freehorse

> You as an individual are not sovereign, and when you come to the land over which the US is sovereign, you are subject to US law.

And if an american, whom ICC have found guilty on crimes, visits a country which upholds ICC rulings they should be arrested, no?

Nobody talked about kidnapping people in the US or doing anything similar. In contrast, the US is in a habit on (among others)

1. kidnapping

2. bombing

3. otherwise assassinating

4. sanctioning

5. demanding extradition (the only actual "legal" part)

foreign citizens that they do not like. We can also say that no other, non american citizen has actually agreed to these practices either, nor to US authority to be the world serif. So these arguments more like read like monopoly of global violence/authority than "sovereignty".

I never said sth about "going back" but we can have all the "skills" related to current models/agents completely replaces by new skills in a completely different paradigm in 5 years. The same way that the early "prompt engineering" skills are irrelevant now. But understanding how a computer and a program works in a fundamental level has stayed more around than any other trend.

> The more raw these proofs are, the better.

Says who? The professional mathematician writing the article disagreed. Why should people start dancing the tune that openai wants to play for their own reasons and interests? And I do not see how taking the time and effort to write a proper exposition makes it "a very elitist science" when this exact effort and time is needed to actually get other experts understand and build on a result. Unless you equate spending time and effort learning math as "elitism", which is the ai-shilling moto some time now with everything time and effort related. I cannot see how spending time and effort to understand a field and then spend time and effort to make a proper exposition so that other people can also understand it as "elitist" vs throw everything out there "in raw form".

> If they could just stop talking about OpenAI and get back to work - they are very much needed, in particular now

This kind of phrasing sounds particularly empty. We are not in WWII researching the nuclear bomb. What are they so urgently needed for to drop everything and work on understanding openai's proof on partition principle and axiom of choice?

It was always and will always be the case that you "futureproof" yourself in a field by getting the basics, not by following the latest trend that may or may not be relevant in a few months or years.

If the work schedule should change, that can be done in either case of the time adopted and the debate would not matter. But with the current schedule, daylight time savings makes much more sense. Where I live in deep winter you just don't see any light at all if you work a normal schedule. If there was daylight savings in the winter instead, you could at least get some light after work.

Where is that the case? In eu at least that is commonly called like "contains naturally occuring sugars" and "no added sugar". "Sugar free" is more specific and should contain <0.5g sugars/100g or ml.

"Sugar free" usually implies that it uses sweeteners instead of sugar.

These are nutrition claims and they are regulated [0]

https://food.ec.europa.eu/food-safety/labelling-and-nutritio...

> Dr. Shi's lab was not situated with that in mind

Never said that, labs are close to places with high viral reservoirs because it is easier to get animal samples to study, obviously, not to guard against outbreaks. Neither one "expects" such an outbreak, obviously. The fact that it is a tail event does not mean it is arbitrary, though, ie that it can just happen anywhere with equal chance.

The other arguments have been answered 1 million times and they are not worth even discussing about anymore. They only exist as justification for somebody really wanting certain conspiracy theories to be true.

Maybe Sam Altman should accept some bad things happening to him for the benefits of the world.

> when two extraordinarily improbably events occur together, there is probably a connection

If the alternative hypothesis is that the events are independent, yes. But it is somewhat more common to have labs studying viruses in regions where there are virus reservoirs. So the events "lab studying viruses" and "virus outbreak in local area" are not independent, as both are more likely in regions with viral reservoirs, and in particular, in dense urban areas thereof. A coincidence is not as extraordinary as it may seem.

Thing is, it is not possible to know at this point, as long as the virus does not seem to be bioengineered, whether it was a lab accident while studying animal samples or an outbreak starting in the market.

Emotional dysregulation is an acknowledged trait of ADHD, "rejection sensitivity dysphoria" appears in some discussions but it is not officially recognised anywhere as a symptom or disorder or anything, but it can be seen as an instance of emotional dysregulation anyway.

