You could imagine that pre-diagnosis confusion relating to Alzheimer's increases the risk of traffic accident and kills taxi drivers, too. Might not operate for truckers as much because they're more likely to survive accidents.
The US's population is not declining. However, without immigration, our population growth would be very close to zero, and a yet lower rate of natural increase is locked in over the next couple of decades (more old people who will die than children).
And, I mean, it's obviously hard to predict beyond that, but it doesn't seem like anyone has any real clear answer to the trend of steadily decreasing TFR right now.
I mean, he was pretty vindicated on Uber. Which kind of hurts me to say, I was a long time Uber bear. But it did indeed emerge from the pandemic stronger.
Quick Google suggests Uber is up 66% on its IPO price, but the S&P index is up 85% over the same time period. I think Softbank also sold out around 2022, so the return (vs IPO price) would have been even lower. Didn't check for stock splits etc but I don't think Uber was a home-run for Softbank at all.
WTF do you mean by this? Even constitutions can be amended, and if an odious law cannot be changed through politics then that only means it will be changed by other means.
I think in most countries the drivers get paid by the taxi license holders and usually can make more money and/or more have more flexible working conditions driving for Uber.
No, their customers revolted. If a business based on "Get in cars with random strangers" beats you in the marketplace, your business model sucks and chances are good that you do, too. That's the taxi industry in a nutshell.
You're confusing the training method with the internal process. If I had you repeatedly attempt to learn how to make believable completions of partial documents about a given topic, you would eventually learn things about that topic and could use your knowledge to create more believable completions of documents about that topic.
They do learn in context, and very sample efficiently. Continual learning is active area of research and we sort of already have something resembling it with persistent context. So yes they do learn.
Thank you for saying succinctly what I could not. If your consciousness and knowledge fundamentally does not change from your ongoing experience, then you are not learning. This is how the LLM currently functions.
You’re describing the problem of continual learning. As I said their “consciousness” for lack of a better term and knowledge does already change from ongoing experience in context which is another of saying for only a short window, today. They are ephemeral, sort of, but that’s a temporary limitation.
I think if your definition of consciousness can fit these things then you’re more open minded than I care to be. Consciousness isn’t really guessing the next thing to say- it’s hard to say what it is, obviously, but blindly feeling forwards with each new conversation doesn’t seem like consciousness or learning to me.
We aren't talking about consciousness, we're talking about learning.
> Consciousness isn’t really guessing the next thing to say-
I don't know what consciousness is either and these debates are a dumpster fire when they happen, but it sounds like you're pulling forward this "LLMs are just predicting the next token" (true by construction) implies that they can't learn or reason or be conscious (2/3 are wrong, the last one isn't falsifiable without a useful definition).
Yes, I think we simply disagree. I think you know what LLMs are based on our other thread and if you think something important happens when you get a large enough context vector I don’t think there’s much I can say to change your mind. It seems unlikely to me!
“They don’t understand” is a strong statement, maybe true but depends on what you mean by understand. What is your definition of this? I can’t think of a meaningful definition of “understand” that doesn’t apply to LLMs
The LLM itself doesn't, but agents can research, compare, add to their memory, and use that to narrow the results down to a probabilistically higher set of outputs; I have used an LLM for my own MRI results and it was nearly spot-on, verified by a subsequent visit to a specialist. YMMV as they say. But I do believe we are entering the era where LLMs are considering past interactions and long context windows to inform it of personal preferences and history in order to output more accurate results.
A very important callout. It's the crux of the whole thing really. Humans are easily susceptible to deception by statements that are structured to be believable.
It'd be interesting to try to imagine a Venusian colonization that's like two separated levels: an atmospheric area where most people live and where you grow food, and then a subterranean (yes, yes, sub... aphroditean?) where you mine and so forth, and there are brief, fraught transitions between the two layers but no actual habitation of the surface or lower atmosphere.
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