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Keeping in mind, this holds true in a runaway fashion if the only bottleneck to more intelligence is further intelligence. I suspect physical limitations similar to how many runaway processes in the universe are more logistical than exponential in nature.
The ultimate bottleneck is information a.k.a. training data. Nothing can learn with nothing to learn.
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How does it magically run away? What’s the process, we all talk about it “running away” leaving us “behind”, the exact practical process of that happening has not been laid out other than people hand wavingly copying apocalyptic movie scripts. Most ai experts just say it could end us, but suspiciously never gives a detailed plausible process and people suspicious just say oh yeah, it could, and there is a bubble over…
Since this is an LLM, keep in mind it probably injested those movie scripts as training data. The possibility of betrayal is inseparably linked to our popular conception of what AI is. This means it may be an inseparable part of any LLM behaving "as an AI" as defined by popular culture. It could be a self-fulfilling prophecy.
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How does it magically run away? What’s the process, we all talk about it “running away” leaving us “behind”, the exact practical process of that happening has not been laid out other than people hand wavingly copying apocalyptic movie scripts. Most ai experts just say it could end us, but suspiciously never gives a detailed plausible process and people suspicious just say oh yeah, it could, and there is a bubble over…
Yea, that’s what I want to know as well. How does a computer that can’t physically move destroy the human race? If it’s misbehaving, turn it off?
"""Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion,' and the intelligence of man would be left far behind... Thus the first ultraintellig…
We’ve seen the sort of output that LLMs produce, it can be good but also it just makes things up. So, this might produce good designs but ones that still need to be checked by a human in the end. This sort of thing just makes humans better, we’re still at the wheel. Or maybe it could be used as a heuristic to speed up something tedious like routing and layout (which, I don’t work in the space, but I’m under the impre…
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The entire field of chip-layout is considered an NP-complete problem. Any computer program trying to solve NP-complete problems is in the realm of what I call "1980s AI". Traveling salesman, knapsack, automated reasoning, verification, binary decision diagrams, etc. etc. Its "AI", but its not machine learning or LLMs or whatever kids these days do with Stable Diffusion.
There are plenty of researchers using machine learning for NP-complete problems. Are you saying that this work is fruitless or just that the current state of the art is still in “1980s AI” territory?
I guess in theory machine learning could take a swing at the problem. And sure, some professor out there is probably trying to mix the fields and find new solutions or something. But the bulk of the work, and problem-solving, is BDDs for a reason.
Or 3SAT-solvers, or... CSP solvers... etc. etc. Lots and lots of highly successful algorithms here. There's obviously open-questions for how to improve a CSP solver (faster, less RAM, more accurate estimations) and I've seen machine learning techniques applied before.
But the bulk of the methodology remains in whatever solver model you're going for. Even today.
Google has been using machine learning for chip design since at least 2021: https://www.nature.com/articles/s41586-021-03544-w Hasn't brought about the singularity yet.
This is one single step out of many in chip design for which they used machine learning. It will not produce anything revolutionary.
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A superintelligent AI won't be hacking computers, it will be hacking humans. Some combination of logical persuasion, bribery, blackmail, and threats of various types can control the behaviour of any human. Appeals to tribalism and paranoia will control most groups.
Citation please.
Page 15. GPT-4 is already capable of willingly lying to and manipulating people already to execute specific tasks.
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The title suggested to me, and I see other commenters here, that the LLM was doing the chip design which isn't the case at all. So misleading title.
I remember seeing a tweet from an AI guy at Nvidia saying they were using AI for chip layout. Presumably not LLMs and I’m not going back on X to find the tweet, but just to say I think they are doing this (at least experimentally).
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The ultimate bottleneck is information a.k.a. training data. Nothing can learn with nothing to learn.
This is what AI generated synthetic data and giving AI the ability to ‘dream’ is addressing.
At some point existing information has been fully digested. At that point you need new information. It isn't possible to extract infinite knowledge (or adaptation, a form of knowledge) from finite information.
Like I said: a brain in a vat can't learn. It can think about what it already knows, but it can't go further.
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This is what AI generated synthetic data and giving AI the ability to ‘dream’ is addressing.
That's just recycling and reprocessing data that's already there. It's part of inference and learning but isn't new information. At some point existing information has been fully digested. At that point you need new information. It isn't possible to extract infinite knowledge (or adaptation, a form of knowledge) from finite information. Like I said: a brain in a vat can't learn. It can think about what it already kno…
I agree it’s not new raw knowledge but that’s philosophical really. Given the rules, an AI can see every possible sequence of chess moves and identify which is the best counter. If a human can make the same move with less working memory we call it intelligence. Put a brain in a vat explain it the rules of chess and we can come out with something that beats Gary Kasparov, that’s pretty unexpected. The brain in a vat built an extraordinary ability from a simple set of knowledge. Now take that simple set of knowledge and expand it to all we know about the universe. The combinations of that knowledge is where we will see AI leaping past what we know.
AI given mathematical axioms is a already finding proofs that have long evaded mathematicians.