Investment is a tricky one.

I'd say that learning how to learn is probably the single-most valuable part of any degree, and anything that has any business calling itself a degree will make this a key aspect. And that, alone, makes a degree a good investment, as most people simply don't know how. They don't know where to look, how to look, how to tell what's useful, how to connect disparate research into something that could be used in a specific application, etc.

The actual specifics tend to be less important, as degree courses are well-behind the cutting edge and are necessarily grossly simplified because it's still really only crude foundational knowledge at this point. Students at undergraduate level simply don't know enough to know the truly interesting stuff.

And this is where it gets tricky. Because an undergraduate 4-year degree is aimed at producing thinkers. Those who want to do just the truly depressingly stupid stuff can get away with the 2 year courses. You do 4 years if you are actually serious about understanding. And, in all honesty, very few companies want entry-level who are competent at the craft, they want people who are fast and mindless. Nobody puts in four years of network theory or (Valhalla forbid) statistics for the purpose of being mindless. Not unless the stats destroyed their brain - which, to be honest, does happen.

Humanities does not make things easier. There would be a LOT of benefit in technical documentation to be written by folk who had some sort of command of the language they were using. Half the time, I'd accept stuff written by people who are merely passing acquaintances of the language. Vague awareness of there being a language would sometimes be an improvement. But that requires that people take a 2x4 to the usual cultural bias that you cannot be good at STEM and arts at the same time. (It's a particularly odd cultural bias, too, given how much Leonardo is held in high esteem and how neoclassical universities are either top or near-top in every country.)

So, yes, I'll agree a lot of degrees are useless for gaining employment and a lot of degrees for actually doing the work, but the overlap between these two is vague at times.

The degree isn't about "getting a high-paid job", it's about knowing what the hell you're doing once you get a job. Although, fair enough, it's quite plausible that not many degrees would meet that standard either.

There is a possibility of a short-circuit causing an engine shutdown. Apparently, there is a known fault whereby a short can result in the FADEC "fail-safing" to engine shutdown, and this is one of the competing theories as the wiring apparently runs near a number of points in the aircraft with water (which is a really odd design choice).

Now, I'm not going to sit here and tell you that (a) the wiring actually runs there (the wiring block diagrams are easy to find, but block diagrams don't show actual wiring paths), (b) that there is anything to indicate that water could reach such wiring in a way that could cause a short, or (c) that it actually did so. I don't have that kind of information.

All I can tell you, at this point, is that aviation experts are saying that a short at such a location would cause an engine shutdown and that Boeing was aware of this risk.

I will leave it to the experts to debate why they're using electrical signalling (it's slower than fibre, heavier than fibre, can corrode, and can short) and whether the FADEC fail-safes are all that safe or just plain stupid. For a start, they get paid to shout at each other, and they actually know what specifics to shout at each other about.

But, if the claims are remotely accurate, then there were a number of well-known flaws in the design and I'm sure Boeing will just love to answer questions on why these weren't addressed. The problem being, of course, is that none of us know which of said claims are indeed remotely accurate, and that makes it easy for air crash investigators to go easy on manufacturers.

It's far from indisputable. Indeed, it's hotly disputed within the aviation industry. That does NOT mean that it was a short-circuit (although that is a theory that is under investigation), it merely means that "indisputable" is not the correct term to use here. You can argue probabilities or reasonableness, but you CANNOT argue "indisputable" when specialists in the field in question say that it is, in fact, disputed.

If you were to argue that the most probable cause was manual, then I think I could accept that. If you were to argue that Occam's Razor required that this be considered H0 and therefore a theory that must be falsified before others are considered, I'd not be quite so comfortable but would accept that you've got to have some sort of rigorous methodology and that's probably the sensible one.

But "indisputable"? No, we are not at that stage yet. We might reach that stage, but we're not there yet.

Eastern Europe was screaming about how dangerous this was, but they weren't listened to.

One of the most insane things is how after Russia's surprisingly poor military performance in the Georgian war, the Merkel government was disturbed not that Russia invaded Georgia, but at the level of disarray in the Russian army, and sought a deliberate policy of improving the Russian military. They perceived Russia as a bulkwark against e.g. Islamic extremism, and as a potential strategic partner. They supported for example Rheinmetal building a modern training facility in Russia and sent trainers to work with the Russian military.

With Georgia I could understand (though adamantly disagreed) how some dismissed it as a "local conflict" because it could be spun as "Georgia attacking an innocent separatist state and Russia just keeping their alliances". But after 2014 there was no viable spin that could disguise Russia's imperial project. Yet so many kept sticking their fingers in their years going, "LA LA LA, I CAN'T HEAR YOU!" and pretending like we could keep living as we were before. It was delusional and maddening.

