Win9x and Win2k (and the other NT descendants) are fundamentally different operating systems. In general, NT had a much more robust kernel, so system panics were and remain mainly hardware issues, or, particularly in the old days, dodgy drivers (which is just another form of hardware issue). I've seen plenty of panics on *nix systems and Windows systems, and I'd say probably 90-95% were all hardware failures, mainly RAM, but on a few occasions something wrong with the CPU itself or with other critical hardware like storage device hardware. There were quite a few very iffy IDE cards back in the day.

The other category of failure, various kinds of memory overruns, have all but disappeared now as memory management, both on the silicon and in kernels, have radically improved. So I'd say these are pretty much extinct, except maybe in some very edge cases, where I'd argue someone is disabling protections or breaking rules to eke out some imagined extra benefit.

Perhaps you should just grow up.

And?

That wasn't *all* I said, but it is apparently as far as you read. But let's stay there for now. You apparently disagree with this, whnich means that you think that LLMs are the only kind of AI that there is, and that language models can be trained to do things like design rocket engines.

That's what I just said.

Here's where the summary goes wrong:

Artificial Intelligence is in fact many kinds of technologies. People conflate LLMs with the whole thing because its the first kind of AI that an average person with no technical knowledge could use after a fashion.

But nobody is going to design a new rocket engine in ChatGPT. They're going to use some other kind of AI that work on problems on processes that the average person can't even conceive of -- like design optimization where there are potentially hundreds of parameters to tweak. Some of the underlying technology may have similarities -- like "neural nets" , which are just collections of mathematical matrices that encoded likelihoods underneath, not realistic models of biological neural systems. It shouldn't be surprising that a collection of matrices containing parameters describing weighted relations between features should have a wide variety of applications. That's just math; it's just sexier to call it "AI".

We know it weakly interacts electromagnetically, which means one of the ways in which it is posited planets form, initially via electrostatic attraction of dust particles, isn't likely to work. This means dark matter will be less "clumpy" and more diffuse, and less likely to create denser conglomerations that could lead to stellar and planetary formation.

What this finding does suggest, if it holds true, is that some form of supersymmetry, as an extension fo the Standard Model is true. Experiments over the last 10-15 years have heavily constrained the masses and energy levels of any supersymmetry model, so it would appear that if this is the case, it's going to require returning to a model that some physicists had started to abandon.

The illusion of intelligence evaporates if you use these systems for more than a few minutes.

Using AI effectively requires, ironically, advanced thinking skills and abilities. It's not going to make stupid people as smart as smart people, it's going to make smart people smarter and stupid people stupider. If you can't outthink the AI, there's no place for you.

Without knowing precisely how Explorer is structured, it's conceivable that there may be different dynamically-linked libraries and/or execution points for running the desktop and for the file explorer, in which case just having explorer.exe running in and of itself doesn't mean that new modules have to be loaded if explorer.exe process fires up. The solution could very well be to load the libraries involved in file browsing when the desktop opens.

Just guessing here. There was a time when there was a lot more horsepower required for GUI elements than folder browsing, but this is 2025, and explorer.exe probably uses orders of a magnitude more resources now than it did in 1995, because... well, who knows really. Probably to sell more ads and load up more data to their AI.

That, on modern hardware, they have to preload a fucking file browser so that it pops up faster is just an indication of what a steaming pile of garbage MS is. They had sweet spots with Win2k-WinXP and with Win7, but their incoherent need to be a whole bunch of contradictory things --- with AI! has led what was a rather iffy OS and UI experience to begin with to become a cluster fuck of incoherence.

I do most of my day to day work on MacOS and Gnome, and fortunately the Terminal services version I have to RDP into is Server 2016, but every time I have to work with Windows 11 I'm just stunned by just how awful it looks and how badly it behaves.

The capacity of the government of a large jurisdiction like California, or more particularly the US, could bankrupt someone like Musk, so I say, bring it on. Within a decade Musk would have abandoned all efforts, or, even better, be stone cold broke (frankly billionaires shouldn't exist at all, and we should tax the living fuck out of them down to their last $200 million).

We're too afraid of these modern day Bond villains when we should be aiming every financial, and probably every real, cannon straight at them and putting them in a sense of mortal danger every minute of their waking lives, so that they literally piss themselves in terror at the though that "we the people" might decide to wipe them out for good.

Lincoln was a Free Soiler. He may have had a moral aversion to slavery, but it was secondary to his economic concerns. He believed that slavery could continue in the South but should not be extended into the western territories, primarily because it limited economic opportunities for white laborers, who would otherwise have to compete with enslaved workers.

From an economic perspective, he was right. The Southern slave system enriched a small aristocratic elite—roughly 5% of whites—while offering poor whites very limited upward mobility.

The politics of the era were far more complicated than the simplified narrative of a uniformly radical abolitionist North confronting a uniformly pro-secession South. This oversimplification is largely an artifact of neo-Confederate historical revisionism. In reality, the North was deeply racist by modern standards, support for Southern secession was far from universal, and many secession conventions were marked by severe democratic irregularities, including voter intimidation.

The current coalescence of anti-science attitudes and neo-Confederate interpretations of the Civil War is not accidental. Both reflect a willingness to supplant scholarship with narratives that are more “correct” ideologically. This tendency is universal—everyone does it to some degree—but in these cases, it is profoundly anti-intellectual: inconvenient evidence is simply ignored or dismissed. As in the antebellum South, this lack of critical thought is being exploited to entrench an economic elite. It keeps people focused on fears over vaccinations or immigrant labor while policies serving elite interests are quietly enacted.

It's different from humans in that human opinions, expertise and intelligence are rooted in their experience. Good or bad, and inconsistent as it is, it is far, far more stable than AI. If you've ever tried to work at a long running task with generative AI, the crash in performance as the context rots is very, very noticeable, and it's intrinsic to the technology. Work with a human long enough, and you will see the faults in his reasoning, sure, but it's just as good or bad as it was at the beginning.

Correct. This is why I don't like the term "hallucinate". AIs don't experience hallucinations, because they don't experience anything. The problem they have would more correctly be called, in psychology terms "confabulation" -- they patch up holes in their knowledge by making up plausible sounding facts.

I have experimented with AI assistance for certain tasks, and find that generative AI absolutely passes the Turing test for short sessions -- if anything it's too good; too fast; too well-informed. But the longer the session goes, the more the illusion of intelligence evaporates.

This is because under the hood, what AI is doing is a bunch of linear algebra. The "model" is a set of matrices, and the "context" is a set of vectors representing your session up to the current point, augmented during each prompt response by results from Internet searches. The problem is, the "context" takes up lots of expensive high performance video RAM, and every user only gets so much of that. When you run out of space for your context, the older stuff drops out of the context. This is why credibility drops the longer a session runs. You start with a nice empty context, and you bring in some internet search results and run them through the model and it all makes sense. When you start throwing out parts of the context, the context turns into inconsistent mush.

It probably makes more sense given their scale for them to have their own power generation -- solar, wind, and battery storage, maybe gas turbines for extended periods of low renewable availability.

In fact, you could take it further. You could designate town-sized areas for multiple companies' data centers, served by an electricity source (possibly nuclear) and water reclamation and recycling centers providing zero carbon emissions and minimal environmental impact. It would be served by a compact, robust, and completely sepate electrical grid of its own, reducing costs for the data centers and isolating residential customers from the impact of their elecrical use. It would also economically concentrate data centers for businesses providing services they need,reducing costs and increasing profits all around.