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.

It is not obvious to me why a water system needs to be on the net. I understand having remote controls of various valves and pumps and so forth, but can't all of that be on a private local network?

It obviously gives us guarantees in terms of what the source will do and what the compiled code should need.

These do not provide memory safety, so memory bugs would not be solved by these. They will find unexpected behavioural issues, though.

The precondition and postcondition statements are not cunningly-disguised assert statements because they're not asserted at runtime. They're enforced at static check and/or compile time.

The policy hints mean that if the kernel is doing something you're not expecting, you find this when testing the code. Equally, though, it means that users cannot cause the software to venture into realms unknown through many of the usual attack vectors because those will require permissions that aren't there.

I suspect that Microsoft, not unreasonably, thinks that the value of their AI slop will be enhanced if they can use an existing property to get people to classify particularly grating AI slop so that they can tune their copilot-related stuff to produce less grating or less obvious slop in the future.

Maybe someone in the org actually cares about linkedin's reputation as a hellscape for aura-farming lunatics; but I'd be shocked if the incentive that MS is actually motivated by is anything but the chance to get a dataset of text ranked by how unpleasantly bot-like it is to try to make their bots less visible.

Looks like Microsoft is trying to convince people to classify more and less distasteful bot slop for them so they can tune copilot outputs in the future.

The winning move is not to play.

Once the supply of customers flush enough to buy under more standard arrangements is saturated you are basically left between ignoring the demand for growth forever or deciding between handling...subprime...customers yourself or keeping the arrangement at arm's length.

This 'restricted mode' that Apple is vigorously denying will be used for lease enforcement suggests that the metaphorical arm is not that long and that Apple seems to be doing more than merely being willing to sell devices to whatever resellers; but it's not a huge surprise that they'd want the risk related to the debt and any shaking down handled by someone who isn't them.

It's entirely possible that they didn't actually care that much. It seems at least as plausible that the sort of people who would risk this sort of legal exposure over a non-issue were more motivated by an excuse to throw weight around and talk like a mob boss than actual concern. Nice to be able to put a hobby project on the company card.

I find it difficult to believe that 'influencers' are a good sign at a society level; but I'm a little puzzled by the degree of hostility to what is basically a degree for self-employed PR/marketing people.

As much as I'm not happy about it, PR and marketing are absolutely entire fields; and I'd assume that people doing those things whose client is themselves would also benefit from a dash of entertainment related law; contracts and accounting related to dealing with sponsor agreements; and the same sort of low-to-intermediate business stuff that routinely trips up musicians, artists, athletes, etc. who suddenly have some worthwhile amount of money/valuable copyrights/etc. but are either wholly dependent on 'agents' of variable quality and honesty or just end up getting screwed.