271, and yes that's a lot. And yes, it does have a relation to what the bugs were and what their impact was. Mozilla, who has no incentive here to hype Mythos or any other AI software https://blog.mozilla.org/en/privacy-security/ai-security-zero-day-vulnerabilities/ said that any one bug would have been a "red-alert in 2025."

I don't know what a weak mind is. We don't live in the Star Wars universe with Sam Altman or Dario Amodei is able to just wave their hand and say "These are not the bugs you are looking for." If by "weak" you mean intelligence, I'll free admit I'm not the smartest Slashdotter, but none of this is relying onon my own evaluation. oAll of these have been examined by the actual Mozilla experts who are highly concerned. It appears that you are confusing the ability to "know a bit more" with "assuming what I want to be true which would make me have to not change my mind at all." These are not the same thing.

There's another element here worth highlighting: By continuing to insist no matter what, that nothing these systems can do is remotely impressive or substantially improving, you are essentially removing yourself from the serious discussion of how to deal with these systems, how to grapple with what they can do, how we regulate them and a host of other issues. In order for those discussions to be useful, we absolutely need the input of people who are not enamored of the systems. But that also requires that those people, like yourself, acknowledge that these systems have genuine capability. I've seen you have conversations about issues that aren't AI on Slashdot, and I can see you can make valid points and sometimes have good ideas. You are a bright person; to apply that intelligence and careful thinking to AI, you need to be open to the possibility that maybe, just maybe, you might be wrong here.

A system that finds hundreds of bugs, which were not found by humans or found by standard fuzzing, and that's "infantile" how exactly? You can if you want disagree with their claim that this will result in somehow finding all the bugs. (That's probably unlikely for a whole host of reasons.) But even you should be able to recognize the significant nature of the system being able to find this many bugs.

Thank you for completely avoiding and missing the point. Reread the comment. If you prefer imagine a world where you gamble. Or instead imagine a friend who was could make either one of these bets. There's one side of the bet where if they took it, you'd likely consider them to be an absolute idiot and the other one where you'd see them as functionally getting free money. So the idea that you cannot estimate a probability for an event that is only going to happen once is just wrong.

Spotted the frequentist. More serious comment: If someone offered you an even bet on one side for $10 that next year Jesus's Second Coming will occur, I'm pretty sure you would take the side of it not happening, even though that's a single event. If they made the same offer for first contact with intelligent aliens, you would do the same. And I can list many similar examples. So you are able to make estimates about probabilities for events which will only occur once, based on your evidence and world models.

The real purpose might be deniability. If Human Zuckerberg is an ass (which probably happens pretty regularly) or suggests something legally questionable (which probably sometimes happens) or suggests something unethical (which I'm sure sometimes happens) then it gets pinned back on him. But if the AI does any of that and there's pushback then meat-Zuckerberg can go and blame the AI.

The judge in question is Michael Liburdi, and unlike many Trump judicial appointees, he was highly qualified. From the Wikipedia article you linked to:

This isn't one of the Trump appointees that needs to be deeply beholden to Trump. It is very tempting to think that a judicial decision one doesn't like has to be due to the judge's politics or connections, but it doesn't look like that is what is going on here.

OpenAI is not the only major player right now. Google and Anthropic in the US, and to a lesser extent Meta/Facebook. OpenAI is just the largest. And there are a lot of Chinese models now also. And this isn't the only thing that has been said negatively about OpenAI or Sam Altman. There was one may recall the entire mess where they transitioned from being a non-profit to a for-profit and all the drama from that that largely revolved around Altman. When there's a bubble it is very tough to tell what finally is going to cause it to pop, and there will always look like there are a lot of reasonable things where one expects this will be the final thing that starts the inevitable cascade. There's an old rule about wanting to short sell stocks "The market can remain irrational longer than you can remain solvent." Also, it is important to recognize that tech bubbles can pop but the fundamental industry can stay. The internet bubble of the late 1990s popped, but we ended having more internet usage now than even the hype would have predicted. Similarly, the rail bubble of the laye 1860s/early 1870s popped, devastating the US economy, but the rail industry survived and largely continued to grow despite that.

I agree with the last part in parethenses. Do you have citations for the rest?

Not for lack of trying. https://www.pbs.org/newshour/health/judge-blocks-rfk-jr-from-scaling-back-childhood-vaccine-recommendations.

Bwah? The article I linked to is on Harvard's news site. It is not just about Harvard. As that article notes there's been about 500 million dollars of contracts canceled. Note that even if that were all Harvard (which it isn't) that would be a sizable chunk even in their endowment. And this has on top of that had a major chilling effect causing corporations to stop doing mRNA treatment research in general.

The US does a lot less preventative medicine than peer European countries, so lower vaccination rates harm a lot more here. And aside from changing the vaccine schedules, they've done a lot else which I mentioned. Like cancelling all the mRNA research https://hsph.harvard.edu/news/slashing-of-funding-for-mrna-vaccine-development-raises-concern/ which is going to have massive long-term damaging consequences.

Minor note: Carter did not have solar cells in the sense of electrical production on the White House. Carter had solar water heating panels but they were not "solar cells" but just direct solar heating for water. See https://projectsolar.com/blogs/solar/white-house-solar-panels. Solar cells at the time were still very expensive and not very efficient.

A stopped clock is right twice a day is the old cliche. Concerns about microplastics are legitimate and are particularly linked to inflammation https://www.sciencedirect.com/science/article/pii/S0048969723075757 and cardiovascular issues https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11009876 among other concerns. We don't know how serious this is, but it is at least a problem and should be looked at furhter. This is a good thing, and should be recognized as such. That the same government is refusing to deal with CO2 and is actively trying to hinder the development of solar and wind power still holds. And I'm sure the damage to vaccines and sabotaging any new vaccine research or mRNA treatments will kill far more people than are helped by this. But it is a problem when science is politicized, and that's what's caused them to be so bad on other issues. It would be a mistake to start associating legitimate concerns about microplastics with the right-wing. Unfortunately, these same people are obviously trying to do that by connecting this to "MAHA" which is really more about really dumb ideas about masculinity and anti-vax attitudes masquerading as science. Don't let the justified contempt for these people cause one to start thinking that microplastics aren't a real problem.