The EU has three times Russia's population and an order of magnitude larger of an economy. In any normal world, Russia should be terrified of angering Europe, not the other way around. But our petty differences, our shortsightedness, our adamant refusal to believe deterrence is needed, much less to pay to actually deter or even understand what that means... we set ourselves up for this.

And I say this to in no way excuse the US's behavior. The US was doing the same thing as us (distance just rendered Russia less of a US trading partner) and every single president wanted to do a "reset" of relations with Russia, which Russia repeatedly used to weaken western defenses in Europe. And it's one thing for the US to say to Europe "You need to pay more for defense" (which is unarguable), even to set realistic deadlines for getting defense spending up, but it's an entirely different thing to just come in and abandon an ally right in the middle of their deepest security crisis since World War II. It's hard to describe to Americans how betrayed most Europeans feel at America right now. The US organized and built the world order it desired (even the formation of the EU was strongly promoted by the US), and then just ripped it out from under our feet when it we're under attack.

A friend once described Europe in the past decades as having been "a kept woman" to America. And indeed, life can be comfortable as a kept woman, and both sides can benefit. America built bases all over Europe to project global power; got access to European militaries for their endeavours, got reliable European military supply chains, etc and yet remained firmly in control of NATO policy; maintained itself as the world's reserve currency; were in a position that Europe could never stop them from doing things Europeans disliked (for example, from invading Iraq); and on and on - while Europe decided that letting the US dominate was worth being able to focus on ourselves. But a kept woman has no real freedom, no real security, and your entire life can come crashing down if you cross them or they no longer want you.

(Score:X, Troll)

And yet, your imaginary friend still isn't real. ;)

They clearly didn't even use a proper image generator - that's clearly the old crappy ChatGPT-builtin image generator. It's not like it's a useful figure with a few errors - the entire thing is sheer nonsense - the more you look at it, the worse it gets. And this is Figure 1 in a *paper in Nature*. Just insane.

This problem will decrease with time (here are two infographics from Gemini 3 I made just by pasting in an entire very long thread on Bluesky and asking for infographics, with only a few minor bits of touchup). Gemini successfully condensed a really huge amount of information into infographics, and the only sorts of "errors" were things like, I didn't like the title, a character or two was slightly misshapen, etc. It's to the point that you could paste in entire papers and datasets and get actually useful graphics out, in a nearly-finished or even completely-finished state. But no matter how good the models get, you'll always *have* to look at what you generate to see if it's (A) right, and (B) actually what you wanted.

And clearly God (who as we know, is a scalar field) is an AI. That's why there's so much "slop" in the Bible - factual errors, contradictions, different versions of the same text that heavily contradict each other, etc etc. It all makes so much more sense now!

At one point last week I pasted the first ~300 words or so of the King James Bible into an AI detector. It told me that over half of it was AI generated.

And seriously, considering some of the god-awful stuff passing peer review in "respectable" journals these days, like a paper in AIP Advances that claims God is a scalar field becoming a featured article, or a paper in Nature whose Figure 1 is an unusually-crappy AI image talking about "Runctitiononal Features", "Medical Fymblal", "1 Tol Line storee", etc... at the very least, getting a second opinion from an AI before approving a paper would be wise.

FYI, their statement about Iceland is wrong. BEV sales were:

2019: 1000
2020: 2723
2021: 3777
2022: 5850
2023: 9260
2024 (first year of the "kílómetragjald" and the loss of VAT-free purchases): 2913
2025: 5195

Does this look like the changes had no impact to anyone here? It's a simple equation: if you increase the cost advantage of EVs, you shift more people from ICEs to EVs, and if you decrease it, the opposite happens. If you add a new mileage tax, but don't add a new tax to ICE vehicles, then you're reducing the cost advantage. And Iceland's mileage tax was quite harsh.

The whole structure of it is nonsensical (they're working on improving it...), and the implementation was so damned buggy (it's among other things turned alerts on my inbox for government documents into spam, as they keep sending "kílómetragjald" notices, and you can't tell from the email (without taking the time to log in) whether it's kílómetragjald spam or something that actually matters). What I mean by the structure is that it's claimed to be about road maintenance, yet passenger cars on non-studded tyres do negligible road wear. Tax vehicles by axle weight to the fourth times mileage, make them pay for a sticker for the months they want to use studded tyres, and charge flat annual fees (scaled by vehicle cost) for non-maintenance costs. Otherwise, you're inserting severe distortion into the market - transferring money from those who aren't destroying the roads to subsidize those who are, and discouraging the people who aren't destroying the roads from driving to places they want to go (quality of life, economic stimulus, etc)

Sure do :) I can provide more if you want, but start there, as it's a good read. Indeed, blind people are much better at understanding the consequences of colours than they are at knowing what colours things are..

The congenitally blind have never seen colours. Yet in practice, they're practically as efficient at answering questions about and reasoning about colours as the sighted.

