851–860 of 936 posts
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They “deploy” much more than what they generate. Their cash position has gone from $44bn to $12bn in the first six months of the year and are now getting other people to pay for datacenters https://www.reuters.com/business/meta-taps-pimco-blue-owl-29...
I take offense to your implication this is an incorrect usage of the word deploy.
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Indeed, for big valley tech companies it's crucial to have a new business developing in the wings which has plausible potential to be the "next big thing." They're desperate to keep their stock price from being evaluated solely on trailing twelve month revenue, so having a shiny, ephemeral hype-magnet to attract inflated growth expectations is essential. So far, it appears the psychology of investors allows the new t…
> as long as there's a new new thing to replace it as the aspirational vehicle. Like any good mark in a con game, tech investors want to believe. Yea, but it seems like the new new thing needs to get progressively bigger with each cycle, which is why I think the shell game is almost over. They really can't overpromise much more than they did with the AI hype-cycle. It feels like a startup valuation in that having a d…
While I agree that "replace all human labor" is already pretty high up there on the overreaching u/dis-topian promise list, there are still a few things left.
Perhaps the next dream to sell will be digitizing the minds of Valued Shareholders so that they can grasp immortality inside the computer.
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Could you explain your claim that ANNs are nothing like real neural networks beyond their initial inspiration (if you'll accept my paraphrasing). I've seen it a few times on HN, and I'm not sure what people mean by it. By my very limited understanding of neural biology, neurons activate according to inputs that are mostly activations of other neurons. A dot product of weights and inputs (i.e. one part of matrix multi…
Neurons don't just work on electrical potentials, they also have a multiple whole systems of neurotransmitters that affect their operation. So I don't think their activation is a continuous function. Although I suppose we could use non-continuous functions for activations in a NN, I don't think there's an easy way to train a NN that does that.
If you really wanted to train artificial spiking neural networks in biologically plausible fashion then you'd first need to discover/guess what that learning algorithm is, which is something that has escaped us so far. Hebbian "fire together, wire together" may be part of it, but we certainly don't have the full picture.
OTOH, it's not yet apparent whether an ANN design that more closely follows real neurons has any benefit in terms of overall function, although an async dataflow design would be a lot more efficient in terms of power usage.
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This is why I ignore anything that CEOs say about AI in the news. Examples, AGI in a few years, most jobs will be obsolete, etc.
CEO's were never credible to begin with, but what about Nobel laureate in Physics, Geoffrey Hinton, telling us to stop training radiologists? Nothing makes sense anymore.
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Between “presumes a solid grasp of which things out there are not fraud besides those which are coercion, but that's not a subject I'm interested in having an opinion about,” before going on and sharing an opinion on that subject, and “even the Invisible Hand of the market is hand-shaped,” I think it may just be AI slop.
Literacy barrier. One of the reason the invisible foot of the market decided to walk in the direction of language machines is to discourage people from playing with language, because that's doodoo.
> One of the reason
I could see that, thanks for explaining why you do this.
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CEO's were never credible to begin with, but what about Nobel laureate in Physics, Geoffrey Hinton, telling us to stop training radiologists? Nothing makes sense anymore.
Well, clearly he should stick to physics. Even if it's likely that AI would replace them soon, a lot of people would likely die unnecessarily if we ran overly low on radiologists by ending the pipeline too soon. They're already overworked and that can only go so far. It's not a bet we should make.
While his Nobel prize was for "physics", his domain is AI.
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Scaling AI will require an exponential increase in compute and processing power, A small quibble... I'd say that's true only if you accept as an axiom that current approaches to AI are "the" approach and reject the possibility of radical algorithmic advances that completely change the game. For my part, I have a strongly held belief that there is such an algorithmic advancement "out there" waiting to be discovered, t…
If we suppose that ANNs are more or less accurate models of real neural networks, the reason why they're so inefficient is not algorithmic, but purely architectural. They're just software. We have these huge tables of numbers and we're trying to squeeze them as hard as possible through a relatively small number of multipliers and adders. Meanwhile, a brain can perform a trillion fundamental simultaneously because eve…
You could certainly implement an async dataflow type design in software, although maybe not as power efficiently as with custom silicon, but individual ANN node throughput performance would suffer given the need to aggregate neurons needing updates into a group to be fed into one the large matrix multiplies that today's hardware is optimized for, although sparse operations are also a possibility. OTOH conceivably one could save enough FLOPs that it'd still be a win in terms of how fast an input could be processed through an entire neural net.
Nothing would give me a nicer feeling of schadenfreude than to see Meta, Google, and these other frothing-at-the-mouth AI hucksters take a bath on their bets.
Why would that give you a nice feeling?
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Ability vastly increases your luck surface area. A single poker hand has a lot of luck, and even a game, but over long periods, ability starts to strongly differentiate peoples' results.
Except you can play hundreds of thousands of poker hands in your lifetime, but only have time/energy/money to start a handful of businesses.
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Except you can play hundreds of thousands of poker hands in your lifetime, but only have time/energy/money to start a handful of businesses.
Sure, but within running a single business, there are a huge number of individual events. Those are the hands.
The main reason why professional poker players are playing the long-game, is because they're consistently playing the same game. Over and over.