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Ilya and David Chalmers, the same vibe.. "Anything which I can learn, anything which any one of you can learn, the AI could do as well. The reason is that all of us have a brain, and the brain is a biological computer. So why can't the digital computer,...

119,333 Aufrufe • vor 10 Monaten •via X (Twitter)

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.Naval: Every human is a lottery ticket bet on the future of the species. One of the things that you really learn when you read David Deutsch’s theories and you authenticate them for yourself is you realize humans are universal explainers. That means everything that we know in the universe follows the laws of physics, and there’s no reason to believe otherwise. If you think otherwise, then please present your better theory that explains the world. If you can’t do that, then you have to go with the laws of physics. Well, the laws of physics are completely computable. They can fit inside a Turing machine or computer, and a computer can simulate the laws of physics with arbitrary accuracy, limited only by the specific power of that computer. If you increase the power of that computer, you can simulate them more accurately. So humans already simulate—in our minds we simulate—and through our computers we simulate the weather, we simulate quasars, we even simulate human systems. We simulate the economy. We simulate all kinds of things. So anything that can be understood, we can understand in our minds. This is something the AGI people get wrong when they talk about superintelligence. There is nothing out there that can understand something fundamentally that we can’t understand. It might be faster at it, it might have more compute, it might have more memory, but there’s no concept that it can understand that we can’t ourselves understand. So we are maximal universal explainers. That means every human is capable of unbounded creativity. Anyone could be the next Einstein or Fermi or Elon Musk or Jeff Bezos or Jonas Salk or whatever. So we can create anything. And if we can create anything, every human is a lottery ticket bet on the future of the species.

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Geoffrey Hinton says one human sentence moves about 100 bits, while two machines can hand each other a billion: "The number of bits of information in a typical sentence is about 100 bits. So even if you understood me perfectly, when I produce a sentence, we can only transfer 100 bits." "If you take two digital agents running on different computers and one digital agent looks at one bit of the internet and decides how it would like to change its connection strengths, if they then both average their changes, they've transferred, well, if they've got a billion weights, they've transferred about a billion bits of information." "Notice that's thousands of times more than we do. And actually millions of times more than we do. And they do this very quickly." "And if you have 10,000 of these things, each one of these things can look at a different bit of the internet. They can each decide how they'd like to change their connection strengths, which started off all the same. They can then average all these changes together and send them out again." "Then you've got a thousand new, 10,000 new agents, each of which is benefited from the experience of all the other agents. So you've got 10,000 things that can all run in parallel. We can't do that. We can't do that." "Imagine how great it would be if you could take 10,000 students, each one could do a different course. As they're doing these courses, they could be averaging their connection strengths together. And by the time they're finished, even though each student only did one course, they would all know what's in all the courses." He's giving the clean textbook version here, and the mechanism is real. Averaging changes across copies is how you get one model out of thousands of machines. His own arithmetic is also where the trouble starts. When 10,000 copies fold their changes into one set of weights, what comes out is a sum. You can't run a sum backwards and ask which copy learned what, or which bit of the internet it read to learn it. A bank or a hospital asks that exact question before it signs anything off. What did this thing learn from? The speed Hinton is describing already shipped. Anything that can answer for what got learned is still years behind it. - Geoffrey Hinton, computer scientist and 2024 Nobel laureate in physics, at Hobart Town Hall (City of Hobart).

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