One may raise questions about qualia, but the older I get, the weaker the qualia argument gets. I'd argue that I have qualia about abstracts, like "justice". I have a visceral feeling when I see justice and injustice, and experience it; it's highly associative for me. Have I ever touched, heard, smelled, seen, or tasted an object called "justice"? Of course not. But the concept of justice is so connected in my mind to other things that it's very "real", very tangible. If I think about "the colour red", is what I'm experiencing just a wave of associative connection to all the red things I've seen, some of which have strong emotional attachments to them?

What's the qualia of hearing a single guitar string? Could thinking about "a guitar string" shortly after my first experience with a guitar string, when I don't have a good associative memory of it, sounding count as qualia? What about when I've heard guitars play many times and now have a solid memory of guitar sounds, and I then think about the sound of a guitar string? What if it's not just a guitar string, but a riff, or a whole song? Do I have qualia associated with *the whole song*? The first time? Or once I know it by heart?

Qualia seems like a flexible thing to me, merely a connection to associative memory. And sorry, I seem to have gotten offtopic in writing this. But to loop back: you don't have to have experienced something to have strong associations with it. Blind people don't learn of colours through seeing them. While there certainly is much to life experiences that we don't write much about (if at all) online, and so one who learned purely from the internet might have a weaker understanding of those things, by and large, our life experiences and the thought traces behind them very much are online. From billions and billions of people, over decades.

Language does not exist in a vacuum. It is a result of the thought processes that create it. To create language, particularly about complex topics, you have to be able to recreate the logic, or at least *a* logic, that underlies those topics. You cannot build a LLM from a Markov model. If you could store one state transition probability per unit of Planck space, a different one at every unit of Planck time, across the entire universe, throughout the entire history of the universe, you could only represent the state transition probabilities for the first half of the first sentence of A Tale of Two Cities.

For LLMs to function, they have to "think", for some definition of thinking. You can debate over terminology, or how closely it matches our thinking, but what it's not doing is some sort of "the most recent states were X, so let's look up some statistical probability Y". Statistics doesn't even enter the system until the final softmax, and even then, only because you have to go from a high dimensional (latent) space down to a low-dimensional (linguistic) space, so you have to "round" your position to nearby tokens, and there's often many tokens nearby. It turns out that you get the best results if you add some noise into your roundings (indeed, biological neural networks are *extremely* noisy as well)

As for this article, it's just silly. It's a rant based on a single cherry picked contrarian paper from 2024, and he doesn't even represent it right. The paper's core premise is that intelligence is not lingistic - and we've known that for a long time. But LLMs don't operate on language. They operate on a latent space, and are entirely indifferent as to what modality feeds into and out from that latent space. The author takes the paper's further argument that LLMs do not operate in the same way as a human brain, and hallucinates that to "LLMs can't think". He goes from "not the same" to "literally nothing at all". Also, the end of the article isn't about science at all, it's an argument Riley makes from the work of two philosophers, and is a massive fallacy that not only misunderstands LLMs, but the brain as well (*you* are a next-everything prediction engine; to claim that being a predictive engine means you can't invent is to claim that humans cannot invent). And furthermore, that's Riley's own synthesis, not even a claim by his cited philosophers.

For anyone who cares about the (single, cherry-picked, old) Fedorenko paper, the argument is: language contains an "imprint" of reasoning, but not the full reasoning process, that it's a lower-dimensional space than the reasoning itself (nothing controversial there with regards to modern science). Fedorenko argues that this implies that the models don't build up a deeper structure of the underlying logic but only the surface logic, which is a far weaker argument. If the text leads "The odds of a national of Ghana conducting a terrorist attack in Ireland over the next 20 years are approximately...." and it is to continue with a percentage, that's not "surface logic" that the model needs to be able to perform well at the task. It's not just "what's the most likely word to come after 'approximately'". Fedorenko then extrapolates his reasoning to conclude that there will be a "cliff of novelty". But this isn't actually supported by the data; novelty metrics continue to rise, with no sign of his suppossed "cliff". Fedorenko argues notes that in many tasks, the surface logic between the model and a human will be identical and indistinguishable - but he expects that to generally fail with deeper tasks of greater complexity. He thinks that LLMs need to change architecture and combine "language models" with a "reasoning model" (ignoring that the language models *are* reasoning - heck, even under his own argument - and that LLMs have crushed the performance of formal symbolic reasoning engines, whose rigidity makes them too inflexible to deal with the real world)

But again, Riley doesn't just take Fedorenko at face value, but he runs even further with it. Fedorenko argues that you can actually get quite far just by modeling language. Riley by contrast argues - or should I say, next-word predicts with his human brain - that because LLMs are just predicting tokens, they are a "Large Language Mistake" and the bubble will burst. The latter does not follow from the former. Fedorenko's argument is actually that LLMs can substitute for humans in many things - just not everything.

Greater Fool scheme finds Greatest Possible Fools (goverments) to keep pumping money into their zero-sum game.