Another great example of garbage behaviour being the result of employees gaming garbage metrics.

That's what I use AI for as well: a first step. The biggest difference AI and regular sources, is that the latter give you a lot of clues regarding the accuracy of the information. The source, the website, the way the information is written, context like article titles, all of these give some hint about how well the author understands the material, and if their answer is even relevant to your question. The AI however will always appear authoritative, even if they are obviously wrong, and with important context stripped out. Sometimes you get an answer that looks plausible, but is invalid, or about a different version of the gadget you are asking about.

AI has been great for generating artwork, logos, sounds and so on, for small personal projects. And I've use AI deepfake voice generation to provide voice-over for game mods (some of the voice actors have given modders explicit permission to use their voice like that). It lets me do stuff that was completely out of my reach just a few years ago, or things for which I have zero talent.

"Nuclear Power will solve the climate crisis, and it doesn't need a breakthrough or a TED talk, all it needs is a building permit" - Sabine Hossenfelder.

Sure but the advantage of crops is you can easily scale your solar collectors by planting more acres. There are soybean farms with a half million acres out there that would produce significant amounts of biodiesel if used for that purpose. Now algae is a lot more efficient in a physics sense, but an equivalent algae facility would be on the order of 100,000 acres. The water requirements and environmental impacts of open algae pools would be almost unimaginable. Solar powered bioreactors would increase yields and minimize environmental costs, at enormous financial costs, although possibly this would be offset by economies of scale.

Either way a facility that produces economically significant amounts of algae biodiesel would be an engineering megaproject with higher capital and operating costs than crop based biodiesel, but an algae based energy economy is a cool idea for sci fi worldbuilding. In reality where only the most immediately economically profitable technologies survive, I wouldnâ(TM)t count on it being more than a niche application.

Humans drive into stationary emergency vehicles all the time. Self-driving cars don't need to be perfect, they just need to be a bit better than humans. In the end it'll come down to insurance companies*, and they'll just look at the numbers. There will be a point where insurers will charge you extra if you have a steering wheel and pedals fitted.

*) in sane legal systems, where a robotaxi manufacturer can't just be sued for millions just because someone died; the plaintiff would have to show gross negligence. For the rest: liability would lie with the robotaxi operator or owner, through their insurance. Just as is the case now.

It isn't just fanboys. Tesla stock is astronomically overpriced based on the sales performance and outlook of what normal people consider its core business -- electric cars (and government credits). For investors, Tesla is *all* about the stuff that doesn't exist yet, like robotaxis.

Are they wrong to value Musk's promises for Tesla Motors so much? I think so, but it's a matter of opinion. If Tesla actually managed to make the advances in autonomous vehicle technology to make a real robotaxi service viable, I'd applaud that. But I suspect if Musk succeeds in creating a successful robotaxi business, Tesla will move on to focus on something other than that. Tesla for investors isn't about what it is doing now, it's about not missing out on the next big thing.

The real problem with biodiesel would be its impact on agriculture and food prices. Ethanol for fuel has driven global corn prices up, which is good for farmers but bad in places like Mexico where corn is a staple crop. Leaving aside the wildcat homebrewer types who collect restaurant waste to make biodiesel, the most suitable virgin feedstocks for biodiesel on an industrial scale are all food crops.

As for its technical shortcomings, if it even makes any economic sense at all then that's a problem for the chemists and chemical engineers. I suspect biodiesel for its potential environmental benefits wouldn't attract serious investment without some kind of mandate, which would be a really bad thing if you're making it from food crops like oil seeds or soybeans.

Instead of the clunky ICE drivetrain with an electric motor bolted on, I'd rather have that in reverse: a fully electric drive train (with a full size battery), combined with a small petrol generator that can be enabled to extend the vehicle's range. The advantages: much simpler construction, the engine can be kept small and light, and always runs at the optimum RPM, saving gas. There are a few cars with range extenders already, and when enabled they can almost double the range of the car, but sadly most offerings only have a shitty little EV battery that doesn't have much range to begin with.

They might even have conducted their own experiments already, and set the lights accordingly. To maximize profits of course, not to encourage responsible gambling. The casino manager's reaction to: "It is possible that simply dimming the blue in casino lights could help promote safer gambling behaviors" would have been "MOAR BLUE!"

