onetimeusename

You're right, it's not but that wasn't what I was asking. If they are going to claim that ICE is targeting left wing movements and then use the Minnesota 15 as an example, I would want to hear about this case. If the Minnesota 15 performed only constitutionally protected speech then this investigation might be concerning but the article didn't really describe that. Could ICE have collected evidence illegally? Yes, that can be decided in a court. I am just a layman but if it turns out that the Minnesota 15 were doing things like blocking law enforcement vehicles or throwing ice blocks, that doesn't seem like constitutionally protected speech anymore. Apparently some of them were charged with such offenses. So that might weigh on whether I thought ICE was "cracking down on left-wing social movements".

Generally the evidence seems vastly more narrow.

The ~10 million were not substantially deported, they entered illegally and then were given Notices to Appear which is completely a lawyerly way to cover for it all.

The bipartisan bill would've still allowed in thousands of people per day. Some people don't want that. It wasn't even proposed until 2024. By then people might not have trusted the admin.

I read the article and the facts don't match up with the title. The thesis is actually

    The Minnesota 15 case is the clearest example yet of DHS pursuing the Trump administration’s efforts to crack down on what have long been upheld as First Amendment–protected activities

But did the Minnesota 15 commit actual crimes? There's lots of hyperbole "15 terabytes of data" but in the end it centers on investigations into the Minnesota 15 and doesn't answer this question. The Minnesota 15 are not accused of ordinary protest. The article gave no evidence that these people hadn't committed any crimes it just went on and on about investigative capabilities of HSI.

Obstructing law enforcement is a crime even if you don't like law enforcement. I think it's a stretch to go from "Minnesota 15 investigated" to "ICE is a private police force used to suppress dissent". Also, there's no mention of the ~10 million people who entered illegally under Biden. Is it democratic to have open borders? I get the sense this writer believes deporting people is anti-democratic.

>math is really a jobs program

Yes. That's completely reasonable. It's sort of like how 100m sprinting is also a jobs program. People like watching very fast individuals compete in it and not, say, people on motorcycles.

It's actually reasonable too. I don't think math is just about results and theorems. It's also a question of the limits of what people know, how they came to know it, and how others can also understand it. It's like the difference between climbing Everest and taking a helicopter up. Both reached the top but surely the person who climbed it had different experiences that might be useful? In my opinion, most published math results are not going to have much application outside of the math community.

Well, my reading of this is Ofcom did not lose overall and 4chan technically lost the lawsuit despite Ofcom having no way to enforce fines. I don't think Ofcom's purpose was ever to collect the fines either. Now keep in mind, 4chan is the first website that had ever been issued a fine by Ofcom under the UK's Online Safety Act. I think that is interesting because it's a noteworthy site which suggests the selection of it was more targeted. Note that is my speculation.

4chan sued Ofcom over the fines. Ofcom has been perhaps waiting for the outcome of this suit and is announcing they can't collect fines but I don't think that was the purpose. They have the power to instruct ISPs to block domains and to me it seems more likely that is what they will do and that was perhaps what they wanted from the beginning.

People have commented on this and said that the gist of the issue is mathematicians egos are bruised. That's true but I think it's defensible. Like we don't typically enjoy watching humans race against motorcycles in a 100m dash. But there's something interesting about watching humans do this in the Olympics when they race each other. Likewise, in math, people are solving problems considered hard by other humans and we acknowledged the art form.

But I think there's a practical side of it too. Finding what the limits of humans are is worthwhile too. Maybe the best analogy is like a group of people trying to find their way through a cave in the dark. One of them found a new passage and has a technique for doing it. So maybe we expanded what we thought humans were capable of. Could there be passages that humans can't get through? That might be useful to know. If we find proofs that humans just can't comprehend or have knowledge requirements that humans can't reasonably obtain that might be useful for us to know. A lot of math is not really applied to anything useful, it is just knowledge that is accumulated that other people thought was worthwhile perhaps because it was considered difficult for humans. So basically the journey to the proof is the value add and not the proof itself perhaps and AI might be erasing the journey. I have previously described it as a helicopter ride to the top of Everest but the point of climbing Everest is the difficult part. That's why people do it, the challenge.

I've seen it done in not even a small-town newspaper. A company I worked for put it into a print newspaper I cannot even find anywhere and I suspect the lawyers who we used to help in the process owned it themselves (but I can't prove this). I am not sure if there is a set definition of what a small-town newspaper is or "widely distributed". Like what if lawyers print it once a month/year and just distribute it around public parks or something? Is that widely distributed?

