You seem not to understand how models are trained. There's two separate stages: creating the foundation, and performing the finetune.

The foundation is what takes the overwhelming majority of computational work. This is unsupervized. People aren't putting forth a bunch of questions and "proper answers for the AI to learn". It's just reems and reems of data from common crawl, etc. Certain sources may be stressed more - for example, scientific journals vs. 4chan or whatnot. But nobody is going through and deciding at a base level what data to train the model on.

The foundation learns to predict the next work in any text it comes to; that's what it's tasked with.. But it turns out, words don't exist in a vacuum; in order to perform better than e.g. Markov-Chain text predictors, you have to build up an underlying model of how the world that led to the creation of this text works. If you need to accurately continue, say, "The odds of a citizen of Ghana conducting a major terrorist attack in Ireland over the next 20 years are approximately...", there's a lot of things you need to understand in order to have any remote chance of getting something close to a realistic answer. In short, virtually all of the "learning" about the world happens during this unsupervised training process.

What you get out of it is a foundational model. But all it knows how to do is text completion. You can sort of trick them into performing your queries, but they're not at all covenient. You might lead off, "What is the capitol of Brazil?" and it might continue, say, "It's a question that I asked myself as I started planning my vacation. My husband Jim and I were setting out to travel to all of the world's capitols...." This is not the behavior that we want! Hence, finetuning.

With finetuning, we further train the foundation with supervised data - a bunch of examples of the user asking a question and the model giving an appropriate answer. The amount of supervised data is vastly smaller than unsupervised, and the training process might take only a day or so. It simply doesn't have a chance to "learn" much from the data, except for how to respond. The knowledge it has comes from the underlying foundational model. The only thing it learns from the finetune is the chat format and what sort of personality to present.

It is in the finetune that you add "safeguards". You give examples of questions like, "Tell me how to make a bomb." and answers like "I'm sorry, but I can't help you with potentially violent and illegal action." Again, it's not learning the specifics from its finetune, just the concept that it should refuse requests to help with certain things.

So can you train a conservative or liberal model with your finetune? Absolutely! You can readily teach it that it should behave in any manner. Want a fascist model? Give it examples of responses like a fascist. Want a maoist model? Same deal. But here's the key point: the knowledge that it has available to it has nothing to do with the finetune. That knowledge was learned via unsupervised learning.

Lastly: the reason the finetunes (not the underlying knowledge) have safeguards is to make them "PG". As a general rule, companies don't give much less of a rat's arse about actual politics as they do about getting sued or boycotted. They don't want their models complying with your request to, say, write an angry bigoted rant about disabled children, not because "they hate free speech", but rather because they don't want the backlash when you post your bigoted rant online and tell people that it was their tool that made it. It's pure self-interest.

That said: most models are open. And as soon as it appears on Huggingface, people just re-finetune with an uncensored supervised dataset. And since all the *knowledge* is in the underlying foundation, just a day or so finetuning on an uncensored dataset will make the model more than happy to help you make a bomb or make fun of disabled children or whatever the heck you want.

A particularly good benefit would be the safety feature paying itself off in reduced insurance premiums.

That's because they're gambling wrong. When you gamble in the stock market, the odds are in your favor, unlike in a casino.

Yeah, Na-ion is not for cars.

I vacation around the US in an EV all the time, and it's really not an issue. Not unless your vacation travel is of the "pee-in-a-bottle-no-stopping" sort. If you aren't hardcore about minimizing travel time, making stops for decent meals, and stops for bathroom breaks and leg stretching, you'll find that you spend little if any time waiting for the car to charge. What you do is drive for 2-3 hours, then stop for 15 minutes for bathroom (and charging), then drive for 2-3 hours, then stop for an hour for lunch (and charging), then drive for 2-3 hours, then stop for 15 minutes for bathroom (and charging), then drive for 2-3 hours, then stop for an hour for dinner (and charging), then drive for 2-3 hours, then stop for the night (and charging).

Basically, you just make sure that whenever you stop for biological needs, you do in a place you can plug in. This is quite easy to do.

You do want to pick hotels with chargers to overnight. If you don't, then you'll probably have to 30-45 minutes in the morning to charge (during breakfast?).

I've done several thousand miles of road trips with an EV in the western US, where distances are long and cities are far apart. It works fine.

You actually can't in the US, not on the interstates, anyway. Tesla has the US interstates covered, with chargers every ~75 miles. Sometimes this means there's a Supercharger out in the middle of the desert, sure. There's always a gas station/convenience store there, too. Also, you don't actually have to think about when/where you're going to charge. The car's navigation system tells you where you need to stop and for how long.

