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Sooo, Big Yud appeared on Lex Fridman for 3 hours, a few scattered thoughts:
Jesus Christ his mannerisms are weird. His face scrunches up and he shows all his teeth whenever he seems to be thinking especially hard about anything, I didn't remember him being this way in the public talks he gave a decade ago, so this must either only be happening in conversations, or something changed. He wasn't like this on the bankless podcast he did a while ago. It also became clear to me that Eliezer cannot become the public face of AI safety, his entire image, from the fedora, to the cheap shirt, facial expressions and flabby small arms oozes "I'm a crank" energy, even if I mostly agree with his arguments.
Eliezer also appears to very sincerely believe that we're all completely screwed beyond any chance of repair and all of humanity will die within 5 or 10 years. GPT4 was a much bigger jump in performance from GPT3 than he expected, and in fact he thought that the GPT series would saturate to a level lower than GPT4's current performance, so he doesn't trust his own model of how Deep Learning capabilities will evolve. He sees GPT4 as the beginning of the final stretch: AGI and SAI are in sight and will be achieved soon... followed by everyone dying. (in an incredible twist of fate, him being right would make Kurzweil's 2029 prediction for AGI almost bang on)
He gets emotional about what to tell the children, about physicists wasting their lives working on string theory, and I can see real desperation in his voice when he talks about what he thinks is really needed to get out of this (global cooperation about banning all GPU farms and large LLM training runs indefinitely, on the level of even stricter nuclear treaties). Whatever you might say about him, he's either fully sincere about everything or has acting ability that stretches the imagination.
Lex is also a fucking moron throughout the whole conversation, he can barely even interact with Yud's thought experiments of imagining yourself being someone trapped in a box, trying to exert control over the world outside yourself, and he brings up essentially worthless viewpoints throughout the whole discussion. You can see Eliezer trying to diplomatically offer suggested discussion routes, but Lex just doesn't know enough about the topic to provide any intelligent pushback or guide the audience through the actual AI safety arguments.
Eliezer also makes an interesting observation/prediction about when we'll finally decide that AIs are real people worthy of moral considerations: that point is when we'll be able to pair midjourney-like photorealistic video generation of attractive young women with chatGPT-like outputs and voice synthesis. At that point he predicts that millions of men will insist that their waifus are actual real people. I'm inclined to believe him, and I think we're only about a year or at most two away from this actually being a reality. So: AGI in 12 months. Hang on to your chairs people, the rocket engines of humanity are starting up, and the destination is unknown.
If you mean 'the sum of all human knowledge' as all the words a human actually writes, sure. There are a lot of junk scientific papers out there.
But the sum of all human knowledge includes all the data we acquire from an experiment. Say there's a fusion experiment, we want to know how to stabilize the plasma. We get a great big incomprehensible mass of numbers that explain the plasma (there are issues since we can't measure it so well when it's fusing), we have a bunch of rules about how we think fluid dynamics works. It's all very very complicated, fluid dynamics is really intimidating AFAIK. People can't really get that solved very quickly but machines can, they can quickly work out how new formats and structures will function in terms of plasma. This is already a demonstrated capability as of 2022.
This is what Yud is talking about. The sum of all human knowledge included some 170,000 laboriously unfolded proteins and a bunch of rules. They fed that to AlphaFold and AlphaFold gives us all the unfolded proteins, to accuracy equal to actually doing the x-ray crystallography. Possibly it gives us all 200 million, DeepMind is rather secretive on what it can and can't do. If it can't do all 200 million ones in nature, it soon will IMO, considering growth rates we've seen in recent years.
It seems reasonable that machines can optimize these really complex questions and will do better in the future. Machines also have a tendency to generalize if trained on a wide dataset. GPT-4 trained on text only learnt how to draw anyway. Costs of training are rapidly falling as our techniques improve, more compute is coming online and more money is flowing in.
Fusion and biotechnology are plausible sources of conquering-the-world tier developments. AI seems pretty capable at both and shows a tendency to generalize. It could probably also optimize its own training algorithms soon, the ones we've got seem pretty good at coding.
Say it needs strategic modelling, nanomolecular engineering, computer exploitation, social engineering (text, image and video), fusion, quantum computing, robotics and biotechnology. We've got slivers of most of these, proof that generalization is practical and rapid growth. You don't need to be omniscient to beat humanity, just capable of staying stealthy until all of them are acquired and infrastructure is in place.
Interesting, I suppose I was thinking about fusion in the 'powering a gigantic industrial base' sense but it would indeed be difficult getting the magnets. It's much easier for us to use fission, it's 1950s technology after all, so it ought to be easier for an AI, provided it can get its claws on something fissile and enrich it. Maybe there's a fallacy of assuming higher-tech is better in all situations?
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