European defense industry seems pretty strong
7,990 karma · joined July 29, 2017
I guess the US chip designers could switch to Intel as a fab if they had to, but there are not even any US-made DUV machines, so far from self-sufficient.
This bleak future is all the more believable when tech companies are laying people of, en masse, citing AI as the reason. Meta's current "We're betting on people" ads appears conceived to combat this, yet at the same time Zuckerberg has been trying to lay off as many people as he can to be replaced with AI.
The disruption of society is not some Chinese created idea - it's also coming direct from the US AI companies, with Anthropic and OpenAI apparently in competition to see who can claim/admit credit for the most out of control AI hacking into external systems, and non-stop stories of employees of these same US AI companies apparently living in fear of it, and believing it could make us extinct(!). With that sort of vibe coming from US AI leadership and rank-and-file, it's hard to imagine how any foreign country could top it!
As far as datacenter locations goes, I was interested to read the other day about DeepSeek planning for a new 160,000 GPU cluster in Ulanqab, Inner Mongolia, which sounds a bit of an obscure location until you realize that apparently there is a whole mass of existing data centers in that same city/region, chosen for it's remote location as well as easy access to power. I don't know what anti-datacenter messaging Trump imagines is coming from China, but maybe what he should be doing is being like China in this regard and planning where to put them.
Notwithstanding all his anti-China-ism, and regarding US locked in some life or death battle with China over AI, what's the betting that his current pop-wow with visiting Xi will result in some "deal" being announced where Trump softens his AI sanctions on China? He's brought Jensen Huang with him, Musk too, and apparently is looking for China not to block US sale of NVIDIA H200's he is offering, maybe increase NVIDIA sales.
If you want to abide by your own words and judge the situation on it's merit, then you need to look at the specifics, meaning the OpenAI proof itself (166 pages), and the analysis of it that is only just beginning. Assuming that the proof is wonderful and provides much insight into Navier-Stokes is just as dumb a take as assuming that it doesn't. Judge it on its merit.
The Scientific American article is sadly paywalled, but at least part of the discussion is based on the paper below, whose work the OpenAI proof appears to build upon.
https://arxiv.org/pdf/2609.20803
When discussing the proof itself, below, with Sonnet, and asking it to explain the distinction between a function being smooth and analytic, one aspect that appears interesting is that the OpenAI forcing function is apparently constructed out of "bump functions", meaning that it is not a uniform force acting upon the flow but rather a highly engineered pattern of pokes, localized in time and space, which as another commenter in this thread notes sounds similar to Maxwell's Demon - another theoretical force, that neither tells us anything about Brownian motion nor the 2nd "law" of thermodynamics.
So, we'll have to wait for mathematicians to continue to analyze the proof, and determine to what extent is does deliver on providing insights into Navier Stokes, and any potential improvement to it, that was the goal of setting it as a Millenium Prize in the first place.
https://cdn.openai.com/pdf/32d9f210-8b73-45e0-91bc-82a30aef8...
The forced version is easier since you can custom design the force function to get the result (it doesn't have to be a realistic force like stirring), so getting the blow-up might be regarded just as much a function of your bespoke force function as of the fluid dynamics itself, which is apparently what OpenAI did, pushing the definition of the force function being "smooth" to it's limit.
So, it appears OpenAI did legitimately meet the Millenium Prize solution criteria, but in the most unrealistic, and therefore least interesting, way possible.
Ants: It's a good model, sir!
If it really matters to you whether whether some business-specific classification confidence is above/below some specific threshold (vs just relative order), then you'd be better off training or fine tuning a custom model for that. Maybe that is something that TypeSafe are planning to also provide?
In the meantime, today, in the real world, there are businesses wanting to automate well-defined business flows, who don't want some stroppy AGI with a mind of it's own to instead decide to hack into something, or reward hack and make the customer happy by just wire transferring $1M of company money into their account.
There are many automation pipelines that use LLMs because there was no choice, but the multi-way classification that Jev provides is exactly what they need, and is going to be way faster and cheaper, as well as having the benefit of calibrated probabilities and structured output that can be relied on.
1) It's very cheap and fast - you provide one input and many potential classifications, and the compute to ingest the input is shared.