This isn't even a good basis. The question is what the purpose of visa to residence work programs achieves. No one ever questions the underlying assumptions. Like for example, could filling skilled roles actually cause a self fulfilling prophecy? If Americans assume immigrants will fill a role, they don't acquire the skill which actually creates a dependence on immigration to fill it.

I would argue this is not accurate. The Elite Overproduction theory suggests you can have too many highly educated people and H-1B requires a bachelor's at least but incentivizes higher education. However, as it stands we already have an oversupply of highly educated people. The theory predicts that having an oversupply of highly educated people destabilizes society.

I would also argue that "global talent" in practice is just creating ethnic labor castes which I would also argue is a very destabilizing structure. So I would push back on your framing that more "global talent" is always good and actually I don't believe the premise that top talent must be imported.

I think you're making an assumption about what the military wants to do with AI. Based on things I have put together, they want an AI without guardrails for various reasons I won't go into. In fact, it's a security risk to have guardrails, given what I think at least one intended use is. I wouldn't jump to conclusions about corruption as the first explanation because this is vastly more complex than that.

I have this theory that the economics of AI development would make it so it's much more viable to make in-house, custom, apps rather than paying subscriptions for apps. I have even seen this play out on a personal level. A friend of mine who has no dev experience vibe-coded something custom that evite does. So it's possible measuring the number of apps miscounts ones that are not public or shared. I'm not negating anything you said, just adding something about metrics on apps.

ok I realize this is a tangent but you're saying my post is very misleading and then also saying that a human mathematician's career is about 100,000 hours of compute and that Navier-Stokes could've had a solution by now if not for perverse incentives. You may be right but I don't think this is a great argument because in a year I would bet that those numbers change since computing power tends to increase or get cheaper over time. So I am taking the stance AI can outdo people if not now, perhaps soon.

Why? How do you define interesting research directions? That used to be defined by testing the limits of human understanding i.e. some people can't figure something out. AI might have very different ideas about what is interesting and I am not sure what humans would get out of putting years into understanding AI proofs for what? What are we doing at that point? Like if you spend years understanding some AI proof of theorem 123456, why is that meaningful? I am actually asking why you think defining interesting research directions will stay relevant. In my opinion, people spend years acquiring knowledge so they can work on problems which is separate.

There's two points about this I am assuming 1) Mathematics actually has a significant subjectivity to it and is community oriented and not just climbing a never ending list of theorems that exists in the universe 2) A lot of mathematical research work is inside of a subfield and isn't directly motivated by applications. Sometimes it is but e.g. people don't work on obscure theorems about elliptic curves because of a dire need for that but more because the community found it interesting.

But the work the Mochizuki case generated can also be done by AI. AI could generate a landmark proof and then people could use it to solve or simplify intermediate problems and you could use a different AI prompt to try to disprove it if you were really skeptical. From my memory I think they said it took 88 hours to solve a Millenium Problem versus the decades of time humans have put into it.

I don't like nuance here. I think progress is really measured by what humans are able to do and understand, not machines. It is significant if we find problems we struggle to solve. That tells us something. What does it take for humans to solve these problems is related.

The best analogy I can give is if you wanted to climb Mt. Everest you might ask someone for guidance. Would it be better to ask someone who has climbed Mt. Everest or someone who took a helicopter ride up near the top and then went to the peak? This is like the AI versus human gap to me. The helicopter is like using AI to generate a proof. The person who actually climbed Mt. Everest has firsthand knowledge of the experience. Same thing for a difficult proof. The struggle people have is actually valuable here. Likewise, we know people are actually capable of climbing Mt. Everest but if they had only ever rode a helicopter to the top, the knowledge of climbing it would not exist, and surely that is meaningful knowledge given the risks.

So if we rely on AI for proofs I think we lose a sense of what is difficult and why. We lose a sense of what human achievement is. Surely climbing Mt. Everest means more than taking a helicopter up? For students, why bother grinding through all the material of climbing Mt. Everest and then attempting it if the helicopter ride is how things are done now? This would have the affect of destroying knowledge.

(please do not nitpick the analogy because it's the best but perhaps a clumsy way to describe my thoughts)

> Does this mean that we wouldn't have mathematicians or physicists or computer scientists or biologists anymore?

In the case of mathematicians, I think not as researchers. What would a research mathematician do? I don't think there would be any reason to try to gain insight from proofs that AI made for the sake of understanding. I don't see what that would achieve besides just retaining extremely niche knowledge (which AI or the oracle already does). The whole point of having that knowledge was to build toward novel work which the AI/oracle does. Also, the time spent and difficulty understanding them could be very high but with no payoff besides just understanding them because the AI/oracle would be used to solve all the problems anyway.