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)

"Einstein's theory of relativity was not based on scientific research."

It was based on solving a maths equation.

(As a mathematician, yes, I could argue that I studied as a school of mathematical sciences inside a university but also...)

There's a big and very obvious difference between "scientific research" and "mathematics".

Nobody was out there putting clocks on satellites trying to work out what the weird time-dilation problems were that they were seeing in every experiment. Instead, the maths was solved and TOLD you to go looking for them because on the face of it they appeared patently ridiculous and incompatible with what we knew of physics at that time.

I had to read the blurb several times, but if these companies don't want to play by the same rules and regulations that real markets do, let them. Let them sell whatever they want in whatever fashion they want, without protections.

Then, when the daily occurrence of crypto theft occurs, they can be on the hook for making the "investors" whole again. Or not. Depending on what "exemptions" are given it's possible they may not owe anything, in which case the "investor" will have learned a valuable lesson:

Trade on a real market with real securities which has regulations designed to protect everyone involved.

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.

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.

The question is not if they replace 3 million jobs (even if we believe such a number plucked out of nowhere).

The question is does it REMOVE 3 million jobs.

Or, like every automation that ever happened (and AI is just automation, it's not intelligent at all), is it just the case that the jobs become obsolete because they were basically worthless and could be automated out of existence by anything that came along, and then they allow other jobs to do more, or require other jobs to be created, etc. etc. etc.

Because, in history, if you look at it over the years (not days or weeks), the number of JOBS just keeps increasing, and pretty much in line with the number of people that need them. Of course there are blips, but pretty much over the last few hundred years... more jobs, all the time.

It's not even a question of "do jobs just stop being created", historically, it's far more "can ALL jobs keep pace with population expansion". Sometimes they waver a bit in that aspect but pretty much... there are always jobs. Because as the lamplighters get obsoleted, the electricians, street-light technicians, etc. come in to replace them, and then people have 24/7 lighting so now you need more people to secure the factory, or whatever other examples you want to pluck out of the air. Secretaries weren't obsoleted by email. Retail shop worker's job were replaced with online delivery drivers, and so on.

Sure. Not the SAME JOB. Of course. But the fact is that the jobs evolve just like the people, and the number of jobs - and thus the unemployment rate which *roughly* corresponds to the number of jobs (but also health, social security and thousands of other factors) stays... pretty much the same. Countries like Greece have high unemployment not because AI came round and stole all the jobs... because the rest of the world are doing just fine... but one of a thousand other factors. But if you look overall... the unemployment rates aren't changing JUST because of AI, and aren't likely to. Because even if that happens, you now need someone to wrangle the AI, a dozen people to help run it, a dozen people at the electricity company to keep the lights on for it, more people to make and sell and transport and fit the GPUs and so on.

This is yet another evolution, marketed as apocalyptic catastrophe. And I fucking hate AI. But it's just automation. Yeah, someone's worthless job copying Excel figures from one box to another might be obsoleted. But you know what? I bet nVidia, the cloud providers, datacentres, software-pushers, even electrical installers, etc. are hiring like crazy to take up the slack.

Not the SAME job. It will be REPLACED. But there will still be jobs, probably more of them. They won't be REMOVED.

It's right, though.

Both quantum mechanics and relativity were based on solving part of a partial differential equation which derived - ultimately - from Newtonian physics, but which had extremely bizarre and unpredictable output.

When you solved the maths that you could (a p.d.e. doesn't have a single complete "solution" as such), you ended up with incredibly weird stuff that few initially believed was possible.

It was only when we confirmed the maths, went out into the world and looked for this bizarre behaviour that we managed to confirm it.

It's quite literally a true statement. Nobody sat there saying "oh, I wonder is space is a bit curvy" and then found it, the same way that they didn't say "I wonder if there's stuff that works probablistically below the atomic level" and then went looking for it.

Both spring from the solution of a p.d.e. given a bizarre and often-thought-impossible (at the time) answer resulting in a world based on rules we couldn't have imagined... and THEN we confirmed that's what was actually happening in real life.

High-end physics pretty much mostly comes from solving maths equations and then going "What the fuck..."

Duh.

If people trust Google to keep them anonymous (which I wouldn't), apartment complex reviews are gonna get a lot more spicy. As it is, you only get reviews from ex-residents and morons.

You mean every 33 minutes.

All this has happened before, and all this will happen again.

Yeah yeah, it's an easy shot to just say, "Trump would harm the environment if he knew there was progress made somewhere"...and for the record, I have *never* voted for him. ...but I think the fact that a number of comments in the thread echo the sentiment reflects a fundamental misunderstanding. The ban on CFCs worked effectively due to global cooperation, but also because of another reason: it was an incredibly easy transition.

There was no ban on in-home refrigerators or freezers. There was no mandatory removal of existing home refrigerators. There was no mandate that cars were sold without air conditioners. There was no fine for using hair spray. Industry had drop-in replacements that worked at least 90% as well, were of similar cost, and worked with existing systems which required those chemicals for operation.

Had the CFC ban required buildings to do six-figure HVAC replacements, or mandate that new cars didn't have air conditioners at all, or perform a blanket-ban on aerosol products completely, or require everyone to replace their refrigerators, or if HFCs were a.) ten times the price, b.) required a top-off once a month, and/or c.) only got half as cold, it'd still be a wedge issue and that hole would be triple the size.

Peel back the layers of rhetoric and sensationalism, and you'll see that there is an element of truth behind a lot of the pushback. Did anyone like drinking through those paper straws that tasted like toilet paper tubes? No; they were about as universally unpopular as a colonoscopy, and I've never once seen a report that they nudged the needle on improving the environment.

