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S1: A $6 R1 competitor?

(timkellogg.me)
851 points tkellogg | 1 comments | | HN request time: 0.21s | source
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yapyap ◴[] No.42947816[source]
> If you believe that AI development is a prime national security advantage, then you absolutely should want even more money poured into AI development, to make it go even faster.

This, this is the problem for me with people deep in AI. They think it’s the end all be all for everything. They have the vision of the ‘AI’ they’ve seen in movies in mind, see the current ‘AI’ being used and to them it’s basically almost the same, their brain is mental bridging the concepts and saying it’s only a matter of time.

To me, that’s stupid. I observe the more populist and socially appealing CEOs of these VC startups (Sam Altman being the biggest, of course.) just straight up lying to the masses, for financial gain, of course.

Real AI, artificial intelligence, is a fever dream. This is machine learning except the machines are bigger than ever before. There is no intellect.

and the enthusiasm of these people that are into it feeds into those who aren’t aware of it in the slightest, they see you can chat with a ‘robot’, they hear all this hype from their peers and they buy into it. We are social creatures after all.

I think using any of this in a national security setting is stupid, wasteful and very, very insecure.

Hell, if you really care about being ahead, pour 500 billion dollars into quantum computing so u can try to break current encryption. That’ll get you so much further than this nonsensical bs.

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1. robwwilliams ◴[] No.42948458[source]
It used to be much easier to be conservative about AI, especially AGI, after living through three cycles of AI winters. No more. Dismissing it as “merely machine learning” is worse than unfair to the last decade of machine learning ;-)

The hard part now is relatively trivial. Does anyone think that there is a fundamental and profound discovery that evolution made purely by selection in the last 200,000 years? I mean a true qualitative difference?

Sure—-We call it language, which is just another part of a fancy animal’s tool kit.

Does anyone think there is an amazing qualitative difference between the brain of a chimp and the brain of a human?

No, not if they know any biology.

(Although that does not stop some scientist from looking for a “language gene” like FOXP2.)

So what did dumb mutations and 200,000 years of selection do that a group of dedicated AI scientists cannot do with their own genuine general intelligence?

Nothing—-nothing other than putting a compact energy efficient LLM with reinforcement learning on a good robotic body and letting it explore and learn like we did as infants, toddlers and teenagers.

Each one of us has experienced becoming a “general intelligence”. I remember it hit me on the head in 6th grade when I dreamed up a different way of doing long division. I remember thinking: “How did I think that?” And each one of us who has watched an infant turn into a toddler has watched it as an observer or teacher. This is what makes babies so fascinating to “play” with.

We have to give our baby AGI a private memory and a layer of meta-attention like we all gain as we mature, love, and struggle.

I read the linked article and as a neuroscientist I realized the “wait” cycles that improved performance so much is roughly equivalent to the prefrontal cortex: the part of the CNS most responsible for enabling us to check our own reasoning recursively. Delay—as in delayed gratification—-is a key attribute of intelligent systems.

We are finally on the door step to Hofstadter’s Strange Loop and Maturana’s and Valera’s “enactive” systems, but now implemented in silicon, metal, and plastic by us rather than dumb but very patient natural selection.

Karl Friston and Demis Hassabis (two very smart neuroscientist) figured this out years ago. And they were preceded by three other world class neuroscientist: Humberto Maturana, Francisco Valera, and Rich Sutton (honorary neuroscientist). And big credit to Terry Winograd for presaging this path forward long ago too.