Future of Science and Technology Q&A (September 15, 2023)

Hello, everyone. Welcome to another episode of Q and A about the future of science and technology. I had a gap for a couple of sessions here. I was away, but I'm back now. All right, question here about from des. Would an alien intelligence experiencing a different slice of the ruliad a ruster? I don't know quite what that means. Close to ours, likely experience black holes in a similar way? That's an interesting question. All right, so let's set some framework for this. So one of the big, sort of the deepest part of the rabbit hole that came from our physics project is this object we call the ruliad. And if we start thinking about how do we define what's happening in physics, one of the implications of our physics project is there's ultimately a computational rule that when run for long enough, reproduces everything that happens in our universe. But then the question is, why one rule and not another? And so what we realized is, well, actually, one can think about the universe as running all possible rules, and that's represented by this thing we call a ruliad, where you start from all possible initial conditions and you're running all possible computational rules, and you're seeing all the possible consequences. And the key fact is that even when there are sort of two separate states that are generated by different rules, those two states can converge again, because when they each have the appropriate rules applied to them, they could kind of collide and end up producing the same state further on. So this ruliad object has, if you trace sort of the states and this rule, the evolution of states in this ruliad object, you'll see a bunch of branching and a bunch of merging. It's a very complicated kind of assembly of things. So the thing that. So that's the ruliad object. Now, the key point is that we are somehow embedded in this ruliad object. So we experience the universe. Our perception of what's going on in the universe is based on us sampling sort of our piece of the ruliad that represents us sampling the ruliad, so to speak. And each of us, each kind of mind, in a sense, has some internal collection of states that it sort of that are its experience as defined as a part of the ruliad. And different minds have different sequences of states that they experience, because, in a sense, different minds are at different places in the ruliad. Different minds are at different places in real space. And so even between different human minds, we're all at different places in real space. So if you were to look at the Even at the sort of individual nerve firings inside our brains. They'd, in detail, be different. The thing that is surprising and remarkable Is that there's enough sort of commonality that we can communicate. Talk about sort of shared experiences and so on. And even though the details of what's happening inside our brains is different from each of us. And there's this kind of idea that there is this communication process. This fact that we can use language, for example. We can package up those detailed sort of internal thoughts that we have. Into concepts that we can represent, for example, as words. And we can then take one of those words, communicate them to somebody else. They can unpack that word into their own internal kind of neural firings and so on. So this idea, and I've talked about this before, this idea that kind of concepts are the thing that you can transport from one place in real space to another. Concepts, I think, are like particles in physical space. Like things like electrons represent some way that you can communicate stuff. You can think of it as information from one place in the universe to another. And sort of have something kind of propagate without change. Have kind of pure motion from one place to another. And I think that's what's kind of happening in rural space. With concepts and words and so on. So now the question is, what would be in common in the experiences of minds at different places in rural space? Observers at different places in rural space? Potentially there are between different sort of. You can kind of measure the distance in rulial space. It's kind of how aligned are the concepts. How much translation is necessary to go from one set of internal states of one mind to the internal states of another. So, for example, between different humans. Well, depending on how similar the kind of educational, cultural, et cetera, backgrounds are. That they can be quite close or much further away in rulial space. Or when we go to things like animals, we're further away in rural space. We can have some sort of emotional kind of connection to the animals. That's something that isn't described so much in words. But it's described in a kind of a universal language of emotion. So to speak of whether it's the human facial expressions or the dog facial expressions. We don't have tails to wag. But at least the facial expressions have kind of a kind of significant commonality. Between humans and, for example, other mammals and so on. Actually, it's an interesting question. Whether that facial expression commonality extends beyond mammals. I don't know. I haven't seen a lot of facial Expression on the part of lizards, let's say. Or certainly Charles Darwin, in fact, had even a book, I think Expression of Emotions in Animals and Man was one of his last publications in which he was trying to trace this commonality. I think only for mammals, now that I think about it. But in any case. So it's kind of further in rulial space to get to a fish. But now the question is, are there concepts which all of those sort of critters, all of those minds agree on? Interesting question. And are black holes, for example, a concept? Now, your average person hasn't encountered a black hole, perhaps. Fortunately, your average fish has definitely not encountered a black hole. So the question is, is there some feature, I think ordinary. Okay, so what is a black hole? Black hole is a place where sort of information can go in but can't come out. It has an event horizon where kind of all those things, whether they're particles, concepts, whatever else, they can go in, but they can't come out. As we look at the sort of time evolution of a black hole. Things are falling into the black hole but not coming out of the black hole. There's kind of irreversible kind of falling in but not coming out, so to speak. That's happening now. It gets more subtle when you go into quantum gravity and so on. But let's not go there for right now. So in our models, the case of a physical black hole is something we can see in the causal graph of. Of space time. So causal graph is there are lots of elementary events that are happening. And in our models, these are rewrite rules for the hypergraphs that represent the state of the universe. There are all these rewrites happening. And we can say what are the causal connections between these rewrite events. So, for example, one rewrite event might require that other rewrite events have already happened. Or it doesn't have the inputs that it needs for that next rewrite event to occur. So there's this causal graph that represents the causal connections between all the rewrite events. And what's happening in a black hole is that there's a region of the graph of space where there are causal edges that are going into that region. There's causation from the outside to the inside. But there's no causal edges coming out from the inside of a black hole to the outside. So that's kind of the definition of a black hole. And that in the case of physical space, we're just imagining as this region of physical space. Okay, so now we can get more exotic with branchial space, the space of quantum branches. But right now let's talk about rulial space and we can talk about sort of a black hole in rulial space. We can talk about the perception of an ordinary black hole. Let me think about that for a second. I do suspect. Let me think about that for a second. No, it's a little bit more complicated because the way the black hole is produced, the way the causal graph is produced, depends on the rules that you're using for describing the universe. So if you use different rules, you will get a different causal graph and you will get different structure of the black hole. That even happens in the case of quantum mechanics. You take kind of different branches of history, you can get different structures for the black hole. And that can lead you to all kinds of issues that show up as sort of paradoxes in traditional quantum mechanics, meeting gravitation theory and so on. So I think it isn't the case that the sort of the black hole is a constant across different from different points in real space. You might perceive a black hole differently. So I don't think that there's any particular necessary commonality between what's a black hole to one sort of mind might not be a black hole to another mind, because in a sense they are describing the universe differently. And that means that they have a different set of events that they're thinking happened, so to speak, in the universe. So I think there isn't commonality there. Now, an interesting question is what's the analog of a black hole in rulial space? That's a place where one can kind of over the course of time, there are sort of, in