"The whole point of this is because Waymo isn't supposed to make those mistakes,"

There is no whole point in such a complex issue, but I would like to tell this person that the idea is part of the argument for automated vehicles is they may make less mistakes. Perfection shouldn't be a condition for improvement.

No, I'm not. Don't be a sperg.

No, it isn't. 12oz 4pk@$10.99 = $2.75

No, it isn't. ~56,500 12oz in a 80k lbs trailer, max.

Wrong "value." Retailers don't pay retail, obviously.

Proprietary service drops support for proprietary protocol..

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.

Yeah, the energy drinks aren't going to make anyone wealthy, but it's still a payday. The retail value of a trailer full of Red Bull is about $130,000. Figure they'll get maybe 10% of that from some retailer and you clear $13,000, tax free. Low risk, because it's not drugs or guns or whatever. Not bad for maybe a couple hours work.

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".

Right now, we're noticing that Chinese companies are offering us exploitative deals, and we don't like it, and think that tariffs will fix it. But with tariffs in place, we will find that now it's American companies that are offering us the exploitative deals, but they can charge more now, because they're insulated from outside competition. What I'm saying is that intranational capitalism is just as sleazy and brutal as international capitalism - only less efficient, because it's less competitive.

I agree with you about NATO states paying for mercenaries to defend Ukraine. There are many experienced fighters in Africa and the Middle East, and it's likely that their services could be bought at a reasonable price. Without more soldiers in the field, Ukraine's front is doomed to collapse.

I love AI and I would and could pay for it if I had to, but why would I pick OpenAI to pay? Their product is not really better than their competitors' products, and sometimes it's clearly worse. They have the advantage of being the first mover in their field, and that gives them inertia with low-information customers - the new AOL.com. But apart from that, they have huge debts and not much else to distinguish them. Their best employees had left, and their former partners have become wary of the way they operate. Projections of their future profitability must be based on the expectation that their AI will figure out some better business plan than what the OpenAI humans have come up with!

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.

Free is a fiction that exists exclusively in the minds of stupid people.

Microsoft is not a person. It is a massive company capable of pursuing many mandates, some of which can either appear or can actually be entirely at odds with each other.

The thing about adopting evidence-based policy is that you also need to review and if necessary change policy when more evidence becomes available. The kind of situation you're describing would surely qualify.

As early as the 1950s, critics of the establishment's public education system said its main purpose was to produce a contented and functional workforce. And they were right. They were so right that even they themselves did not understand the full implications: they were so right that it ultimately made them wrong. And then they won, and we are facing the consequences. Not just since 2013: Arne Duncan was indeed an unmitigated disaster for American education, but much of the problem is older than him. And no one is willing to admit that what came before worked better.