Well, adult treatment paths for complex ptsd are definitely much more resource intensive than adhd (medication) or autism (congrats for getting the diagnosis and good luck). So I don't think this can be what the article is about. It may not be well-covered by insurance, though, and thus not as much pursued (as compared to treating the superficial symptoms of depression, anxiety etc), especially as evidence for positive outcomes and standardised treatment is much more lacking.

> as of today seems like there isn't evidence that ADHD stimulant medication helps with non-ADHD executive disfunctions

Because there is not much research into that, not because research presents evidence against.

"More research is needed to determine whether executive dysfunction in adults with complex PTSD who did not present with ADHD symptoms as children respond to and tolerate ADHD medications."

I think it says that psychologists/psychiatrists do not really know what to do when adhd/autism symptoms overlap with childhood-rooted complex ptsd/trauma in adult patients and more research is needed. That's how I read it mostly.

I don't know as much about this issue, but definitely do not doubt that, and the fact that this has not carried on indicates more and deeper issues (the video does mention about the progress of the project being too slow under Biden and does broader criticism than towards Musk/Trump). But corruption being a thing during previous governments does not make the current overt corruption better.

I don't think that "multibillionaire gets big chunk of the money intended for building durable infrastructure due to being friends with/funding the president, resulting to no infrastructure being actually built" is shocking (anymore) but it was still worth watching.

I don't see it as a strawman. The comparison here is a program breaking compatibility with a file _used by another program_. If vim and neovim undo files are incompatible, why does neovim delete vim's file instead of using its own file name/extension and not caring about vim's undo? And why do they use the same subdirectory even? To me it is a case of a program deleting cached files of another program, which, as a user, I see as deleting user data that said program should have touched.

> there is just zero transparency provided when it happens?

Neither does openai, as there keep coming third-party reports of incidents that have happened there that openai either did not know or basically concealed.

Grothendieck "overshadowed an entire field" firstmost because mathematicians found what he was doing important. Granted, he was able to show results, but it was not just that he managed to give some proofs, his techniques and theories (and philosophy/approach in a general sense) gave rise to entire subfields of mathematics.

In this way, it is exactly an example of what has been argued over and over: that what is important in mathematics is creating a continuity and a progress in understanding, building new theories etc.

Research output is a metric that has been chosen to guide employability, promotions etc, otherwise it is a mean to the goal of understanding, it is not a real goal in itself in building mathematics itself (except regarding careerism).

What did OP misunderstand? I am not sure how and where their understanding of "persistent undo" is different from "persistent across process restarts"?

> Apple has changed its policies since the lawsuit was filed. As of iOS 18.1, developers are able to offer NFC contactless payments in their apps.

The lawsuit was files in 2022, and apple opened access to the NFC chip in 2024 (iOS 18.1). Searching I could find alternative wallet apps that offer contactless payments, but only in EEA, eg [0, 1, 2]. It is supposed to be accessible in the US, but I am not sure why there are no apps there, unless I have missed them.

IANAL but if access to NFC is open since 2024 and (assumingly) the amount banks etc pay for apple pay has not really decreased, wouldn't that mean that their main argument is not really substantive?

[0] paypal @germany https://www.macrumors.com/2025/05/13/paypal-contactless-paym...

[1] curve pay @eu(?) https://www.macrumors.com/2025/05/23/curve-pay-launches-ipho...

[2] Vipps mobilepay @norway https://vippsmobilepay.com/en-NO/news/2024/12/09/vippsmobile...

> For who though?

For the collective (humanity, mathematical/scientific community etc). Math is not done in isolation, and if somebody does so then feedback to the community does not work as well.

Mathematics, and basic science to a degree, face the issue that they create their own problems and paths through this kind of tranformation, where external feedback is secondary. It is not as if "I want to build an app/car/robot, I let AI do it". It is as if you decide to let AI decide what to build for you and how to build it, and you do nothing at all. Instead, the pursuit of understanding is the goal itself, and through the course of humanity we have learnt that this understanding can also be useful, but this is not necessarily guiding how this understanding is gained.

Most of the contexts people here have in mind are when problems are well and externally defined. Cure a disease, optimise an engine, make an app that does X, etc. This is not exactly the case in theoretical math and never was really.