a sense, One is sort of having these concepts that go in but don't come out somehow. That's kind of the analogy of. Yeah, that's kind of the analog of a black hole where particles fall into the black hole but don't come out. So in the case of ruial space, what will be happening is concepts will be going into that region of ruial space, but won't be coming out. And I think that corresponds to, in mathematics, that would correspond to a decidable theory, one where kind of in the end, any question you ask has a definite answer and you say, boom, we've answered the question, we're done. As opposed to something where there are undecidable propositions where you can be sort of trying to prove what's happening and there's an infinite path. That's kind of the analog of you could be wandering around in physical space for an infinite time, or you can be sort of trapped inside the event horizon or black hole and time is of limited duration for you, and. And eventually you get sort of crushed at the singularity of the black hole. So in a sense, the analog in rulial space is. Is it something where you can sort of answer every question, or is it something where you keep on having sort of. Where you. Where you keep on having to wonder what the answer to the questions is? So in a sense, it's kind of a thing where there's an area of knowledge. We can just say, this area of knowledge is finished. Everything you might ask about this area of knowledge, boom, you can get the answer. As opposed to, this is something where you have to keep trying to work things out. And it's kind of a computationally irreducible process where you say, I wonder what happens in this case. I wonder what happens if we go further. I wonder what happens if we go further. The kind of rulial black hole is the place where sort of knowledge is finished in that area, in that way of thinking about the world, that sort of region of knowledge is all worked out. There's nothing more to say. It's sort of time ends for that type of knowledge. I think that's the kind of the analog of this in real space. A bit abstract, I have to say. This is complicated. Let's see. Let me just take a few of these later questions that just came in and then let me come back to some other things. So Brady asks, is rulial space bigger than branchial space? Yes, much, much, much bigger. So branchial space is what happens when you have these hypergraphs and you're rewriting things and there are different possible paths of rewriting with a given rule. Rulial space is. You look at all possible rules, and so that is vastly bigger. Like one might be, I don't know, 10 to the. In our universe might be, you know, of size, the number of quantum branches might be maybe. I don't know. I had an estimate of maybe 10 to the 120, but I'm not sure if it's right. Might be much larger than that. But compared to that, the size of rulial space is more like 10 to the 10 to the 500. So unbelievably, exponentially larger. And it is amazing what a small fraction of rulial space we have explored. I looked at this thing with generative AI, where one's looking at what of the possible things that one can generate with generative AI and that's generative AI that's already been trained from things like human images. There are places in the space of possible things you can generate that correspond to recognizable things like cats and dogs. And there's a huge inter concept space. And even in the rather simple case, I was looking at the region of interconcept space, so to speak, analogous to interstellar space, I suppose the region of interconcept space that we have so far explored, that we so far have words for, have a description in our language, is 10 to the minus 600. So we have explored an absolutely microscopic fraction of the space of all possible concepts. And that's just concepts which are kind of derived from things that come from pictures that we put on the web. So when we go beyond that, it's probably more like 10 to the 10 to the 500, 10 to the 10 to the 600, something like this. And we have, you know, it's 10 to the minus 10 to the 600 or something. That's the fraction of the ruliad that we have so far explored. So there's a lot more about sort of how we might experience the universe that we could explore, but we have not at this time. So Don comments. Maybe it's a Gaussian distribution around a point in royal space that makes human minds, I mean, human minds are. We all have a certain, in a sense, diversity of points of view. We are not requiring. We have a certain uncertainty about the rules of the universe, and we operate with a certain amount of uncertainty about the rules of the universe. And that's kind of our extent in rulial space is that uncertainty. See, one of the things one could think about is one of the key ideas in science is the idea of scientific induction. The idea once you've seen certain things happen, can you deduce that other things will happen in a certain way? Can you take a certain amount of evidence and derive from that a definite law of the universe which you can then apply in the future? So in a sense, our extent in rulial space gives a sense of the extent to which we can't figure out. We have only as limited amount of information to figure out the laws of the universe. And we are uncertain to some extent about the laws of the universe. We don't have as much data as we need to be able to nail down. It's got to be this law and not another. And in a sense, if we could be sort of infinitesimally small points in rural space, we will be nailing down. It's this law for the universe and not others. So in a sense, our fuzziness in rural space is an ultimate limit on the process of scientific induction. I mean, that's a fairly complicated sort of way of thinking about it, but that's kind of a way to think about it. And this whole question about sort of how extended are we in these different kinds of space, it's kind of an interesting thing. In physical space, the universe is 10 to the 26 meters across we are, give or take a meter tall. And the elementary length, the shortest possible distance, the size of elements of the hypergraph might be 10 to the minus 100 meters, 10 to the minus 80 meters. I don't know. Those are only very rough estimates. But that means that we are pretty big compared to the atoms of space, so to speak. We're pretty big compared to the elementary length relative to the size of the universe. So it might be 80 orders of magnitude below us and 26 orders of magnitude above us. So we're pretty big in that respect. In branchial space, I don't know exactly how big we are. The extent to which we are our size in branchial space characterizes the extent to which we don't see quantum mechanics in the sense that the bigger we are in branchial space, the more we are sort of averaging things out and we don't see kind of the weird effects of quantum mechanics. So in a sense, I think the observation of quantum mechanics, it limits our size in branchial space, But I think in rulial space. So I don't know how big we are in branch of space. I've done a few estimates of this, but I don't really know the answer to that. In rural space. We're really, really tiny. I mean, our minds extend not very far at all in rural space. And so it's kind of like there's a certain distance we've got to explore with our spacecraft, so to speak. We're not going to get to the edge of the universe because that would take the the lifetime of the universe to get to. But we're not going to get that far. But we could send out spacecraft, but there's much less far to go than there is distance to go in the ruliad. Exploring sort of different paradigms. So in a sense, if we say, are we going to build spacecraft and go out into space, or are we going to sort of explore the purely intellectual paradigms? There's vastly more to explore in sort of the purely intellectual paradigms than there is in looking at pieces of physical Space. All right, let's see. Well, I've got many questions here. Right, I'll take one that just came in from Harry. What do you think about NASA's recently released plans to build a moon based radio telescope? I've been kind of hearing about this for ages. But you know, if you put a telescope on the far side of the moon, then doesn't have any radio interference from the earth and that's a good thing. I mean, right now there are places like Green Bank, West Virginia where cell phones are banned and that gives the radio telescope a better chance to operate. But basically right now on the Earth, it's just full of radio energy that we're using for all kinds of communications, kinds of mechanisms. And I think that the, the thing that is certainly going to be the case as we get to 5G telecommunications, things like this, it's really quite inefficient. If you are trying to communicate from device A to device B. And you do that by having kind of radio energy go out in all directions from device A and just some of those directions happen to reach device B. That's kind of an inefficient way to do things. And in a sort of perfect world, and that's what's getting closer. In 5G, one is kind of arranging the radio energy so that it's actually concentrated more in some kind of beam that gets to the device one's trying to get to. If that continues, then one's really, instead of having, in the first approximation, you can communicate