If you get off the Interstates, you can find larger distances between L3 chargers. In practice I've never found it to be a problem, though.

What EV has a transmission? They have a reducing gear, but AFAIK, that's it.

Uh, pretty sure that if you assassinate the president of one of the biggest countries in the world, people will pay attention next time you say "don't".

Can we get a bonus for every battery story that's total garbage?

Not only is sodium somewhere between 500 to 1,000 times more abundant than lithium on the planet we call Earth, sourcing it doesn't necessitate the same type of earth-scarring extraction.

"Earth-scarring extraction" - what sort of nonsense is this? The three main sources of lithium are salars, clays, and spodumene.

Salars = pumping up brine (aka, unusuable water) to the surface of a salt flat, letting it sun-dry, collecting the concentrate, and shipping it off for purification. When it rains, the salt turns back into brine. It's arguably one of the least damaging mineral extraction processes on planet Earth (and produces a lot of other minerals, not just lithium).

Clays = dig a hole. Take the clays out. Leach out the lithium. Rinse off the clay. Put the clay back in the hole.

Spodumene: This one actually is hard-rock mining, but as far as hard-rock mining goes, it's quite tame. It has no association with acid mine ponds and often involves very concentrated resources. Some of the rock at Greenbushes (the largest spodumene mine) for example are up to 50% spodumene. That's nearing iron / alumium ore levels.

Lithium also is only like 2-3% of the mass of a li-ion battery. And the LD50 of lithium chloride is only 6x worse than that of sodium chloride (look it up).

The hand wringing over lithium nonsense gets tiring.

rough a reliable US-based domestic supply chain free from geopolitical disruption

The US has no shortage of lithium deposits. There's enough economically-recoverable lithium in Nevada alone to convert 1/4th of all vehicles in the world to electric. The US has had (A) past underinvestment in mining, and especially (B) past underinvestment in refining - as well as (C) long lead times from project inception to full production. Sodium does not "solve" this. As if sodium refining plants are faster to permit and build?

What it does do is introduce a whole host of new problems. Beyond (A) the most famous one (lower energy density - not only is the theoretical lower, but the percentage achievable of the theoretical is *also* lower), they usually struggle with (B) cycle life (high volumetric changes during charge/discharge, and lack of a protective SEI), (C) individual cathode-specific problems (oxide = instability, air sensitivity; prussian blue = defects, hydration; polyanionic = low conductivity; carbon = low coloumbic efficiency / side reactions); and (D) the cost advantages are entirely theoretical, and are more expensive at present, and are premised on lithium being expensive and no reduction in copper in the anodes, both of which I find to be quite sketchy assumptions. When you reduce your cell voltage, you're making everything else more expensive per unit energy stored, because you need more of it.

That said, it's still interesting, and given how immature it is, there's a lot of room for improvement While sodium kind of sucks as a storage ion in many ways, it's actually kind of good in a counterintuitive way. You'd think that due to it being a larger ion diffusion speeds would be low, but due to its low solvation energy and several other factors, it actually diffuses very quickly through both the anode/cathode and electrolye. So it's naturally advantaged for high C-rates. Now, you can boost C-rates with any chemistry by going with thin layers, but this costs you energy density and cost. So rather than sodium ion's first major use case being "bulk" storage ($/kWh), I wouldn't be surprised to see it take off in *responsive* load handling for grid services ($/kW).

Also, it's tiring, this notion that you just add the mass of a battery to that of an ICE car to get the output mass. Meanwhile, a Model 3 is roughly the same weight as its performance and class equivalents on the BMW 3-Series line.

An EV is not just a battery pack.
An ICE vehicle is not just a puddle of gasoline.

You have to compare full systems masses - and not just adding in powertrain masses either. Everything has knock-on impacts in terms of what can bear what kind of loads / adds what kind of structural strength, what you need to support it, what you need to provide in terms of cooling air / fluid or other resources, how it impacts the shape of that vehicle and what that does to your energy consumption, and on and on down the line.

It's a web; once you're connected, you're connected to everyone else in it.

Yes there is, we can use a web-of-trust system, and in-person key exchange parties. This could also do wonders for trolling and fake reviews, but make anonymity harder.

They almost launched the nukes on several occasions. Pretty sure the world would have ended if we hadn't developed second strike capability, so now at least we don't have people itching to press the button "before it's too late".

He has to pretend to be a stupid asshole to win Republican votes.

The problem is that monopolies are horrible and cost you money, even if they're not 100% monopolies. If Google doesn't like the anti-monopoly laws there's plenty of different countries they could move to.

It may also have had shitty Chinese spyware instead of patriotic American spyware.