Like this?

https://www.dreamstime.com/two...

There is reason for some skepticism because some previous claims have turned out that the problems were in fact not unsolved. The LLM just found the existing solutions and used those:

https://techcrunch.com/2026/05...

which is not useless, but not the same thing either. So I would hold on for a bit before accepting the claims.

You are so wrong. The country I live in now has it. It's not called the same, but it amounts to the same. Near impossible to sue the police here.

I'm pretty sure most countries have something similar on the books.

I'm fairly sure at least one entire department at MS is tasked with making sure people don't switch to other formats, that despite on-paper "open" XML it remains incompatible and no competitor software can flawlessly read and write it.

So no, unless you can hire a dozen people full-time to counter that, you don't have a chance to break through that.

Qualified immunity is a reasonable concept that I agree is needed for police work.

It's just being completely overdone, used to cover up clear abuse. The basic idea of "when in doubt, police still needs to be able to act" is sound. The actual practice "unless you can prove to criminal standards and beyond, that the police officer knew at that exact moment, that what they were doing was totally definitely illegal and they intentionally decided to break a law. That's quite a bit too much of "err on the side of caution".

What a complete and utter surprise... to the three people who are so high their brain stopped working but miraculously didn't kill them.

For everyone else, this was literally the first thing we thought about, right? Please tell me I'm not the last sane person on planet Earth. Nobody expected that this would NOT be abused in such ways, right?

I have also been WFH for years before covid. I don't believe my circumstances are the same as everybody's, but I do know I am far from the only person whose duties almost exclusively involve working with people and things that are in another region anyway.

Put another way, employers who gave everyone an effective raise due to exigent circumstances and suffered no harm as a result are now mystified as to why their employees are reluctant to accept an effective pay cut now for no apparent benefit. Given the latter part, they rightly suspect some sort of malfeasance somewhere in management.

Workers want or even need a cost of living adjustment. Employers do not want to and may not be able to afford to increase payroll. For that reason, the COL increases are often several years in arrears as it is. WFH gives the employees an effective raise by eliminating their commute costs and an opportunity to save even more by living somewhere with a lower COL.

As an additional incentive, the employer saves on office space.

On the other hand, WHF was a win-win for employers too. The employees got an effective raise by lowering their cost of living and a reduction in unproductive daily aggravation and wasted time. The employer didn't have to actually pay them any extra to make that happen and could even save on expensive office space. It just wasn't a win for the managers who could no longer hide how bad they were at their jobs.

Perhaps not narcicism so much as short-sighted self interest. Either way, it would be in the company's interest (and the shareholders) to give THEM the heave-ho and leave the workers remote. The workaround for their ineffectiveness costs millions a year.

Adoption is a function of existing adoption and existing availability of resources.

Extremely good OS' and truly amazing computers have failed, not because they were too expensive or had issues, but because they were perceived to be unpopular OR simply lacked enough software that could run on them.

Extremely bad OS' and truly awful computers have succeeded for the opposite reason.

Linux has an extremely good architecture, at least for machines that are mostly operating with CPUs. When most of the work is done by the GPU, it's less obvious that Linux provides the necessary mechanisms to manage resources and abstract away the hardware specifics. That doesn't mean I expect Linux to start fading, but I don't think a centralised OS is necessarily where things will go. However, the reason it hasn't done better so far is simply because potential users and potential software houses had a negative view of it (even though actual users were almost invariably loving the system).

Windows is crashing now not because it is a slow, bug-ridden piece of spyware (which it is, but users have never cared about that in the past), but because it is perceived in increasingly negative light.

They can get vertical samples from space and the ground. What they can't get from space or the ground is how the internals of a system evolve.

The problem with "models" in the abstract is that there are a lot of them and some of the time the thing you want is to know the same point relative to the system and not to the mudball.

Lots of people have gut feelings about AI, positive or negative.

Most of the AI research I can see people doing is focusing on single-element problems (such as finding counter-examples to a mathematics hypothesis) or solving very simple engineering systems (at most a dozen or so components). Most of the benchmarks are even simpler (write a short story at the level generally asked in English classes of primary school kids).

As a result, I think that people have developed either a very cynical outlook or a very optimistic look. Neither of these is entirely realistic, for the simple reason that no actual useful problem fits any of those descriptions.

Digging much deeper, I'm finding that when problems get into the hundreds or thousands of elements, even ChatGPT Sol 5.6 and Claude Fable 5 struggle badly to keep track of accurate relationships, let alone any level of detail.

If you want to solve a relatively simple coupled system (whether to use solar panels or direct solar heating, and which side of the house to place them), I'm sure AI is fine. If you want AI to write a five hundred word story detailing a conversation between Kim Possible, Rufus, and a smoked herring, I'm sure it could cope. Just.

If you want it to do anything hard enough that a human could do with an assistant, the tests I've been using (meaningful rather than synthetic problems) suggest you've developed a fantastically expensive blue smoke generator. We are going to need to see the inference engines developed for previous generations of AI, and the reasoners developed for the semantic web, and perhaps tools that haven't begun to be imagined yet, before AI can do anything non-trivial.

A balloon is not static, it moves with the atmospheric system it is in. Ergo, it tells you how that system evolves. A drone cannot do this.

A drone can stay put, relative to the ground, telling you how a location's atmosphere evolves. A balloon cannot do this.

These are solving completely different types of problem.

You could, of course, construct a hybrid, as balloons are traditionally single-shot. If a balloon carries the measurement gear and a drone capable of carrying that same gear PLUS a deflated balloon, then you can have something that operates as a balloon until it reaches some pre-set location, whereupon the balloon's gas is released and the drone flies the ensemble to a collection point.