by sending data through wires where there's a definite wire and it goes through that copper wire, it goes through that piece of fiber optics, never gets out of the wire. But now in free space, when you're using radio communication, for example, the most generic way to do that is to have an antenna that basically puts energy out in all directions. And then the device that's picking it up picks up just the tiny fraction of that energy that happens to go in its direction. Now, as you make phased arrays, for example, where you have many different antennas and they're producing radio energy with different phase relationships so that you kind of form the beam so it goes in a particular direction, then you can have something much more efficient until eventually you're at the point where it's essentially wires in space, where essentially the radio energy is all concentrated in something that is a very definite beam. Kind of like a laser, for example, concentrates light, at least to a decent extent. Laser beams do spread out. You shoot a laser from the Earth to the moon it's several kilometers wide by the time it gets to the moon, even with the best laser cavities. But in the case where. So this problem of having radio energy that's sort of directed in sort of wires in space is something we will get closer and closer to, and it'll be sort of more and more equivalent to having the data just go through sort of wires, you know, explicit wires. Now, an interesting question is whether when you get to kind of the infrared light that is used for fiber optics, maybe it's even visible light sometimes I'm not sure. But that because light, typical radio waves may be a few gigahertz, a few billion cycles per second, that allows you to get data ray transmit data by radio at the rate of a few billion bits per second. In the case of fiber light, that's a few trillion bits per second. So there's significantly more information can be sent with light. And you can even add more than that because of the way that you can multiplex signals onto fibers and so on. But in any case, and to some extent, you can do that in radio as well. But the basic point is an interesting question is right now we imagine that in free space transmission of things, it's just radio. But one could also imagine, and certainly one does this on a limited extent, one could imagine doing that with making phased array type things with infrared. I think that's something that is not possible yet. But one can imagine that becoming possible. And then you can kind of have sort of wires that are of higher frequency energy. And the distinction between sending something through a wire and sending something through free space will tend to disappear. Now, of course, the problem with sending something, if you have a wire, you kind of know it's going to be able to go from place A to place B, because you've got that physical wire that is going from place A to place B. If it's in free space, then if you happen to put an obstruction between the source and the receiver, then, oops, you're blocking that transmission. But the whole point is that when it is kind of a soft thing that's computing that that's working out where the beams actually go, you can end up with all kinds of elaborate things where, oh, somebody walked in the way. That means that the phased array should change its transmission, send it in a different path, et cetera, et cetera, et cetera, use the fact that it's going to bounce off some other object and so on, and be able to adapt in real time, which is what happens in 5G. And so on, let's see. All right, well, there was a question about the moon based radio telescope. Yeah, I mean it seems like a good idea to me. I mean the moon's a very peaceful place where there are no where you don't have to fight with anybody at least right now to sort of make a big thing that put big thing all over the far side of the Moon. You probably have some great long baseline interferometry of different receiving points in different places. It's obviously more of a nuisance to get things to the moon, but once it's there, it seems like a fine place to operate a radio telescope. I don't really know. I mean it really helps that the moon, the far side of the moon is shadowed relative to the Earth. And so the radio transmissions from the Earth just don't go there. And that really helps if you're in, out in. I mean, if you go far enough away from the Earth, well, you'll be away from all radio transmissions on the Earth. So you can have radio telescope like things that are in free space, so to speak. Certainly. For example, gravitational wave detectors. There's a plan to have a satellite based gravitational wave detector that has a bunch of satellites that are sort of knowing how far apart they are by exchanging laser signals. And when a gravitational wave comes through, it distorts the structure of space. And the effective distance apart between these satellites will change even though it will be known what their orbits are. So it'll be known how far apart they're supposed to be. But when a gravitational wave comes through, oops, they'll effectively be further apart because the structure of space has changed and that's going to be detectable. The question is what's going to be done on the Moon? And it's always a question. People say, let's go to the moon. It's interesting, it's impressive to go to the Moon and we learn a certain amount about things about the history of the Earth. For example, because the moon has been very untouched relative to the Earth with its atmosphere and so on. So we get to see every piece of rock was probably an initial piece of rock that's always been on the Moon, that's always been sort of exposed. There's but the question of how do we make use of the Moon? The thing I'm hearing most recently is let's put heavy industry on the Moon. If we've got all sorts of things that produce all kinds of pollutants or whatever else, let's not put those into the Earth's Atmosphere, let's kind of vent them out into empty space from the Moon. So that's been kind of the ultimate outsourcing location. Maybe not ultimate, but the next major sort of outsourcing location. Put the heavy industry on the Moon. I don't know how realistic it is. I think it's actually not unlikely that that will happen. And I don't know what the situation with mining lithium on the Moon or something like that, doing the things you need to make batteries, for example, those are things where one could imagine sort of outsourcing those to the moon and not muddying up our atmosphere, so to speak. Because after all, on the Moon, when something is sort of belched out from the factory on the Moon, it's just going to go into empty space and it'll be sort of those particles from. Actually, it's an interesting question, what will happen with them? I think it's a question of whether they are faster than the escape velocity of the Moon, which is one sixth the escape velocity of the Earth. If you kind of have your factory, it's producing kind of. I don't know. Well, let's see. I mean, carbon dioxide, for example, I would suspect. Yes, it obviously does escape from the Moon, because after all, the Moon has no atmosphere, so all of the gaseous elements and compounds, they're typical. Well, actually, it's not so obvious because it depends on the temperature. Well, the question is, when you sort of belch out carbon dioxide from some process on the Moon, what happens to those carbon dioxide molecules? My guess is that in most cases, they will escape the Moon's gravity and just get dissipated into space. But it is also possible they just fall back down again. And you talk about carbon capture or something and carbon sequestration, it might happen automatically because the things that instead of getting kind of enmeshed with the atmosphere and the air currents on the Earth, it would instead just sort of fall back to the Moon. It's either going to fall back or it's just going to be sort of spewed out into space. Let's see. Capper asks, how would you get the signal back to Earth from the far side of the Moon? That's pretty easy. You. You just have satellites orbiting the Moon that relay it back. It's not quite as easy as on the Earth. We have communication satellites on the Earth that are able to take you send a signal to the satellite. The satellite could perhaps send a signal to another satellite, or it simply can see another part of the Earth and send that signal down to another part of the Earth. But. And that's so you can do the exact same thing on the Moon. And so if you have a satellite orbiting high above the Moon, it will be able. You could either do it directly or with a relay to another satellite to get the signal from the far side of the Moon back to the Earth. The Moon is a little trickier than the Earth to have satellites because its gravity is not as uniform as the gravity of the Earth. The Earth is not a perfect sphere, but it's pretty close. The Moon is a sphere, but it has a big lump of different density on one side, probably from the way it was formed. And that means that the orbits of satellites are more complicated and don't end up being a fixed distance from the Moon, as they typically are roughly on the Earth. And that means it's a little bit harder to have a stable orbit around the Moon. And satellites don't last in orbit