1) They don't need to turn the core on Earth. 2) Core's don't get straight from slightly enriched uranium to plutonium to highly radioactive in a few seconds. They take time for radioactivity to build up as there are more fission products.

In order to get numbers like 5 million gallons one has to be looking at the very largest data centers, counting all water use as single use, even though water used for cooling is often reusable, and counting all the water used not by the center directly but used for power plants also as discussed earlier. Typical data center consumption is much lower. For example, see https://www.brookings.edu/articles/ai-data-centers-and-water/ which has one of the high-end estimates for what a typical data center consumes. As for the idea that there's a lot of data centers being built in the Southwest, more are being built or planned to be built in California or on the East Coast. Northern Virgina is the fastest growing region for data centers. See map here https://usdatamap.com/ (This isn't a perfect map. The situation is in flux. And admittedly, this map doesn't show size of them. My impression is that at least some of the ones being built in Arizona are very large so the map here isn't showing everything.)

Yes, building some of the largest data centers, making them all near one city, would take up a lot of water. However, that would be silly; the people building these are not idiots and aren't going to go shove all their centers in a region they know they then won't have enough water for all of them. Moreover, in many jurisdictions, one has historical water rights to contend with. In many jurisdictions for major water resources, historical users get priority over new users, so farmers and others would get priority before data centers if it came down to that. (Yes, this does mean that in parts of California, golf courses get priority over some other uses.)

This is not remotely why AI systems are being used. ChatGPT is being used daily by hundreds of millions of people https://explodingtopics.com/blog/chatgpt-users. Right now, ChatGPT is the 5th most visited website in the world by some independent metrics. https://en.wikipedia.org/wiki/List_of_most-visited_websites. These systems are not being used just because some rich people want to not have to pay people or bother with civility. The regular, common people are using them. Understanding where this is going, the impacts it will have, both positive and negative, requires understanding the actual usage, not what one imagines it to be.

The water use for AI seems to be greatly exaggerated. Estimating water use complicated. Different data centers use different amounts of water. Also, systems need more water use for cooling when the weather is hot, so centers may use more water in summer. A data center will use more water when the center is at close to maximum usage, so data centers will use less water if they are handling queries when few users are using the system. Complicating things even further, some people are counting not just data cooling water but also counting the indirect water use from the needed electricity production (fossil fuel and nuclear plants use a fair bit of water for their steam turbines). There's a good article here discussing the difficulties in making water estimates https://theconversation.com/ai-has-a-hidden-water-cost-heres-how-to-calculate-yours-263252 However, all things considered. they estimate that all things considered it takes about 39 milliliters of water per a typical query. Now, for comparison, a high efficiency shower uses about 1.5 gallons of water a minute, which is about 95 ml of water a second. So making a query to an LLM AI system costs less than a second of water. If this estimate is off even by a factor of 3, this is equivalent to taking 1 second longer on a shower. The water use is just not hat high. The total water use is also not very high. If for example you use estimates for how much water is used by golf courses in the US https://www.usga.org/content/dam/usga/pdf/Water%20Resource%20Center/how-much-water-does-golf-use.pdf, the largest estimates of AI use put the water use as about a tenth of the water use by golf courses, and golf course water estimates put it at most about 1% of total US water use. So even if one is concerned, just getting rid of some of the gigantic water hungry golf courses in California and Arizona (seriously who the heck puts a golf course in Arizona) would largely offset this. Now, it is true that as data centers grow, more water will likely get used. But as we switch to more wind and solar power, the indirect water use will go down, and data center builders are working hard on reducing water use since it is such a hotbutton issue.

There are a lot of legitimate concerns about AI. Water use should not be high on the list.

These issues are all very minor. Submarines are cramped and people can remain incommunicado for months. Messages to Earth is essentially just means one will be relying on email equivalent. And vacuum packed food can keep for years. Drinking water that is reclaimed from pee isn't fun, but isn't a big deal.

Mechanical problems are a big issue. That's why for example even today submarines carry some replacement parts, and why big surface ships historically had machine shops. Some things will need to be carried. But others may need to be ready to be made on site. That's why there's now a 3D printer on the ISS, to get used to doing exactly this. The gravity issue isn't a large one: on a 90 to 120 day mission to Mars, the level of bodily deteriorating isn't that big. We don't have a lot of data for the exact "how bad is it" but I'd strongly suspect that 3 days in microgravity and then 2 years on the Moon is going to be much worse than 90 days in microgravity and then 2 years on Mars.

A 90 or 120 day trip just isn't that big an issue. People have spent far longer on the ISS and managed fine.

People don't go insane and murder each other nearly as much as they do in movies. Again, look at submarines. The degree to which there are psychological issues is drastically exaggerated.

One of the lessons from the ISS and Mir is how incredibly difficult and expensive in-orbit construction is. Now, we've learned from it but its still a big issue. If you want to send 12 people then the most pessimistic estimates give you around 250 tons of stuff for a 2 year mission. That's only slightly higher than the Starship design, which is capable of being built on Earth, and masses about 5000 tons. Serious on Earth-designs for rockets have been bigger than that. For example Sea Dragon was going to mass 18,000 tons. And you can also do things to reduce the difficulty by launching multiple rockets, say one with the humans and the stuff they need for the first few months, and then another just full of cargo.