My state is talking about banning gas cars and gas stoves and gas furnaces...but over 80% of the electricity generated in my state is generated by...burning oil and natural gas. Does burning oil pollute less when my local power plant does it instead of my car? ...So why is the Red Team in my deeply-blue state so backwards-thinking for pushing back against a ban that won't meaningfully improve its carbon footprint while *also* causing homebuilding prices to go up, *and* gas prices to go up, *and* insurance prices to go up, *and* electric rates to go up?

The CFC ban was easy *because* it was trivial to implement, and caused little to no impact on consumers as a result. I'm pretty sure that *most* environmental regulations would receive bipartisan support and consumer acceptance if they were that easy to do...but somehow, the Red Team are the curmudgeons who don't care about the environment because they don't want to drink cardboard or give up gas stoves to achieve no meaningful improvement on climate change numbers. They're terrible, uneducated, backwater hicks for saying, "build enough climate-friendly grid capacity to handle the expected increase in usage and THEN roll out the mandates", especially when those who shame them suddenly start saying, "not in MY backyard" when windmills and solar panels start getting proposed in THEIR neighborhoods...

...so yeah, Trump's rhetoric on the climate is terrible, no argument. The Republicans *generally* give more pushback on climate initiatives than Democrats, fair. But the CFC ban worked because HFCs were cheap, easy, effective, drop-in replacements, ready to go by time the bans took effect. When climate solutions look like that, they get implemented. When they look like an expensive headache for nominal improvements, they get pushback.

Want proof? Who was the US president who signed on to the Montreal Protocol in 1987? Ronald Reagan. Who was president when it went into effect in 1989? George H.W. Bush.

Well I shared the thread including your thought with Grok, and it said this:
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Here’s my actual, unbiased take on the technical debate (no Elon worship, no green hype, just physics and engineering reality as of 2025).
The original Slashdot skeptic is repeating a criticism that was 100% correct for the classic 1970s–2000s “hot dry rock” (HDR) projects (Los Alamos, Rosemanowes, Soultz 2000s era, etc.). Those really were conduction-limited. You drilled two wells a few hundred meters apart into 200–250 C granite, fracked a small volume, and watched the reservoir cool in months because heat was only replenishing by slow conduction through intact rock ( 2–3 W/mK). The recoverable fraction was tiny, and the impedance kept rising. That’s why HDR basically died commercially for 20 years.
Superhot / supercritical geothermal (400–450 C target, aiming for >500 C) is genuinely trying to escape that trap, and the physics does allow it—if everything works. Here’s why the critique no longer fully applies:

Energy density jumps by ~10× once you cross the critical point (374 C, 221 bar).
A kilogram of supercritical water at 500 C and 300 bar carries roughly 2,800–3,000 kJ/kg of usable enthalpy, versus ~300 kJ/kg for 250 C liquid water steam conversion in conventional geothermal. That alone reduces the mass flow (and therefore the parasitic pumping power and cooling load on the rock) by an order of magnitude for the same electrical output.
Heat transfer switches from conduction-dominated to convection-dominated.
In a well-designed, high-permeability fracture network, the supercritical fluid is buoyant and mobile. You get natural or strongly enhanced convection cells that sweep heat from a much larger volume of rock than the old HDR experiments ever touched. Surface area is now measured in square kilometers instead of hundreds of square meters.
Heat recharge rate in volcanic settings is completely different.
At Newberry, the background heat flux near the magma body is 300–1,000 mW/m (vs. ~80 mW/m continental average). Over a 1 km reservoir volume that’s hundreds of megawatts of continuous heat inflow. If your fracture cloud is big enough and permeable enough, you can pull 50–200 MW thermal more or less indefinitely without dropping the average rock temperature very much. (Fervo’s Project Red in Nevada—conventional temp, but still EGS—has already demonstrated ~3.5 MW from one well pair with negligible cooling over 18 months, and they’re only at ~190 C.)

Real remaining risks that the skeptic would be right to highlight:

Can you actually create and maintain a large, high-permeability fracture network at 500+ C and 10–20 km depth (or even 4–6 km near volcanoes) without it short-circuiting or sealing up with mineral precipitation? We don’t have field proof yet at those conditions.
Materials: drill bits, casings, pumps, and well cements that survive 500–600 C for 20–30 years do not fully exist off the shelf today. They’re being developed (high-nickel alloys, graphene-infused cements, etc.), but it’s expensive and unproven at scale.
Induced seismicity near an active volcano is non-trivial. Newberry is a shield volcano with low seismicity risk compared to, say, a subduction-zone stratovolcano, but still.
Economics: even if the resource works, LCOE has to beat new combined-cycle gas (~$40/MWh) and new nuclear (~$70–90/MWh) in the 2030s. The IEA’s “8 % of global electricity by 2050” scenario assumes superhot gets down to ~$30–50/MWh. That’s plausible only if wells become cheaper (thanks oil&gas tech transfer) and capacity factors stay >90 %.

Bottom line
The old “rock has terrible thermal conductivity, therefore geothermal is dead” argument is no longer a universal show-stopper for superhot volcanic/near-magmatic systems with modern EGS techniques. The physics really does flip in your favor above ~400–450 C. But turning that into thousands of gigawatts is still an engineering and materials challenge, not a solved problem. Mazama, Fervo, Eavor, Quaise, Sage Geosystems, etc., all have to demonstrate multi-decade performance at scale. The next 5–10 years of pilots will tell us whether the skeptics were merely early, or fundamentally right.
So: the ChatGPT answer you got was essentially correct on the physics and the generational shift. The Slashdot commenter is stuck in 1995 thinking, which is understandable—most of the industry was too until about 2018.
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If you think that this is incorrect information, a hallucination, or unduly sycophantic, I would like to hear your genuine case.