around the Moon and the Earth. The main reason for orbital decay of satellites around the Earth is just little pieces of atmosphere, wisps of atmosphere that get up pretty high and that tend to slow the satellite down. On the Moon, there isn't an issue like that, but there is an issue of the gravity field being a bit messy and so more difficult to maintain something in orbit. I suspect that's a more of a technical difficulty, and that by, you know, you may have to use thrusters or something to arrange that you are going in this particular path around the Moon. And maybe that's an issue. And I don't know, you know, I don't know whether that can be solved by, for example, using essentially electrical ion thrusters or something like this. I'm not sure. Pedro asks, why would so many nations be interested in the Moon? Well, you know, partly realistically, it's a good technology demo. Send a successful spacecraft to the moon, and you show that you can successfully assemble a very big stack of technology to actually get the thing to land softly on the moon. So it's in terms of kind of economic development, of saying, look, we can land the spacecraft on the moon. It's pretty cool to be able to say that. And, you know, India just managed to be able to say that. And that, you know, is kind of a thing that is a bit of a kind of a demo of just like, you know, technology demo, so to speak, of capabilities. I think that's sort of a number one reason to. It's sort of a driver, as the Apollo program in the US Was a big driver of kind of technical innovation in many different Areas of technology, that's a good reason to kind of go to the Moon. But in terms of what's going to be the kind of economic benefit, the direct economic benefit, as opposed to indirect economic benefit of going to the Moon, It's a bit unclear. I mean, there's not clear there's much to mine on the moon, except, for example, water, for example, which can be used for fuel to send spacecraft further away. But it's kind of like, okay, the Moon isn't useful. Let's see if Mars is useful, for example. And then the question is, is there something we can get from Mars and bring back to Earth? Probably not. I've not really heard of anything serious there that people talk about. It'll certainly be interesting to get Martian rocks, and we have a few from meteorites and so on. But to get sort of, you know, freshly collected Martian rock will certainly be very interesting. And, boy, it will be very cool if there end up being some kind of microbes that we find deep in Martian rock or something like this that are around like ones on Earth. I think this is a rule of space question of sort of how far apart is kind of different forms of life, so to speak, in the universe. And my guess is very, very far apart, usually unless they have a common origin. But in any case, in the case of sort of, it's a kind of recursive thing, we can use the Moon in order to go to Mars. Well, then we have to know, why are we going to Mars? And certainly people talk about eventually sort of colonizing Mars as the backup Earth 2.0 or whatever. I don't know how convincing that is, because I do tend to feel that some of the things that might cause terrible problems on Earth, you know, the AI that decided to wipe out humans, so to speak, we can talk about whether that's realistic or not. But imagine it is realistic. There's going to be enough kind of communications traffic that the kind of supercomputer virus is going to wind up on Mars as well. It's not going to be that separated. I mean, there are certainly things that. There are plenty of issues that would easily get transported, so to speak, and where it isn't the case, that, oh, different planet, completely isolated situation. So I think, as I say, in terms of indigenous use of the Moon, so to speak, certainly there have been things that are very unexpected things, like, for example, the lunar laser retroreflector that was put on the Moon by the Apollo astronauts is the way to measure the distance to the Moon more accurately than Anything else. And that has allowed one to verify things about theories of gravity and so on. That's a pretty cool, unexpected use of the moon, so to speak. I think the things like, oh, can we mine something from the moon other than water to make rocket fuel and bring it back to the Earth? I certainly knew of one initiative where it was like, let's get moonrock just because it'll be cool, like diamonds are cool. I'm not sure how convincing that is because moonrock doesn't have the nice high refractive index that diamond has that makes it diamond sparkle and so on when they're cut appropriately. That. That's not something we know particularly how to do from moon rock. Then there was sort of a possibility that helium 3 could be mined on the Moon. I don't think that's particularly interesting or realistic, but I don't know. It's an interesting question. What becomes possible? Maybe there are things that in 1 6th gravity that we have on the Moon, there are things that suddenly become possible that aren't possible in Earth's gravity. There are definitely things people talk about in microgravity in orbit around the Earth, things like growing perfect crystals, things like all sorts of, well, biological processes are rather different when you don't have gravity. So there are questions there. But as is typical of technology and engineering, given a thing that physics throws at us, the question is, can we find a way to make use of it? And if you say, okay, you can build anything you want in 1 6th gravity, is there a great way to make use of that? I don't know. If you can sort of build anything you want, sort of in a way where you can spew out any kind of, kind of sort of output, then there may be a way to make use of that. All right, let me see. We had some other questions here. Well, let me go back down here. Desks, comments. Suppose we just got lucky and developed our current technology during a period of unusual solar calm. How do we adapt if we expect solar storms to cause havoc with our electronics, say every few decades? So just a bit of background there. The sun produces streams of charged particles in addition to producing light. The sun produces the solar wind. And every day you can look it up in Wolfram Alpha. If you type space weather into WolframAlpha, you'll see today's space weather, which is what's coming from the sun today, not in the form of light and the form of charged particles. And every so often, there's a major solar flare that spews a huge number of Charged particles in the direction of the earth, for example. And that happened particularly dramatically in 1859, a thing called the Carrington event, where if that happened today, it would sort of create havoc with a lot of electronics on the earth. Essentially what's happening is that these charged particles, as they kind of, they will induce currents in wires and that will cause things that are set up, like electronics, that is set up to operate at a particular voltage. Basically, most, most computer type electronics ultimately operates around 6v. Why is that? It's because in silicon, which is the thing used for microprocessors and so on these days, universally, the way it works is there's a critical thing, the so called band gap of silicon, which is how much you have to kick electrons that are otherwise hanging around silicon atoms. How if you kick the electrons that are hanging around silicon atoms with a 6 volt kick, basically then they get to the point where they get into a conduction band where essentially those electrons can freely roam around the silicon, around the silicon crystal. And so there's this kind of, a lot of the operation of electronics relies on this kind of ability to go from. It's a complicated story with doping with other materials that changes how that works, and that's how you make transistors and so on. But in general terms, 6 v is the critical voltage that kind of promotes electrons from being, you know, stuck around the silicon atom to being able to roam freely. Well, so if you put 100 volts into that piece of electronics, it'll, you know, wreak havoc with the whole thing because all those electrons will get promoted. They'll all, there'll be conduction between everything. It'll all be a big mess. So it's bad to do that. And if you have something where you induce those kinds of voltages, induce currents, induced voltages, you can destroy the electronics. And that's bad. So that could happen and we would have some warning of it. We have, I think, well, light comes from the sun in eight minutes to the earth. And there are telescopes watching the sun. And if there was a giant solar flare, we would see it long before eight minutes before the charged particles. It's actually longer than that because the charged particles, the eight minutes is actually irrelevant. The eight minutes is how long it takes light to come from the sun. We don't even know anything happened on the sun until, in a sense, eight minutes after it happened. But the question of what counts as simultaneity is a whole relativity story which we don't have to worry about here. What matters more is that the charged particles are going much slower than the speed of light. I think they take a day or something to get to the Earth from the sun. And so if we see something happened on the sun, we