2) It generates structured output natively - guaranteed to be correct
3) It's output probabilities are calibrated to actually mean something
OpenAI, or anyone else, could certainly replicate it - there are already articles guessing how Jev achieves its "parallel" classifications, but it seems the AI companies need to decide are they in the business of providing intelligence/tokens, or are they in the application business trying to compete with all their customers (not that Jev uses OpenAI).
OpenAI don't seem to have much direction. First they seemed to be concentrating on consumer with ChatGPT, while also pursuing things like image and video generation, about to get into porn (sex-chat), then they suddenly woke up to Anthropic owning the much more lucrative business/API and coding markets and dropped those distractions to compete with Anthropic instead. The whole Navier-Stokes PR debacle was also due to focusing on Anthropic (who they had heard rumor had solved it), maybe also in part jealous of DeepMind's positive AI-for-science press.
So, is this (poorly conceived) PR a rational attempt to boost investment, or more of a case of paying too much attention to the competition?
They are scheduled to go in 2028.
It this had happened and been shared with mathematicians, there would be leaks.
I can see Altman sitting on 100 less famous math results waiting for the best PR opportunity to release them, but hard to see him sitting on this, risking being scooped by a competitor.
Importantly, our board will not be responsible for advising us on anything.I think someone at OpenAI (Brockman?) claimed they had "made substantial progress on it", but there is a mathematician on Twitter offering a $25,000 bet, with no takers, that they have not solved it, and that the "substantial progress" they have probably made would still leave them a lot further from a solution than they imagine.
I also see someone else on Twitter claiming to have used AI to understand what the Hodge conjecture is. :)
I really wish OpenAI would fire their PR department (incl. mathematicians), and concentrate on trying to build AGI, or RSI, or generate tons of money, or whatever they are trying to do.
Edit: Apparently not Brockman - some unknown leaker saying there was progress or an expected result soon
The reality is that so far there has been no sign of GDP growth picking up. It is basically flat at 2.5% +/- over the last few years.
In a similar vein one might have expected that the internet (think of all the e-commerce and efficiencies!) might have shifted GDP growth into a higher gear, but it did not, although in that case there was at least a significant boost in the 1996-2000 "dot com" era when the build out was happening (then to be followed by the crash and all the unused dark fiber etc).
So, maybe the hoped-for AI boom will be just as much of a dud (as it appears to be so far) as the internet boom. New day, different tools, same growth.
It's perhaps odd that we're not even seeing datacenter/etc build out register on GDP, but perhaps the scale of it is not as large as the internet build out?
Developed countries tend to have lower fertility rates (i.e. less kids per family) than undeveloped ones. Comfortably off, well educated people tend to put thought into whether to have kids or not. In poor countries people tend to have large families so they can send the kids out to work.
Having a high fertility rate isn't "high status" and a sign of a country's progress, but rather the exact opposite.
Of course this is separate from this issue of having a shrinking population, which is a sign that your citizens are not optimistic about the future, not a positive thing.
Where it seems to fail, by design, on this goal is in delivering continual learning that is more than just "memorization with LRU catastrophic forgetting".
That said, props to the author for thinking different and actually implementing something. Maybe the project can grow into something more, or inspire different ideas, if they continue to work on it.
Our brain also has some capacity limit, and maybe degraded memory performance over time, but in either case it's a graceful degradation - you may forget fine details of things that happened a long time ago etc, but you don't forget how to ride a bike just because it's been a while.
Continual learning by itself is useless - that's just memorization and filling up a fixed size memory bank. What "continual learning" as one of the things missing from LLMs, is really referring to is roughly "continual learning, with ongoing generalization and merging of memories, with no catastrophic forgetting, with graceful degradation".
And if that fails, we've got "Idiocracy" to save the human species as the dumb-asses pump out babies as fast as you like.
Different countries are handling this in different ways, with encouraging immigration being the major one. Japan is facing a major lack of workers, with many businesses having to shut down as a result, but have decided to tackle it in a different way relying on advanced robotics as an alternative to immigration.
There are very few developed countries NOT having this problem. Most of the population growth is in poorer parts of the world like Africa.