261–270 of 803 posts
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There's no reason it's intelligence should care about your goals though. the worry is creating a sociopathic (or weirder/worse) intelligence. Morality isn't derivable from first principles, it's a consequence of values.
Precisely. This is attempting to implement morality by constraining. Hence, it’s not morality.
"Super" intelligence typically refers to being better than humans in achieving goals, not to being better than humans in knowing good from evil.
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this is not evidence in favor of your position. We could use this to argue in favor of anything such as “humans will eventually develop time travel” or “we will have cost effective fusion power”. The fact is many things we’ve tried to develop for decades still don’t exist. Nothing is guaranteed
I'd put decent odds on a $1B research project developing time travel if time travel were an ability that every human child was innately born with. It's never easy to recreate what biology has done, but nature providing an "existence proof" goes a long way towards removing doubt about it being fundamentally possible.
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There is significant possibility that true AI (what Ilia calls superintelligence) is impossible to build using neural networks. So it is closer to some tokenbro project than to nuclear research. Or he will simply shift goalposts, and call some LLM superintelligent.
> There is significant possibility that true AI (what Ilia calls superintelligence) is impossible to build using neural networks What evidence can you provide to back up the statement of this "significant possibility"? Human brains use neural networks...
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> Closest thing we have to a Manhattan Project in the modern era? Minus the urgency, scientific process, well-defined goals, target dates, public ownership, accountability...
If public ownership means we give one guy a button to end the world, I'm not sure how's that's a meaningful difference.
Lots of comments either defending this ("it's taking a chance on being the first to build AGI with a proven team") or saying "it's a crazy valuation for a 3 month old startup". But both of these "sides" feel like they miss the mark to me. On one hand, I think it's great that investors are willing to throw big chunks of money at hard (or at least expensive) problems. I'm pretty sure all the investors putting money in…
Ilya has discussed this question: https://www.youtube.com/watch?v=YEUclZdj_Sc
On one hand, I understand what he's saying, and that's why I have been frustrated in the past when I've heard people say "it's just fancy autocomplete" without emphasizing the awesome capabilities that can give you. While I haven't seen this video by Sutskever before, I have seen a very similar argument by Hinton: in order to get really good at next token prediction, the model needs to "discover" the underlying rules that make that prediction possible.
All that said, I find his argument wholly unconvincing (and again, I may be waaaaay stupider than Sutskever, but there are other people much smarter than I who agree). And the reason for this is because every now and then I'll see a particular type of hallucination where it's pretty obvious that the LLM is confusing similar token strings even when their underlying meaning is very different. That is, the underlying "pattern matching" of LLMs becomes apparent in these situations.
As I said originally, I'm really glad VCs are pouring money into this, but I'd easily make a bet that in 5 years that LLMs will be nowhere near human-level intelligence on some tasks, especially where novel discovery is required.
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I'd put decent odds on a $1B research project developing time travel if time travel were an ability that every human child was innately born with. It's never easy to recreate what biology has done, but nature providing an "existence proof" goes a long way towards removing doubt about it being fundamentally possible.
Nature didn’t build intelligence with non biological activity. And we won’t either
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> Closest thing we have to a Manhattan Project in the modern era? Minus the urgency, scientific process, well-defined goals, target dates, public ownership, accountability...
If public ownership means we give one guy a button to end the world, I'm not sure how's that's a meaningful difference.
https://amp.cnn.com/cnn/2017/11/18/politics/air-force-genera...
Lots of comments either defending this ("it's taking a chance on being the first to build AGI with a proven team") or saying "it's a crazy valuation for a 3 month old startup". But both of these "sides" feel like they miss the mark to me. On one hand, I think it's great that investors are willing to throw big chunks of money at hard (or at least expensive) problems. I'm pretty sure all the investors putting money in…
The argument about AGI from LLMs is not based on the current state of LLMs, but on the rate of progress over the last 5+ years or so. It wasn't very long ago that almost nobody outside of a few niche circles seriously thought LLMs could do what they do right now. That said, my personal hypothesis is that AGI will emerge from video generation models rather than text generation models. A model that takes an arbitrary r…