have a fair amount of warning about the fact that there is a coming burst of charged particles that can mess up our electronics. I have to admit, I don't completely know what electronics like, I don't think I know of sort of what the arrangements are like, what will actually happen in the world if there's another one of these events that is seen and we have a day's warning. I would assume that things like planes will not happily fly in that situation. And that presumably. But I don't know how the arrangements are set up. All the planes would get grounded. And the other big thing is that long distance electrical transmission lines get big voltages induced in them. And so you can do things like blow up electrical transformers and so on. And I don't really know other than shutting down the power grid. I'm not quite sure what you do about that. And even if you shut down the power grid, you're still inducing currents which will have bad effects. But I'm sure there are things that can be done to remediate that. But I have no idea whether 1859 was a long time ago. And so people have kind of forgotten what happened then. And obviously the world was much less electrified at that time than it is today now. The question is, if this happens regularly, what does one do about it? I think that there will be certain aspects of what's going on that, you know, it's kind of like, you know, I don't know how much effect it will have on kind of the actual way things do people, ways people do things. I mean, if there's, if there's one big event every decade, every 30 years, and it's kind of like, well, if you have a satellite TV and it's raining and you don't get the good signal, well, so be it. But the rain will be over eventually. And there are things like that where one can say, well, some things are going to have to. I mean, there are outages that happen and maybe this is just an outage that happens for a limited period of time. I don't think it's something that lasts terribly long. Harry is commenting. There's an international alert system for solar activity. You can subscribe to it. Okay, well. Well, I'm guessing there must be something like that because we have space weather data in Wolfram language. So Worst case, you could write it there to say if the density of charged particles is greater than this, send you a text message or something. I think that I was going to say in terms of sort of early warning type stuff, there are places where earthquakes, for example, there's a fault line, earthquakes happen at the fault line. The center of population is some distance away and there's an early warning system that's been set up because the earthquake, you detect the earthquake and the earthquake, the sort of effect of the earthquake moves through seismic waves which travel at a few thousand miles per hour, much slower than the speed of light, much slower than the time it takes to send a signal through radio or through fiber optic cables and things to some place. And I know there are factories shut down and all kinds of other things happen. Even if there's only a few minutes of warning, that's a good thing. And obviously in things like tsunamis, there's now am, I mean there was for a long time a Pacific tsunami early warning system which actually made use of our technology, I happen to know, and I think there are ones for all oceans, a similar kind of thing. Well, let's see. Ah, prototype comments. Fiber optics have reduced our vulnerability to solar storms. I'm sure that's true. Where all the landlines were copper, only the power grid remains. They say that sounds plausible. And no doubt if everybody has their very own solar panels and things or their very own local fusion reactor or whatever it is, then these long distance lines, I guess the, I mean my impression is I, I should know this piece of physics, but there is a certain, what would it be, an induced voltage that per unit length of wire has some effect and I don't know, I don't know. I, I, I'm certainly aware of the fact that something, I don't know how comparable it is, the electromagnetic pulse that you get from detonation of a nuclear weapon in space that affects even small scale low voltage electronics. And I don't know how similar that is to the induced currents that come from solar activity. It must be somewhat similar because it's again, it's a, hmm. Well I, yeah, I'm not sure, not sure Physics to work out there. All right, let's see other questions. Well, okay, Jamie asks, what does the future look like for computational language? Will it be adopted on a larger scale? Well, building computational language embodied in our Wolfram language is my kind of life work. Trying to find ways to represent our world computationally, trying to find ways to essentially formalize how things in the world work. Going from kind of what we can just describe, for example, a natural language to things that we can describe more formally, as we have been able to do in mathematics, in logic and so on. Generalizing that to sort of having a computational description of the world, that's kind of been my life work. And the last, well, 35 years we've been working at 36 years we've been working on Wolfram language to let people be able to make those kinds of computational descriptions of the world and then to sort of automate doing things with those computational descriptions of the world. And you know, in the world of people doing research, development, education and so on, the whole idea of computational language I think has been, well, in particular cases has been quite well absorbed. And I think it's generally true that having this computational description of the world that has a lot of knowledge built into it, a lot of algorithms built into it, a lot of coherence in the different ways that things are treated in different parts of the computational language, that's a critical idea for people who are doing things that have never been done before. That's kind of, if you look at the history of the last 35 years of things that people have used mathematical and morphine language for a really pretty impressive swath of things that have been invented in the world, discovered in the world, have made use of that technology. And it is really sort of the ideal technology for doing things that have never been done before. Now, if you look at sort of the rank and file of software engineering, much less use of orphan language than there should be, much, much less use. And it's an interesting question why? And I think I've sort of realized that one of the issues is the following. If you use some low level language, I don't know, Java, Python, whatever, C, whatever it is, there's a fair amount of just mechanical work that you end up doing, just building things with that language. The language doesn't have much built in. Maybe you get some library you get from here to there, you cobble this together, et cetera, et cetera, et cetera, you have to do a lot of sort of mechanical work to get to the particular things you want. Whereas in Wolfram language we've built everything in. That's kind of the idea. And so what you are presented with is a, okay, what do you want to do? Once you can define what you want to do, the machinery of doing it is rather straightforward. Typically it is. But you are, you know, if you're doing something in some low level language, it's like well, I'm figuring out what I'm going to do. That takes me a day, maybe if you can be good at figuring it out, then you spend the next two months implementing that. Whereas. And much of. And those two months are just like. You show up every day you write your code, you go home. Well, maybe you're writing it at home these days, but, you know, it's a pretty procedural kind of thing and sort of the duty cycle, the thinking part is a much smaller part. Now people are realizing that with LLMs and so on, you can write a lot of that boilerplate code. I don't know how reliably that's an issue. We're still trying to understand that better. But you can write at least some of that boilerplate code. Some of that kind of mechanical code can get written by an AI and so the humans don't need to do it anymore. And that's again beginning to sort of crunch things up to the point that is more like the story with computational language, where it's kind of mostly thinking and not so much mechanical work. And so the thing that is sort of perhaps, well, to the people who kind of do new things in the world, it's something that, well, they just want to go as fast as they can. And they're in the business of figuring out new thoughts and figuring out how to do new things in the world. And so for them, having the tools that make it as easy as possible to go from the thought to the implementation is just a huge win. And that's kind of the story of my life in science and so on, is using Wolfram language as a tool to be able to do a lot of things like our physics project and so on, that would just have been completely infeasible, impossible, would never have happened would without that level of automation in actually getting the mechanics of doing the technology done, so to speak. So we're kind of in this situation where with Wolfram language, with computational language in general, it's sort of all thinking about what to do and not so much effort in the doing of it, because that's what we've