Blaise Agüera y Arcas: evaluation

Transcript context

…going on. You can't have the spirit without the matter as it were. So function is really important and, and function is something that, you know, a rock on a non living planet, somewhere doesn't have. You know, if you if you break a rock on a non living planet, you now have 2 rocks. You don't have a broken rock. If you break a kidney, you now no longer have a working kidney. That's the difference between something functional and something non functional. This idea of function was formalized by Alan Turing, who never intended the Turing machine to actually be built, when he wrote it in 1936, but there is 1 that was built by Mike Davy in 2010. I don't need to review Turing machines with all of you, of course. You you all know how they how they work. But I do want to review briefly von Neumann's update to Turing's thinking about computation, which which he did a few years later. This was published posthumously after von Neumann died. But the idea behind behind von Neumann's thinking is he was trying to answer the same question that Schrodinger had quite had asked in his What is Life book? And in particular, he was trying to ask the question, if you have a robot that is swimming around, on a, you know, in a in a pond and the pond has lots of loose Legos around. There were no I don't know if there were Legos in 1950, but let's pretend there were Legos in 1950. And the job of the robot is to assemble those Legos into a new robot like itself. You know, there's something a little bit mysterious about that. It feels a little bit like pulling yourself up by your own bootstraps or like a paradox. And so he asked, what does it take for something to be able to make something like itself? Which seems, hard, almost paradoxical. And his conclusion was, well, you need to have instructions for how to make a mi. You need to have a tape with instructions for how to make a mi, and you need to have a universal constructor that will follow the, the instructions on that on that tape in order to assemble the necessary parts. You also need to have a tape copier, so that you can give your offspring, another copy of that tape. By the way, the tape has to also include the instructions for making the universal constructor and the tape copier. If those things all hold, then you have life. You have something that can build itself. And, what's what's so profound about about von Neumann's insight, I mean, first of all, he predicted all of this before we knew the structure and function of DNA, before we we understood what ribosomes were or discovered DNA polymerase. So he called it exactly right. Those all of those things really do exist, inside cells and he figured this out from pure theory, never having set foot in a bio lab. The the profound insight is that he said, by the way, a universal constructor is a universal Turing machine. Those are literally 1 and the same thing. And by by making that observation, what he discovered was that life is literally embodied computation. It is computational. You cannot have life without having computation. So obviously not everything that is alive reproduces, but everything that is alive has to be able to make itself. ied computation. It is computational. You cannot have life without having computation. So obviously not everything that is alive reproduces, but everything that is alive has to be able to make itself. It has to be able to do some combination of healing, growing, maintaining itself, reproducing. All of that is autopoiesis. All of that involves self construction and all of that necessarily involves a universal constructor. Now, what do I mean by embodied computation? This is a really important distinction between Von Neumann and Turing. In Turing, the symbols that the that the head writes are different from the head itself and the tape and, and the table of rules that the that the head follows. Whereas in von Neumann, it's it's more like a 3 d printer. The the memory is atoms, not abstract symbols. In other words, you know, you could think about a Turing machine as like this laptop, you know, which can't extrude another laptop out the side. But a von Neumann replicator is like a combination of a laptop and a 3 d printer that can print another laptop. So its memory is actually atoms. That's what I mean by embodied. So I don't mean embodied in the ways that a lot of roboticists talk about embodied. I mean that that there is a closure between the the medium in which the computation happens and the thing that is actually doing the computation. That's the key. So computation that is embodied in that sense and that is autopoietic is alive. You can't reproduce non trivially, evolvably without without computation. No computation, no life. I do wanna say a word briefly about what I mean by computation and in this I'm following the the work of, Susan Stepney, Dominic Horseman, Rob Wagner, Viv Kendon. This is from a nice paper they wrote in 2023 relating, the evolution of a physical system and the computation that it does. So, you know, on top you have logical gates, on the bottom you have, you know, transistors in your computer. This is important because, you know, there's there are no bits in a computer, there are just voltages that go up and down. In fact, even the voltages are an abstraction of something further, you know, if we go further down. But, you know, the the point is that you have to coarse grain those voltages into bits and then you have to have a logical machine that talks about how those bits evolve, what are the what are the what are the computational processes that those bits undergo, and there's a mapping from the physical system to the logical system and vice versa. When we say something computes, what we mean is that it is possible to construct such a mapping and that therefore as the physical system evolves, that is equivalent to the logical system evolving. So, you know, there are some caveats. You can have stochastic computation in which there's a little bit of randomness injected so it doesn't have to be fully deterministic. Another really important caveat is that you don't want that description to be infinitely complex. Otherwise, you could have the trivial case of saying like, you know, the water in the SEN is a computer and the longer my computation, I just need to make my description longer and longer in order to match. No. you could have the trivial case of saying like, you know, the water in the SEN is a computer and the longer my computation, I just need to make my description longer and longer in order to match. No. That doesn't work either. You need a kind of a Occam's razor, description that, for it to be valid. But this is a good definition of computation, but it emphasizes that there's something subjective about computation. You need to have a model for how the, how the physical system translates into the logical system in order for any of this stuff to work. There are implications about entropy, free energy and heat and so on in this model. And in particular, you as you all know, we've talked already, you know, Hector Zenil in his very elegant, talk of a couple of days ago talked about, and actually Chris Kempis also talked about the Landauer limit, and the fact that in a computational system you're constantly reducing the entropy of of your state space and in doing so you therefore require free energy. So, you know, you need to have free energy available and you need to eject waste heat. The exception in a way only proves the rule which is reversible computation. In reversible computation you generate ansyllabits and, and that's equivalent to just saying there's no exhaust But, you know, then you either have to keep on making your computer bigger and bigger and bigger as you accumulate these ancillibits or you have to, shrink what you consider to be the computer and then you're back to reversible to to non reversible computation once again. 3 important fallacies that I wanna point out before continuing. 1 of them I will call the Sapolsky Era. Robert Sapolsky, you know, has written famously about, people not having free will, because we're built on physical systems. You know, the physics is is, you know, if you like deterministic, let's set aside quantum mechanics and stuff like this. Let's imagine we live in a Newtonian universe. It's fine. It's good enough. The point is that physics is reversible. All of the basic physics that we understand, whether that's Newton's equations, Maxwell's equations, Einstein's equations, quantum mechanics, all of those are essentially time reversible. So you can move them either forward or back. Computation is not reversible. When I add, you know, 3 plus 5 to get 8, once I've got the 8, and I've, you know, haven't kept my ancillips around, let's say, I no longer know what was added in order to make the 8. Computation is inherently irreversible. And so to say that what is true of the physical system is also true of the of the computational system or the logical system is is not is not the case. And, reversibility would be 1 trivial example of how that is not the case. Causation, by the way, only makes sense in the light of irreversibility. Right? So if you have a purely physical system, then, you know, to say that a causes b is equivalent to saying that b causes because everything is kind of a block universe, you like, in that kind of setup. But in computation, you can talk about causality because there are ifs and thens in there.…

Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.