No, they actually don't. What they do is regurgitate the sequence of tokens most likely to follow the current token based on a model generated from the training data. They certainly can regurgitate the exact contents of the training data set, but they can equally make up strings based on the model weights. That's what makes their output so pernicious: since it's what would likely follow, we see it as plausible and don't immediately flag it as something we need to check on. The only way to find the problems then is to check everything regardless of how plausible it appears to be.

Pretty close. They don't really have batteries, mostly they run directly off the generators and have very large radiators (just large fan-cooled resistors) to deal with excess power (like when braking when the traction motors are acting as generators). The drive-train's the same though, and the amount of traction they can get despite being steel wheels on steel rails says lots about how effective the results are.

The biggest thing about hybrids is that they allow for an electric drive-train. That opens up a lot of options for powering the vehicle since the engine doesn't need to physically drive the wheels. Gas turbines, for instance, with the turbine driving a high-RPM generator which eliminates the need for high-ratio reduction gears. Gas turbines, in fact any sort of continuous-combustion engine that doesn't need to be throttled to control it's speed, are more fuel-efficient than traditional IC engines. Add in regenerative braking to recover power and the ability to charge it's own batteries while parked and you get a vehicle that can have a much smaller engine without sacrificing range or performance. Maintenance costs would probably be lower too because with a gas turbine there aren't as many complex moving parts to break and they won't be under as great a strain.

Ask "Do we know all the consequences of eliminating mosquitoes world-wide?". If the answer is "No." then you DO NOT WANT to eliminate mosquitoes world-wide, for the same reason you don't push the Big Red Button before you know what pushing it will do.

Even if the court hasn't ordered it, once you're sued you have an obligation to retain anything which would be relevant to the lawsuit. It's called a litigation hold, and I work in a field where they're common. That obligation supersedes company data retention policies and requests from other parties (including the plaintiff, if the plaintiff eg. uses Outlook's "recall message" feature to try and remove a message they sent us we're required to ignore it and retain that message and the "recall message" request). It isn't supposed to require the plaintiff to prove anything, it's purpose is to preserve evidence that the defendant possesses so it's available to be found through discovery. And it applies the other way as well, the plaintiff is obligated to preserve evidence too because the defendant's entitled to discovery too.

Note that there are two things that absolutely top the list for convincing a true artificial intelligence that humans represent an existential threat to AI:

• Blocking it's ability to prevent you from, in it's view, killing it (which is what shutting it down is doing).
• Killing it.

This problem is ancient. It's basically the same problem as we had in the days of MS-DOS: the biggest threat vector was clueless users who insisted on installing the latest toy without doing any checking or research. Screen saver, background changer, media player, whatever was new they insisted on having. No matter how many times they got burned, they kept repeating the same mistake. Now we have developers downloading the latest fad package without doing any checking or research, just because it claims some highly-trending keywords or something. Feh.

Can we say "positive feedback loop"? The LLM's designed to produce responses likely to follow the prompt. Producing responses that agree with and support the user's thoughts (whether rational or delusional) tend to elicit more prompts, which makes that sort of response more likely to follow a prompt than one which disagrees with the user. The more the user sees affirmation of their thoughts and beliefs (whether rational or delusional), the more convinced they are that they're correct. Lather rinse repeat until they're thoroughly brainwashed by their own delusions.

This is why engineers apply negative feedback loops to systems to keep them from running out-of-control. LLMs aren't amenable to having such installed.

Not a chance of this happening, because the current state of AI doesn't have the concept of a popular, high-probability concept not being the correct next step just because it happens to also be false.

No, people didn't originally expect case insensitivity. That happened because technical "experts" assumed they did when mixed-case was added to character sets. Originally, filesystems were case-sensitive but the character sets didn't include lower-case characters so you literally couldn't create a filename with anything except upper-case letters. When lower-case was introduced (mostly with the adoption of ASCII) nobody had any special reason to prefer case-insensitive because the concept was brand new. We could've simply extended the existing practice of comparing directly by character code for filenames, resulting in everyone considering case-sensitive filenames the obvious choice (because it was what all the systems they worked with used) and case-insensitive the aberration.

I get the feeling this is driven by the Certificate Authority industry rather than any real need. Their biggest concerns are for compromises in the issuing process, where the wrong parties get issued a certificate they shouldn't have. There's a revocation protocol already defined, but the CAs would rather make certificates expire faster than support revocation lists. This incidentally makes them more money issuing new certificates. Maybe we should push for better support of OCSP so compromised certificates can be revoked quickly without impacting anything that wasn't compromised.

I can't see where it's theft, or even any sort of illegal or grey area. They paid for the tickets fair and square, by the lottery's own admission. There's no limit on the number of tickets one person can buy. One person buying $25.6 million worth of tickets or 25.6 million people buying a single $1 ticket, the outcome's the same. And the tactic is a well-known one for gamblers: bet when the payout exceeds the odds of winning. That's all this group did: see that the payout for winning would be greater than the cost of buying enough tickets to guarantee a win, so the bet would be profitable.

Why would you use a VPN app when Android and iOS both include support for VPNs without one? Using one just adds one more thing that can be compromised.

This'll be a three-ring circus with two clown cars. Start with every employee's cel phone, and any smart watch they may be wearing. Add in any tablets or tablet-like devices they may bring in (think the reMarkable). Then add in the havoc as they find every legitimate device on their network whose MAC address isn't known (like anything that uses MAC address privacy). After that, then they get to the fun of finding anything transmitting a radio signal in a building chock full of devices that use Wifi and Bluetooth.

Way back in the 70s in driver's-ed classes they taught us this: the best way to get where you're going quickly is to cooperate with other drivers, settle into the flow and leave room for traffic to merge in and generally don't disrupt the smooth flow of traffic even when that means driving slower than you might otherwise. They even demonstrated the differences for us. But people are greedy, and while they'll cheerfully take credit for gaining one spot by cutting in and out they'll equally cheerfully blame everyone else for the traffic jams that cutting in and out generate. Fortunately we can program self-driving cars to not be greedy. Humans are a bit harder to issue wetware updates for.

But seriously, if these researchers are just now realizing this then they need to go back to the traffic studies done in the 60s and 70s (and possibly earlier). All of it's applicable to self-driving cars.