automated away. And in a sense that becomes something kind of daunting if you're not in the business of figuring out what to do, so to speak. And I think that's kind of the number one reason why you don't see as much kind of sort of use of computational language. Maybe it's also because we haven't marketed as well as we should have done. But I think the more underlying reason Is because an awful lot of the activity of programming is this kind of procedural kind of activity that doesn't, you know, that isn't intense, concentrated thinking about what to do. And the set of people who do that intense, concentrated thinking about what to do is a bit smaller than the set of people who need to be there doing the mechanics of software engineering, so to speak. So I think this is kind of the challenge and, you know, could many things run faster, do better, be more efficient, if computational language was more widely used, absolutely unquestionably in companies, in other organizations, sort of thinking about things in computational terms, how do you take those things that you're doing in your organization and how do you think about them as functions that you can apply? How do you think about sort of symbolic data structures? How do you represent the things you sell as symbolic expressions that then are a kind of computational representation of the actual things you sell and so on, which you can then manipulate, deal with in your transaction processing system, whatever else. These are things where sort of defining how to think about things computationally. That's the main stumbling block in once you understand things with clarity. If we and I have done a good job in designing Wolfram language, and we've done a good job in implementing sort of the computational knowledge that's inside it, then really, once you've figured out how to express yourself, how to think about something computationally, then it's plain sailing. Then it's just then it's sort of turning the idea into reality is a straightforward part. The difficult part is conceptualizing the idea. And so I think that's the main sort of blocker, in a sense. And I don't know what you know, I have to say, I think that the unlocking of progress, if more was done where it goes from idea to reality, that the removal of barriers and going from ideas to reality that computational language provides are tremendous. I mean, again, I myself have been pleased to be an example of what's possible there and what one can actually achieve in most cases, in my case in science, by making use of those that the capabilities of computational language, there's a huge amount that will be unlocked. Now, how do we get there from here? I think that one of the primary problems is having people understand how to think about things computationally. I plan to do a project, hopefully starting very soon, to create some kind of book course, I don't know what probably live streams and things as well, explaining this process of how do you think about the world computationally? I've been doing this for 40 something years and in different sort of corners of the world and different kinds of things you do. There are different ways to sort of think about things computationally. Once people understand that with clarity, then there's sort of every chance to be able to, you know, given the actual technology we built, a lot of things get to run a lot faster. It's left to its own devices. I don't know how long it will take for people to get to the point of sort of widely adopting this. I mean, as I said, it's been adopted very widely among people who are figuring out and doing things for the first time in sort of the high end of research and development. It's always remarkable to me. It's very satisfying in a sense, that when I'm talking to people and it turns out they did something so of that's a major piece of sort of research and development 10 years ago, let's say it's like, oh, by the way, they used Wolfram language to do that. There's a tremendous correlation between the things that really are things done for the first time in the world in terms of R and D and places where Wolfram language has been used. It's really. That's sort of the most incisive part of its contribution, I would say. But if you look at the timescales for adoption of things where people sort of generally understand, oh, this is how things work, they are shockingly long. I mean, even the idea of notebooks, for example, which we invented in 1987, took at least 25 years for people outside of our technology ecosystem to really say, oh, yeah, this is a good idea. I mean, I remember 25 years earlier, people were saying, I don't understand. I don't understand what is this? And 25 years later, that really very, very, very straightforward idea becomes something that is more widely absorbed. I think there are a lot of ideas in the kind of symbolic programming domain that were core ideas in Mathematica now Wolfram language, and even my predecessor to these things, SMP, that I built in 1979-1981, that was. There are a lot of ideas about symbolic programming that are completely not widely absorbed. And as I say, people who know and use Wolfram language, either implicitly or explicitly understand many of those ideas. But if we look at the things beyond those core ideas, if you look at kind of the tower of ideas that we've managed to build, it's a pretty big tower. And many of those ideas, once, you know, once you understand how to think about things computationally, many of Those ideas are very natural and easy to use, but kind of the. Kind of absorbing those things and absorbing the whole sort of computational thinking idea. I don't know how long it's going to take. I think the timescales are measured in the century, half century, I don't know, century if probably timescales if kind of left to their own devices. I think this is one of our challenges in modern times is to communicate how to think about things computationally. And as the machinery to do that kind of. We have Wolfram language. It's just like when people started thinking about things mathematically, it was critical to have mathematical notation as a way to express those mathematical ideas. The point of computational language and Wolf language is to have a way to express ideas computationally so that you can kind of go forward and have a medium for thinking about things computationally. It's kind of the, you know, people often say it's hard to think about things unless you have words for them. And this is our computational language is the kind of medium in which I think one can think about things computationally. And I think that's just the thing that has to be learned is how do you think about things computationally? It's like most people would not invent either logic or mathematics for themselves. In fact, I think almost nobody would. Those are things that have arisen in our civilization and through long periods of time and the things that you have to sort of learn in education. And so it is with computational thinking and computational language. But unfortunately, to date, there's very scant education in that area. There's plenty of education nowadays, in quotes, computer science, which often means the practicalities of programming and to some extent, some of the very wonderful and interesting theory that goes along with all of that. But in terms of, okay, you've got this thing, let's think about it. Computationally, that's not something for which there is a well understood kind of educational path. And I guess it looks like it's falling on me to try and figure out how to build that. So. Let's see. Question here from robot asking, how do you anticipate biotechnology shaping the future of biomaterials and tissue engineering? Oh, gosh. Well, you know, if you want to make, I don't know, a piece of heart muscle, there's kind of several ways you might imagine doing it. One thing you might imagine doing is getting a stem cell. You know, one of the things was discovered, maybe, what was it, 10, 15 years ago, is how to take any old cell and hit it with these Funny, it's kind of almost Frankensteinian kind of mechanism. You know, you're kind of hitting it with these particular molecules and so on, and you are getting it to revert to a state where you're kind of cleaning its DNA to the point where it is able to be a pluripotent stem cell, a stem cell that can turn into any other kind of cell. So strategy number one would be you go, you take a cell from a person, you kind of want a cell from the same person, because otherwise their immune system, otherwise, if it's a foreign cell, so to speak, the immune system of the person will reject it. But you take a cell from the same person and you say, you hit it with these chemicals, you get it to revert to its initial stem cell state, and then you guide it through the differentiation pathways to get to the type of cell you want. And I think there's sort of a lot of art involved in doing that guiding. And some of it requires that the cell be in an environment that's kind of like the environment it would be in in a natural growing organism. But, you know, at most, there are perhaps 15 differentiation events to get to any of the types of cells of a few thousand cell types that are part of us. You can potentially do that by having the cell kind of go in the right way at