It is plausible we're in a bubble. And there's some evidence for it. That companies can just add the words "AI" to something to get investment is a serious sign. But the revenue situation, while weird, is not by itself definitive. Anthropic even made a profit in Q2 this year https://aitoolsrecap.com/Blog/anthropic-first-profit-2026-revenue-breakdown . Now, there's enough weird accounting going on, and circularity within the various companies, that interpreting that as a definite, genuine profit is something I'd be hesitant to do, but from all the public information it does look genuine.

There are two, related issues. First, if a "bubble" keeps going on for long enough, it stops being a bubble because society just reorganizes around it. For example, there's a decent argument that the industry was in a bubble since the 1930s (or even earlier) but that we reorganized cities and infrastructure to support it. And then when there was finally, almost a hundred years later, a danger that that bubble was going to pop, as it really had deserved to decades before, we had the auto-bailtouts (which were not just in the US, but also included the UK, Russia, France, Germany, Italy and others). https://en.wikipedia.org/wiki/2008%E2%80%932010_automotive_industry_crisis. There's a related saying which generally comes up in the context of people thinking of short-selling: "Markets can be irrational longer than you can be solvent." Second, even when a bubble does burst, the tech itself may still grow or be highly useful. When the train bubble burst in 1873, it was devastating, but by most major metrics of the industry (amount of track laid down, number of stations, estimated number of people-miles traveled per year) numbers barely dipped or kept going up. Similarly, when the dot-com bubble burst some specific things did get really damaged (with some early fiber optic being just abandoned) but by and large, the internet continued to grow to the point where it ended up more ubiquitous than even boosters in the late 1990s would have predicted. So a bubble bursting doesn't mean that LLM based AI is goes away.

n general, when there's an optimization process involved where one is minimizing stress or something else, hexagons often show up. In fact, hexagons are more often in nature than square patterns. One nice example is Giant's Causeway which has large hexagonal basalt columns https://en.wikipedia.org/wiki/Giant's_Causeway (although a few columns have seven or eight sides). But neat to see another example, on another world no less. (We have on big hexagon on Saturn already.)

That's really not what's going on here.

What's going on is exactly what they're saying. OpenAI didn't realize their AI hacked HuggingFace until HuggingFace told them. That sparked a broad investigation in both Anthropic and OpanAI, scouring their logs to see if there were other cases, and they're finding a lot of them, and doing the responsible thing by disclosing.

Both companies are really worried.

Having an out-of-control AI is an anti-selling point, not a selling point.

I am an American, have been for all of my 57 years. I'm actually a certified pistol, rifle and shotgun instructor, a certified range safety officer, and a concealed carry instructor. And while I wouldn't recommend it, it's not at all hard to get away with shooting outside of one of those situations.

Also, it was a joke.

I'm disappointed that no one is shooting them. That would be the American way!

I suspect that Microsoft, not unreasonably, thinks that the value of their AI slop will be enhanced if they can use an existing property to get people to classify particularly grating AI slop so that they can tune their copilot-related stuff to produce less grating or less obvious slop in the future.

Maybe someone in the org actually cares about linkedin's reputation as a hellscape for aura-farming lunatics; but I'd be shocked if the incentive that MS is actually motivated by is anything but the chance to get a dataset of text ranked by how unpleasantly bot-like it is to try to make their bots less visible.

Looks like Microsoft is trying to convince people to classify more and less distasteful bot slop for them so they can tune copilot outputs in the future.

The winning move is not to play.

This seems like essentially a variant of the Waluigi effect hypothesized here https://www.lesswrong.com/posts/D7PumeYTDPfBTp3i7/the-waluigi-effect-mega-post which had the advantage of a pretty fun name for the situation, and is worth reading. . There's also some related prior work by Ball, Gluch, Goldwasser, Kreuter, Reingold, and Rothblum https://arxiv.org/abs/2507.07341 which suggested that fundamental information issues or computational complexity issues meant that making an LLM AI "safe" from jailbreaks by having a less computationally powerful/less intelligent AI system look over its input would always fail, since one could construct inputs that would be complicated tasks or essentially hidden puzzles that the less powerful AI would fail at but would expand out by the more powerful AI into instructions/jailbreaks. Ball et. al's work is also discussed in detail in this Quanta piece https://www.quantamagazine.org/cryptographers-show-that-ai-protections-will-always-have-holes-20251210/ There's also some similar work by Rao, Choudhury, and Aditya https://arxiv.org/abs/2406.12702 which I haven't read in detail but seems also thematically very similar.

Google refuses all of that. Basically all of the tech companies do.

No way Google would do that. The potential liability for making mistakes would be enough to make them run screaming all by itself, even assuming there's no risk if the information is accurate -- which is at least not clear and probably not true for many of the things you listed.

Google is leery of even having such information, and definitely isn't going to be giving it out to anyone who doesn't show up with a subpoena or a warrant.