The funding on mathematics is already one of the lowest accross science [0, 1], and theoretical math funding is probably much smaller than the applied math one already, so that's not even close to how much funding theoretical math gets.

So, we are talking about a field that already does not use that much funding anyway, and most high end theoretical mathematicians probably would make much more money in the industry anyway, so this seems like missing the forest for the tree imo.

[0] Table in page 1 in https://nsf-gov-resources.nsf.gov/files/71_fy2025.pdf?Versio...

[1] Figure DISC-13 in https://ncses.nsf.gov/pubs/nsb20257/academic-r-d

1/3 of articles warrantying such a comment means it is still important information. If it was 100% of the articles I would agree that it gives no information, but with 1/3 one cannot claim it does not contribute information.

AI can also introduce its own "bad friction", or it (ppl?) can bypass good friction without necessarily directly be removed by ai, eg bikeshedding, slowly pivoting towards directions and problems that ai is better in tackling, because that can produce these accelerated results vs fields and problems that ai may not be able tackle as well and thus the output there is poor, demotivating people from following these fields and missing important insights from them. Of course this could have the opposite effect, depending on which direction the whole hype can go, or not happen at all if ai will be able to tackle everything equally well.

That's a good point. And yeah I got the term from Tao, as I had not described it this way before but I think it elucidates well the issue.

The problem imo is that, from a purely psychological/phenomenological perspective, there is not always a perceivable difference between "eutripsis" and "dystripsis" (just made it up but "dys" is the opposite of "eu") as experienced. There is some reward coming from learning through friction (depending on personal interests, environment etc), but mostly it is effort and humans usually try to reduce or avoid effort.

Moreover, even if one tries to be fully mindful and choose where to employ friction and where not, there could be systemic factors to optimise away any kind of friction. Imo we already see that in software engineering, judging from a lot of different anecdotes, where increasing the pace of generating code sacrifising human understanding is already taking place. It is not like these forces are not already in place widely in academia too even before AI (eg optimising for paper output quantity), so AI reinforcing this direction sounds a reasonably probable scenario, unless some other action is taken.

Imo judgemental as in starting from "my life experience" and getting to that's "how to live" is a reason to dismiss it as an argument, as others may have different life experiences and yours is not universal.

I meant about the title as used by the author, not the one who linked it here. But in any case I said it was a joke about not giving many sex related details in the article.

Technological progress is not bottlenecked by most of the millennium prize problems or erdos problems per se, or most of the rest open problems in theoretical math, ie that merely knowing the solution of them will help applications in some manner. I doubt the solution of such problems has any direct effect on technology progress at all, at least in any deterministic, foreseeable manner.

In fact, the relationship between theoretical mathematics and "real physical problems" is bidirectional, as in "real physical problems" informs to some degree some problems that may be interesting to research on in theoretical math, and at the same time pure mathematical research that is developed completely independent may find applications at some point. And even theoretical mathematicians working close to applications are mostly dealing with problems not directly addressing applications. Eg maybe they study properties of a certain function that arises often in application without any view to solving a specific "real physical problem" with it, and somebody after may find that useful for some application after some point, but that could be one out of 50 papers (random number) and it is hard to predict that. There is of course some work more related to specific real problems, but that's most often not what theoretical math is about, and not what these new developments with erdos problems, navier stokes etc are about.

So what could (in a chaotic sense) have effect in application is mathematical theories developed along the way of solving these pure math problems, which brings us back to the question of what happens if we remove this friction and if AI can do more than construct examples and proofs, ie actually build theories (autonomously or humans+AI). If anything, it is through building theories that mathematical progress germinates applied sciences, as this is the process that develops mathematical tools that can be taken up later, including whole mathematical fields. Building mathematical theories is a heavily social process, and it is the community that basically decides which directions are important to follow.

It may have been flagged as the title being misleading, as it did not really present as many details around the sex part as the title suggested.

Jokes aside it would have probably flown a bit better by removing the sex from the title, as the issue and problem brought up is about it being a cult, and not about the sex part specifically.