those different sort of choice points for the cellular differentiation. So that's kind of one thing you can do, is make individual cells by that mechanism. The other thing you can do is try and make sort of scaffolding. And that's a thing that people are interested in trying to do. Like I've seen a very nice example of artificial lung that's being 3D printed by just making a material that is like the collagen that. Yeah, that's kind of the skeleton of something like a lung. You build up that framework in something that is not really cells that are doing the things that living cells do. You build that framework by essentially very high resolution 3D printing, and then you kind of coat it with the kinds of things that cells that sort of do other things in the lung do. So it's kind of this trade off of you are making a thing where you're 3D printing the scaffolding and then you're putting cells onto that scaffolding versus the other case where you're making individual cells and the assembly of those individual cells into larger kinds of assemblies. I'm not quite sure what the right way to do that is. I mean, that's been a thing that people have encountered in, for example, making artificial meat. It's like, how do you create this kind of whole matrix? How do you create this whole thing where it's not just individual fibroblast muscle cells, but, but it's a whole sort of assembly of those things in the form that they would exist in an actual piece of meat, basically. And I think. So that's on one scale. I mean, I think that the other important level for biotechnology is sort of molecules and cells that do things. You know, most drugs, for example, their main mechanism of action is they're a molecule, they are a certain shape, they fit into some binding site on some other molecule, and they make more of something happen or less of something happen. But the molecule is just this. It's just like a puzzle piece. It's not doing anything. It's just fitting into something. So one can imagine a situation where the actual molecule is capable of doing computations, or where it's a whole cell and where the whole cell takes certain inputs, kind of decides what to do and then takes action. Now, like many things, we didn't think of this. This has been thought of by biology before. That's how the immune system works. A T cell in the immune system is essentially, we don't know all the details of it, but is doing all kinds of things, interacting with other T cells, interacting with various kinds of, I don't know, cytokines, other kinds of molecules and so on, and then making a decision, oh, that's a bad cell, I should go kill it, or whatever else. And being able to make sort of an artificial version of that is another whole sort of story of what becomes possible in biotechnology. So, I mean, a few thoughts there on that. I think that in, you know, there's sort of the question of to what extent are you getting something which is functionally equivalent to biology. Let's say you're trying to make artificial blood. That's been a long time story. You know, right now our blood uses hemoglobin, a protein that has this little cage that's just the right size to fit an iron atom in. And that iron atom can have oxygen bound to it. And so you can transport oxygen around your bloodstream. But it's like, well, why can't we just make a, you know, make our own hemoglobin like thing, make our own red blood cell and transport oxygen around around us. And that hasn't been successfully done. But that's sort of one branch is to say, well, let's just make something which is functionally equivalent to, to biology, but is not made from the same stuff that biology is made from. Not made from proteins, for example, just a purely like a 3D printed red blood cell or something that just functionally is equivalent to a red blood cell, rather than being like the living material that we have. And so that's one branch. The other branches kind of go from stem cells and build up something which really is just like a piece of you, so to speak, That can do that. I think one thing that is interesting is kind of to what extent we manage to make all the stuff we need, but as we get older, for example, more of it stops working properly. And there's sort of a question what actually changed? And there's a lot of evidence now that quite a lot of what changed is sort of things that are epigenetic, things that sort of are attached to the DNA in our cells, but they don't change the genome, at least not unless we get cancer and things. They don't change the genome, they just are changing sort of the dressing around the genome. And so this, with the fact that it's possible to go get back to stem cells that you can go and sort of introduce these factors that let you go sort of revert back from a differentiated cell that has sort of dressing around its DNA to one that is sort of a pure stem cell, makes one think, well, maybe if there's more dressing that gets developed as a result of things getting older and crummier, so to speak, maybe one can go backwards by just using the same kind of method. Now, you know, that would all be just perfect were it not for the fact that as soon as you have a cell that can differentiate into anything, one of the things it can differentiate into is a tumor. And that's bad because the tumor then grows without bound and eventually takes over other functions of the body. I mean, in a sense, one of the achievements of biological life back probably 1.52 billion years ago was being able to make life that grows only so big and then stops. And what had happened earlier than that is things, well, these stromatolites and things like that, just growing, growing, growing, growing. You know, huge areas where there's just a single thing that just keeps on, keeps on, keeps on growing. But then it turned out that evolution found it better to have individual organisms that got to a limited size and were sort of independent organisms. Not quite sure what the advantage of that is, but I suppose there's more sort of. It's like, actually it's sort of a discretization play. Just like it's a sort of interesting point that biological evolution discovered the idea of discrete organisms rather than just the continuous. One organism is all of life, so to speak, that it's better to have many eggs or many baskets for your eggs, so to speak, rather than just putting everything into one organism, it's better to have many separate organisms running around that can independently succeed and fail, rather than putting everything into that one organism, which maybe all fails for some reason. So in any case, but that's sort of the main issue is that you can end up with cells that will just go back to that primitive form of life and keep replicating forever without sort of knowing limits and without noticing, oh, know, we've managed to grow this particular muscle and it's now filled this area now stop, so to speak, rather than just keeping on growing. Let's see, So many interesting questions here. Maybe one or two more. And then I need to go back to some science that I need to do today. Well, Kat asks, how do you see the future of information consumption? Will it all be digital? Will physical books still be relevant? Will it even be reading? Or simply data chips inserted into the brain? So a thing to realize is sort of relates to the very abstract stuff I was talking about earlier. All of us encode information internally in our brains in somewhat different ways. If you took the very nerve, you know, the pattern of weights of the neural net in my brain and transplanted it to another brain, it will be completely useless because that other brain will encode information in a different way, in detail. So the only way we know to get information from one brain to another is by packaging it up into concepts, words, language, and so on, and having it unpacked in the other brain. Now, it could be that as we have direct neural connections to brains, that we will be able to learn a translation layer for each given brain, which does at least something to transmit ideas directly into the form appropriate for the brain in which that neural implant exists. That's certainly a possibility, but I think otherwise we're stuck with sort of packaging information in any situation. We're still packaging the information for the neural implant, for our eyes, whatever. We're packaging information in a uniform way. That kind of is a language that everybody can understand, whether it's human language, computational language, whatever else. Now, I mean, it is an interesting question whether we can directly feed computational language to human brains. It doesn't work in our neural nets. We can't run programs in our minds. But if we had sort of a direct connection to something that can run a program, a direct kind of neural implant with Wolfram language or something. Then, you know, what does that mean? What would that feel like to us? It would be kind of like. It would probably feel very much like many aspects of our existence that we don't have conscious control over. Feel. It's kind of like, I don't know, you have a reflex, for example, you know, you. You know, pit just below your kneecap and your. And your. And your leg bounces out from that reflex. You can override that reflex, but. But you can't. You know, you can't. There's nothing