wouldn't make it so blatantly obvious).
and the same occurs with phone(-repair)-and-vape shops in shopping areas (which I guess are somewhat more understandable, since they only require one employee present each and do get footfall, and the cost to rent a shop has imploded since the coronavirus hit the final nail in the town centre's coffin)
(and also know whether the safeguards they're trying to implement/improve towards have been achieved or are theoretical)