No. It can't be properly expressive without understanding the story that it's reading. Punctuation is just not enough, it doesn't capture many different shades of meaning. E.g., an ironic statement should be read in a different tone than a factual statement, even with exactly the same punctuation. (That's one example out of MANY. Consider, e.g., the scene in "Alice in Wonderland" where she's talking about jumping off the top of the house.)

Well, I *do* want an "AI PC", but not anything currently on the market. I want one that will understand books in HTML format and read them to me in a reasonably expressive tone. I'd also like it to be able to pause and then answer questions about what was going on earlier if I missed a point.
OTOH, I'd also want it to be strictly segregated from most of what I do.

That's the way the internet works on land these days, over any distance. Your multiple carriers all turn out to depend on the same infrastructure.

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..

I don't think you understand the process of science. That is the appropriate reaction to any initial claim. An initial observation needs to be repeated by others, and the data that justified the initial claim should be reanalyzed by others to see if they agree with the interpretation. Then arguments ensue. Eventually people "pretty much" come to an agreement.

Sometimes the arguments last for decades.

It also suggests that as time goes by, dark matter will decay into normal matter (photons). Rather slowly, however.

Apparently you'll need to be able to see gamma rays to be able to see it.

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.

I'm not saying any particular person said that, and the question to Slashdot was asked over 2 decades ago. But I was assured that SSDs were "now reliable as an archival store", despite my informal test failure. (I had backed up something to them, and stuck them in a drawer for perhaps a year. They became unreadable.)

My sample size was small (just a couple), but it decided me not to trust SSDs for backup even though everyone on Slashdot said I should trust them. What I'm afraid is that portable USB drives will start being main with SSDs rather than spinning rust without bothering to tell me.

Not a good idea, but you could try paper tape.

Without knowing precisely how Explorer is structured, it's conceivable that there may be different dynamically-linked libraries and/or execution points for running the desktop and for the file explorer, in which case just having explorer.exe running in and of itself doesn't mean that new modules have to be loaded if explorer.exe process fires up. The solution could very well be to load the libraries involved in file browsing when the desktop opens.

Just guessing here. There was a time when there was a lot more horsepower required for GUI elements than folder browsing, but this is 2025, and explorer.exe probably uses orders of a magnitude more resources now than it did in 1995, because... well, who knows really. Probably to sell more ads and load up more data to their AI.