You're half right, they're not Markov chains. But OP isn't describing a Markov chain, he's talking about the transformers used in LLM, which use the output tokens from prior steps as an input to probabilistically generate the next token (based on what word is most likely next, given the entire context and training weights).

You generally wouldn't. Why would you need to upgrade it? The main reason for most systems is security vulnerabilities. That's not an issue if it's properly air gapped. You're certainly not going to trust something like Windows update or aptitude to update the system anyways (those are a *huge* security risk for state-level entities). If it really absolutely needs upgrades, you'd just pull the hard drive, or replace the entire system.

These responses are a great example of why LLMs are absolutely godawful for producing factual information, because both are massively inaccurate or just plain wrong. 1) To produce neutrinos you use protons, not electrons (it might technically be possible to use electrons, idk I'm not that kind of physicist, but no one does). 2) you don't smash them together, you hit them against a target. 3) Neutrinos are neutral particles and can't be guided using electromagnetic fields. 4) Momentum conservation means the produced neutrinos have to travel in the *same* direction as the incoming protons, not the opposite.

You're mistaking funding for income. The source of income is the end user, but funding mostly comes from investors. Income is (generally) what allow a company to sustain itself and keep running in an operating mode. Funding OTOH allows the company to setup and explore new avenues for income, which in this case means setting up mines/wells/etc, which is far more destructive (long term) for the environment than simply keeping existing projects running. Income can be used as a source of funding, in some cases, but it's a lot harder and scarcer, as investors usually demand the profits in return for their investment. The point of pushing for divestiture is mostly to limit the *expansion* of fossil fuel usage (which is sustained primarily by investors), and not to restrict or reduce current usage (which is sustained primarily by users, not investors). Obviously there are efforts to limit usage as well, but that's done through different means (like fuel efficiency, emissions standards, EV tax credits, etc ).

Which is why no one is suggesting moving to a post-quantum algorithm alone. What Chrome is implementing is a hybrid key exchange, ML-KEM768+X25519 (the X25519 part is a standard elliptical curve cypher). Unless your implementation is absolutely terrible, you can't decrease security by layering on multiple encryption schemes, so even if ML-KEM is no more secure than ROT13, it still won't introduce any new vulnerability.

Actually it's true for any symmetric distribution. IQ happens to be normally distributed (by construction: the underlying raw scores are mapped to a normal distribution, though I suspect the underlying scores are themselves probably normal as well), which is very much symmetric. So, you know, maybe don't cast shade on other peoples' intelligence while making a false claim of your own?

The fact the law has been broken has already been decided, and not by the judge, but by a jury.

The mere existence of other app stores is not enough to say Google is not a monopoly, if those other stores have negligible market presence. Googles monopoly then became illegal when engaged in anticompetitive behavior with their monopoly (monopolies are not inherently illegal unless abused somehow). What *should* happen (and should have happened a decade ago) is Google being split up. But what they'll end up getting is a fairly minor slap on the wrist in a field they only marginally care about as a prop to their real business of ad sales.

Well no, because exactly no one recommends using them by themselves. They're meant to be used with standard key encryption/signing algorithms, so you'd need a QC to break that anyways. Actually at this point laying post-quantum algorithms probably makes sense too, if you're really paranoid.

The Nobel prize to her supervisor wasn't for discovery of the kaon, it was for the development of the photographic technique used in its discovery. The second was also not for the discovery of the particle itself, but for showing it violated CP symmetry.

For that matter she wasn't even the first to discover the Kaon at all: that had happened 2 years earlier at the University of Manchester. Her observations were of an alternative decay pathway. Significant, yes, and that would eventually lead to investigations that would yield a Nobel prize, but simply making those observations (using a technique developed by someone else, in someone else's lab, and under someone else's supervision) might be worthy of a PhD, but wouldn't ever have even been under consideration for a Nobel prize.

Lines like these will be DC, as HVDC is more efficient at long ranges than AC, so there will be negligible electromagnetic radiation, no need for shielding.

That quote isn't why they refused to fulfill the request, it's from an OIG report that mentions the letters. TFA doesn't give a reason for the FDIC refusal to supply the letters.

No, training an AI literally involves making a copy of the training data set. If you walk through any guide on how to get started training your own neural network the second step (after you install Tensorflow et al) is literally "go download a copy of the training data set". Even if you argue that the process of training is somehow similar to a human listening to music (which it's really not: the word "training" is used by analogy with how humans learn, the fundamental process is almost completely different), they would need to have bought a copy of every song in the data set for every single thread they used in their training process, as each of those threads will have its own copy of the training data.

No, they very much have a chance for winning (much as it pains me to agree with the music industry on anything). Copyright, as the name implies, gives the owner the right to control how and when copies of the work are made. Training an "AI" requires making copies of the original work. So unless the rights holder gives permission, using copyrighted data for AI training is a violation of copyright. The "AI" developers will certainly try to argue some kind of fair use exception, but that's a pretty poorly defined area even at the best of times (and commercial uses that compete with the original work are definitely not the best of times).