The weird thing about that scenario is, they made it into a kid's movie.

You're not thinking it through -- the goal isn't just to put everyone on benefits and make them spend the rest of their lives clicking the TV remote and waiting for their next welfare check. If you want to do it right (and the robots provide sufficient surplus resources to support it), you go a step further and hire people to do the job they always wanted to do, whether it makes a profit for anyone or not. If that means we have 100,000 ski instructors and 300,000 mediocre artists, then so be it; the robots do the grunt work, and the people are paid to do their preferred avocation.

Not that I expect that to actually happen, of course; in the event the robots actually can replace all labor, the upper classes will make sure that economic surplus goes to themselves, with only the absolute minimum getting distributed to anyone else.

Honestly, they don't "need" robots or anything else; they could just keep doing what they've always done and hope for the best.

However, unlike some countries I could mention, the Chinese government has a vision of what it wants its future to be like, and is willing to work and invest to realize that vision. Hence robots, and other economic development.

There has been plenty of progress in using AI to control robotics; they use robotics-specific AIs for that, of course.

The fact that ChatGPT (or even LLMs in general) isn't particularly useful for robots shouldn't be a surprise, since robots (other than maybe C3PO) are about physical manipulation of objects, not about language generation.

The point is, its possible to drive on roads in NZ that are not maintained by the government, so the tax ostensibly being paid per mile in fuel tax isn't going to maintain the road you are necessarily on...

And when driving from the UK to France, the ICE drivers are using UK road-taxed fuel, so the counter-point is the same :)

It doesn't even have to be linked to the car tax.

NZ uses "Road User Charges" for diesel - it does not have the tax built in at the pump (petrol does), so all diesel cars have to buy blocks of kilometres as tax. The government get updated when your annual vehicle inspection is done, but between those inspections its up to you to make sure you have enough spare kilometres left for your trips. If you get stopped by police and they check, being too far out is considered to be tax evasion and a criminal offence.

Who are already required to record mileage on UK roads for other reasons, so thats a solved problem.

And in New Zealand you can easily drive miles and miles on private roads, which are not maintained by the government...

I think this view gives the crypto bros too much credit. They might now be thinking about taking advantage of the opportunity to wrestle the system away from the Wall Street bros, but there was no such plan.

To intercept them you still have to identify them, which you can't do until after they perform the sabotage. Given that, what's the benefit in sinking them rather than seizing them? Sinking them gains you nothing, seizing them gains you the sabotage vessel. It probably won't be worth much, but more than nothing. I guess sinking them saves the cost of imprisoning the crew, but I'd rather imprison them for a few years than murder them.

Very much unlike an intern (the doing-over part).

You ignored his core point, which is that "rocks don't think" is useless for extrapolating unless you can define some procedure or model for evaluating whether X can think, a procedure that you can apply both to a rock and to a human and get the expected answers, and then apply also to ChatGPT.

Heh. It says a lot about the pace of AI research and discussion that a paper from last year is "old".

This is a common thread I notice in AI criticism, at least the criticism of the "AI isn't really thinking" or "AI can't really do much" sorts... it all references the state of the art from a year or two ago. In most fields that's entirely reasonable. I can read and reference physics or math or biology or computer science papers from last year and be pretty confident that I'm reading the current thinking. If I'm going to depend on it I should probably double-check, but that's just due diligence, I don't actually expect it to have been superseded. But in the AI field, right now, a year old is old. Three years old is ancient history, of historical interest only.

Even the criticism I see that doesn't make the mistake of looking at last year's state of the (public) art tends to make another mistake, which is to assume that you can predict what AI will be able to do a few years from now by looking at what it does now. Actually, most such criticism pretty much ignores the possibility that what AI will do in a few years will even be different from what it can do now. People seem to implicitly assume that the incredibly-rapid rate of change we've seen over the last five years will suddenly stop, right now.

For example, I recently attended the industry advisory board meeting for my local university's computer science department. The professors there, trying desperately to figure out what to teach CS students today, put together a very well thought-out plan for how to use AI as a teaching tool for freshmen, gradually ramping up to using it as a coding assistant/partner for seniors. The plan was detailed and showed great insight and a tremendous amount of thought.

I pointed out that however great a piece of work it was, it was based on the tools that exist today. If it had been presented as recently as 12 months ago, much of it wouldn't have made sense because agentic coding assistants didn't really exist in the same form and with the same capabilities as they do now. What are the odds that the tools won't change as much in the next 12 months as they have in the last 12 months? Much less the next four years, during the course of study of a newly-entering freshman.

The professors who did this work are smart, thoughtful people, of course, and they immediately agreed with my point and said that they had considered it while doing their work... but had done what they had anyway because prediction is futile and they couldn't do any better than making a plan for today, based on the tools of today, fully expecting to revise their plan or even throw it out.

What they didn't say, and I think were shying away from even thinking about, is that their whole course of study could soon become irrelevant. Or it might not. No one knows.

We know it weakly interacts electromagnetically, which means one of the ways in which it is posited planets form, initially via electrostatic attraction of dust particles, isn't likely to work. This means dark matter will be less "clumpy" and more diffuse, and less likely to create denser conglomerations that could lead to stellar and planetary formation.

What this finding does suggest, if it holds true, is that some form of supersymmetry, as an extension fo the Standard Model is true. Experiments over the last 10-15 years have heavily constrained the masses and energy levels of any supersymmetry model, so it would appear that if this is the case, it's going to require returning to a model that some physicists had started to abandon.