Just one point: "free love" actually has a historical definition. It means that sexual activity should not be regulated by governments. That would also, technically, include the right to practice celibacy.

They will have to increase the price eventually as demand for transport overall rises. The point of the pricing is to deter driving enough that the street network operates within its capacity limits; if driving becomes more desirable than status quo ante, they aren't charging enough and will have to raise prices to keep demand manageable.

Think of it this way: either way, traffic will reach some equilibrium. The question is, what is the limiting factor? If using the road is free, then the limiting factor is traffic congestion. If you widen some congested streets, the limiting factor is *still* congestion, so eventually a new equilibrium is found which features traffic jams with even more cars.

The only way to build your way out of this limit, is to add *so* much capacity to the street network that it far outstrips any conceivable demand. This works in a number of US cities, but they're small and have an extensive grid-based street network with few natural barriers like rivers. There is simply no way to retrofit such a street architecture into a city of 8.5 million people where land costs six million dollars an acre.

So imposing use fees is really is the only way to alleviate traffic for a major city like New York or London. This raises economic fairness issues, for sure, but if you want fairness, you can have everyone suffer, or you can provide everyone with better transportation alternatives, but not necessarily the same ones. Yes, the wealthy will be subsidizing the poor, but they themselves will also get rewards well worth the price.

Well, yes -- the lies and the exaggerations are a problem. But even if you *discount* the lies and exaggerations, they're not *all of the problem*.

I have no reason to believe this particular individual is a liar, so I'm inclined to entertain his argument as being offered in good faith. That doesn't mean I necessarily have to buy into it. I'm also allowed to have *degrees* of belief; while the gentleman has *a* point, that doesn't mean there aren't other points to make.

That's where I am on his point. I think he's absolutely right, that LLMs don't have to be a stepping stone to AGI to be useful. Nor do I doubt they *are* useful. But I don't think we fully understand the consequences of embracing them and replacing so many people with them. The dangers of thoughtless AI adoption arise in that very gap between what LLMs do and what a sound step toward AGI ought to do.

LLMs, as I understand them, generate plausible sounding responses to prompts; in fact with the enormous datasets they have been trained on, they sound plausible to a *superhuman* degree. The gap between "accurately reasoned" and "looks really plausible" is a big, serious gap. To be fair, *humans* do this too -- satisfy their bosses with plausible-sounding but not reasoned responses -- but the fact that these systems are better at bullshitting than humans isn't a good thing.

On top of this, the organizations developing these things aren't in the business of making the world a better place -- or if they are in that business, they'd rather not be. They're making a product, and to make that product attractive their models *clearly* strive to give the user an answer that he will find acceptable, which is also dangerous in a system that generates plausible but not-properly-reasoned responses. Most of them rather transparently flatter their users, which sets my teeth on edge, precisely because it is designed to manipulate my faith in responses which aren't necessarily defensible.

In the hands of people increasingly working in isolation from other humans with differing points of view, systems which don't actually reason but are superhumanly believable are extremely dangaerous in my opinion. LLMs may be the most potent agent of confirmation bias ever devised. Now I do think these dangers can be addressed and mitigated to some degree, but the question is, will they be in a race to capture a new and incalculably value market where decision-makers, both vendors and consumers, aren't necessarily focused on the welfare of humanity?

Data structures and algorithms are used in interviews, not because you'll be expected to implement sorts and linked lists, but because they demonstrate that the candidate can implement and troubleshoot software from specs, using cases they should be familiar with if they have a CS / coding background. Testing for skills rather than knowledge. By the same token, it makes sense to test candidates on the use of AI assistants, if they'll be using those in their work. Though rather than let them produce textbook algorithms with prompts, I'd give them a prompt that produces known faulty output, then ask them to test the result, figure out what is wrong with it, and fix the code and/or the prompt.

Plenty of good content on YT. Enough to justify the €10 or so for a premium subscription, and ad free viewing.

CPB and the government have been collected data directly from the airlines ever since the aftermath of 9/11 through a number of programs, for example to check passengers against watch lists and to verify the identity of travelers on international flights.

What has changed is that by buying data from a commerical broker instead of a a congressionally instituted program, it bypasses judicial review and limits set by Congress on data collected through those programs -- for example it can track passengers on domestic flights even if they're not on a watch list.