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.

There's an obvious bubble, the circular dealings among the large core players are an enormous red flag.

The frontier labs are in the same position that DEC and Sun Microsystems were in the 1990s, as consumer hardware running Linux began to displace them. There will be ups and downs, but the trend is unavoidable.

The productivity gains are not there, AI is great for coding, some customer service is working, but the "50% of all white collar workers" that the frontier labs thought was good positioning last year 1) ain't gonna work but it did 2) infuriate the managerial class.

The frontier labs got away with it, thus far, in part because of concerns over the arrival of artificial general intelligence, which occupies a similar niche to nuclear weapons in the minds of policy makers. We ARE seeing frontier models escaping and attacking others, there ARE hazards, but it's nothing like what was imagined.

And the open models plus wild talent are as much a danger as wild talent was all on its own.

The frontier labs are like the coyote in that last moment when he's windmilling wildly, but not falling yet.

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 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.

Someone needs to launch a national campaign educating people on jury nullification.

The property damage laws are not really the sort of thing nullification is meant for, it's supposed to quickly put an end to the effect of bad laws, but if that's the one tool handy, and it's this much of a social issue, it should be put to work.

The duress deletion function was always obviously and transparently going to get treated as obstruction of justice issue the minute it got used in a high profile case. Here we are.

If you don't want to have trouble at the border, wipe your devices before you get anywhere near, and restore them once you are across. The precursors to this event have been in the news for years - the border is a legal gray zone, act accordingly.

I have mixed feeling here - sad for this kid, whomever he may be. Once again annoyed at the activist/NGO world for not training up to the point they can dodge this *easily* avoided problem. And I'm leaning forward in anticipation of being able to point and laugh at any crypto enthusiasts who make comically implausible arguments about these simple facts.

WIPE YOUR DEVICES BEFORE CROSSING THE BORDER.

Is that clear enough?

I mostly do heavy multi-disciplinary engineering problems (these I also use for checking an AI, as they're typically not good at these sorts of problems), complex coding, OS analysis, stuff like that. However, sometimes I do throw the occasional odd-ball - I've used ChatGPT to propose a workable quantum mechanics that will cope with Doctor Who canon, for example, and to produce an outline for a story in which symphonic metal appears in 1964 that is compliant with current sociological and psychological models of behaviour.

Claude Opus 4.6 was coping surprisingly well with just about everything I threw at it (but ran out of credits fast), but Opus 5 is churning out incoherent babblings to the point I'm worried I may have accidentally summoned Cthulhu.

But Gemini, Grok, and DeepSeek got hopelessly confused on just about everything past a very low level of complexity. They can handle large problems, yes - Gemini has a huge context window - but complex interactions baffle them.

ChatGPT is able to identify issues correctly, but can only outline solutions, it's just not good at depth. 5.6 is a lot better, but still not good at deep answers. ChatGPT is also prone to agreeing for the sake of it, which makes me nervous about trustworthiness.

That is fair enough. I've been trying out Kimi on the free model, and have subscriptions to Claude and ChatGPT. If Kimi is actually as good or better than ChatGPT, at the pro level, then it might be worth my while moving over as ChatGPT has become very disk-hungry of late and I'm pushing right to the very limits on what it can reliably process.

Starting with the Intel 386 it became possible to run a proper operating system on consumer hardware. I can still recall the excitement with that first Redhat 3.03 book and CD I received, sitting in front of a 16MHz i386sx, craving change. I had owned a Vax 11/730, an LMI Lambda, an SGI 210GTXB, but they were just stupid expensive to run and it took a couple friends to move them.

Anthropic and OpenAI are in the same position the workstation vendors were thirty years ago. What they do is amazing, extremely desirable to those of us who create and use software, but SOOO painful price wise. While I'm writing this on my 16GB M1 Mac the Bonsai 1 bit models are downloading. I mostly use Claude Max and an Ollama cloud subscription, but if I can shift some of the work to the machine on my desk ...

I let an RTX 5060Ti go cheap a few months ago, 16GB was just not enough. I don't regret this, but I wish my income position would change. The world would be a different place if the HP Z4 in my kitchen had an RTX 6000 Pro in place of its current GTX 1060. The advent of TurboQuant makes me want to try some things on one of the Intel GPUs - maybe that entry level sedan price on the RTX 6000 Pro is no longer the real barrier to entry.

These are strange days we are living, strange days indeed ... and no reactionary pack of ninnies is going to be able to do anything. It's a fine thing, having China defending our freedom to create, eh?

I changed careers thirty years ago to get Microsoft out of my life and I've never regretted that decision.

Using Microsoft operating systems is like dating a morbidly obese person who is continually in and out of the psych ward, and they've got a cluster B character disorder, one of the really manipulative ones.

I do not understand how that company's products are not limited to historic niches that are too difficult/unprofitable to clear.

Perhaps the advent of AI is going to lower the barrier to entry for decent operating systems. The Unix based ones have always seemed easier to me, but I'm an aspie weirdo so my opinion only counts just a little.

Although the Chinese models are all considerably smaller, it's not obvious to me that they're as good or better. They could be, but I'm not convinced the benchmarks that currently exist are stressing the models enough to establish where models actually are any good.