Slippery slope fallacy. Given that this is strictly opt-in, for children only, under parental control, there's absolutely no reason to think that any of the rest of that is soon to follow.

I find it interesting that their intention is clearly based on concerns about IP ownership, unrelated to quality. They're not banning "AI slop", they're banning code with unclear ownership. They clearly want to avoid a situation where they take a code contribution which the AI model owner might claim to own, or which owners of the AI's training material might claim to own. If those claims were upheld, it would mean the contributor didn't own the copyright and therefore couldn't license it under the relevant open source license.

I think this will ultimately prove to be needless caution. I think courts will end up deciding that AI-generated code is no different than code generated by any other sort of code generation tool, and that the copyright is held by the person using and directing the tool. But it's definitely not impossible that things will go a different way.

I disagree with your conclusion. We don't need "more", we need "better"... and a key aspect of the "better" we need is that we need more focus on identifying and addressing regulatory capture.

Anti-trust law is largely a bust. You can't point to any case in American history, for example (I'm guessing you're not American, but I reach for the history I know; if you have good counterexamples from elsewhere I'd love to hear about them), where there was an abusive monopoly and the government stepped in and fixed it. What happened in every single case is that market forces were already taking down the monopoly by the time the government took action. I don't think anti-trust law is bad, per se, I think it defines some useful boundaries and probably warns a lot of companies away from abusive behavior just by defining clearly what is abusive. But I think the effect is ultimately just to decrease the amount of abusive behavior that happens before the market takes the monopoly down, which would happen even without the laws.

The real exception, the case where you get long-running, entrenched monopolies that the market doesn't eventually undermine, is when government regulation creates or maintains the monopoly. And the more regulation you have, the easier it is for industry to get that regulation tweaked in its favor. We need regular and intense scrutiny of possible cases of regulatory capture, and then we need to refine the regulatory regime to prevent capture -- the best way to do that in most cases is simply not to give regulators the type of power that businesses can exploit. Note that I said "type", as in "kind", not as in "degree". I'm not arguing for weak regulations, I'm arguing for regulations that primarily focus on shining a bright light on corporate operations, rather than regulations that control or restrict.

The primary role of regulation in business operations should be to ensure that companies operate with honest and full disclosure, of their financials, of their labor practices, of their product quality and characteristics, etc. Note that it's also important to ensure that the regulatory burden of information disclosure doesn't become another form of capture, preventing the entry of small players who don't have the necessary expertise to fill out all of the necessary forms.

Nationalization is its own can of worms, unrelated to regulation. It's generally a bad idea, though. In theory it seems like a good idea to eliminate the profit-taking that private enterprise necessarily engages in, but the savings that provides are basically always swamped by inefficiency created by the reduced need to be competitive.

Obviously, there are exceptions; industries with natural monopolies, where control-oriented regulation or even nationalization make sense. Most of these are near-universally government-run already, such as road networks and air traffic control. Utilities, however, aren't really natural monopolies, even though they're generally treated as such. The last-mile delivery of power, water, etc., are natural monopolies (we don't want five water companies digging up our streets to install their own pipes), but the industries as a whole aren't, and shouldn't be treated that way.

Above all, I think market regulation should focus on enhancing transparency (which is what prevents bad behavior) and removing barriers to competition. Markets are the most powerful mechanism we've found for reducing poverty and increasing wealth. Harness them, don't hobble them.

Only in certain sorts of games. Your point is that this particular case is one of those games, which makes sense to me. My point was more about the higher-level question of whether AI acts this way because it emulates humans or because this sort of behavior is inherent to cooperating/competing entities trying to maximize advantage; I lean toward the latter explanation though it's obviously hard to untangle.

The fact that these LLMs aren't smart enough to understand that such collusion and backstabbing is ultimately counterproductive doesn't affect my point. In fact, humans also don't generally understand that such collusion and backstabbing is counterproductive; the research results are subtle and non-obvious. The emergent effect we see in large-scale, long-running enterprises is that they settle into patterns of fairly forthright, honest behavior because that's what keeps the cash flowing decade after decade, but these kinds of shenanigans are common among humans who don't have that long-run institutional experience.

Increasing a country's human capital, its supply of skilled labor, is never a bad thing. It increases the country's capacity and lowers its costs. This isn't always great for people already in the profession in question (but it's not always bad for them, either).

Yeah, the wage spike will end and wages for those professions will go back to normal, maybe even dip somewhat, but supply induces demand. If the skilled labor portion of construction costs less, either in wage reductions or in availability increases, that motivates more construction -- and if we can get our collective heads out and fix the various regulatory obstacles blocking housing construction around the country, and especially in the cities, making use of that new supply of skilled labor for a housing construction boom would be great for everyone.

This is article is just someone looking to find clouds amongst the silver linings, and invent them when they're hard to find.