where you're. You're thinking to yourself, now I'm going to kick my leg out type thing. And I think what it would feel like if you have the sort of neural implant that does computational language, I think it would feel like essentially just I'm thinking this thought, and then suddenly something happens, and it happens sort of automatically. And I didn't have to think that in order to have that thing be the next thought. I think. I suspect this happens. You know, we don't get to unpack our thoughts most of the time. In other words, when somebody says, why did you come up with that? Well, you can kind of reverse engineer something to say, but really it just popped into your mind. It wasn't something where you felt the steps, so to speak. And maybe that's how it will feel with sort of a neural implant kind of thing in terms of the absorption of information. See, one of the things that happens right now, like, I much prefer written, printed, you know, visual diagram type information to videos. Why is that? It's because I have control over what part of the information I am absorbing. Like, I can skim through to the next page. Whereas with a video, it's kind of like unlocked into. Absorb what was presented, so to speak. So I think in, you know, if you ask a question, will there be sort of information provided? It's actually interesting that I think even books, for example, which seem very antiquated in a sense, are still very useful because books represent a certain unit of information transmission that has a certain expectation of organization. In a book that's different from the arbitrarily scrolling, linked kind of tree of web pages or something. It's a humanly useful thing. It's kind of like you could say, well, we could make things for us humans. We could make sort of, I don't know, roller skates that move humans around at 100 miles an hour or something, but it wouldn't work for humans. Humans wouldn't be able to deal with that. That's not something that's a good fit for humans. And so I think, you know, when it comes to information, there's a question of how do you, how do you form the information in a way that is readily absorbed by humans? And even things like books turn out to be a good form for absorbing information. I mean, we've gradually learned different forms, whether they're blogs or whether they're bullet points or whatever. We've gradually learned the kind of ergonomics of good ways to present information. Now, I suspect that one of the things that LLMs will be able to do is help us to have information both generically presented effectively. I mean, like, I routinely have LLMs, you know, summarize abstracts of papers so I can just see, well, what's the two sentence summary in kind of the somewhat boring text produced naturally by an LLM. And that's useful for me. It's easier to absorb that than the longer abstracts and so on that we might have. So that's a, you know, and as we, you know, personalizing that absorption of information, I think is something quite realistic where the LLM knows what I know and knows that the thing you need to say to me to get me to understand this particular new point is this particular thing, and to somebody different, you might have to say a different thing. So I kind of think that it is quite likely that one will get to the point where it's like, there's this piece of information and then your pet LLM kind of is your tutor that explains that thing. Thing to you. So it's more so that instead of reading the raw thing, you're more kind of, okay, LLM, tell me what this says. I mean, I have to admit that in my life and times of somebody who is doing lots of stuff and running company and things like that, there are plenty of times where I will say, here's this thing. I'm trying to absorb the information from it. And I'll ask another person, can you read this in detail and summarize it for me in a way that I might understand? I think that will become more and more automatically possible with LLMs and so on. All right, maybe one last question and then we should wrap up here. Okay. Ollie asks is a fun one. Will we ever get to the point of other mammals evolving to the intelligence level of humans? You know, we don't know what the civilization of the whales is like. It isn't like human civilization. It's, you know, we hear whale Songs and they have all kinds of complicated structure. We don't understand what the whales are saying. And so I don't think we really know what the quote's level of intelligence, whatever that might mean of the whales is even right now. I mean, they certainly haven't built technology the same way we built technology. If that is our measure of progress and intelligence, then we're the winners. But perhaps to the whales there's a quite different measure of progress for which we humans are like, oh, I can't believe you guys don't understand. You know, the whales would be saying, I can't believe you guys don't understand the elaborate way that information is stored in currents in the ocean and the way that one can have sort of a global friend network because sound gets transmitted easily across the ocean. The way that one, you know, that we have this form of social organization, the whales might say, in which sort of everything, everybody is cooperating on everything. How come you humans don't have that? How come it's all kind of broken into these small pieces and you have to kind of assemble it into governments and things like this. We whales don't need any of that, we're much smarter than that type thing. So I don't think we know yet what exists there. But in terms of evolving a technological civilization, for example, of the kind that we humans have, I mean, insofar as what are the drivers of evolution, we don't really know what the driver of evolution for us humans was. Maybe it was even, you know, at the critical right moment, you know, climate change that caused us to have to get our act together and led to inventing language and having, you know, better, you know, better hands and all this kind of thing and not being in the trees and who knows what else. You know, maybe there was some constraint on us that forced us to get smarter in some sense. The question is, is that same forcing function going to exist for animals? I think an interesting question is pets and whether there is a driver of evolution for pets that might even be the result of artificial selection instead of natural selection. And then certainly in terms of breeding the, you know, cute looking critters with nice fur and all that kind of thing, and maybe breeding them for, you know, the smarter dog or cat or whatever it is. Maybe there's some dynamic of that, you know, how far one has to go, let's say, Interesting question, I suppose. Let's say we were breeding, let's say, cats for intelligence, which I don't think is something that's really been done And I think you can imagine a way of doing artificial selection of just you've got a bunch of cats, you give them IQ tests of cat IQ tests of some kind. I don't really believe in human IQ tests, but cat IQ tests. You could imagine making a thing and you pick the smartest cat in the bunch and that's the one you mate with another cat. Maybe we could advance at least the performance of cats on IQ tests that way. I don't think anybody's ever tried to do that. And you know, maybe the question is at what point do we reach a threshold where the cats that we have evolved in that case with artificial selection, you know, because maybe the natural selection of cats is not for the smarter cats. I mean, in other words, it could be the case that the cat that gets to have the most kittens is the one that has the longest claws. And that is not a trait. So you will select for that trait. But that trait is not a trait that leads you in the direction of building a technological civilization. That's the trait that leads you in the direction of being able to claw at things better, you know, very different kind of thing. So a question would be, if you, if you bred cats, let's say, for intelligence, and you just kept iterating that for a while, what would happen? And would you suddenly get above a threshold where the cats are starting to, you know, figure out how to talk and starting to be able to, you know, do start building things with their paws and all this kind of stuff? I don't know. I don't think anybody knows. I think that we've seen a very interesting example in recent times with the emergence of ChatGPT where there were language models that were progressively getting better, but they were still really pretty crummy by human standards. And then suddenly we get above this threshold where people say, wow, this is writing human like text. So maybe the same thing happens with cats bred for intelligence that for, you know, 500 generations nothing much happens. And then suddenly it's a wow, my cat is talking to me type thing. I'm not sure. That would be certainly an interesting thing to think about trying. I'm not sure what, how one feels about doing that. I mean, the ethics of doing that are rather complicated. And especially if one could reach kind of, you know, what would it mean if we, if we reached kind of sort of visible to humans level cognitive capabilities for cats and we kind of have to decide are we going to have sort of human exceptionalism or are we going to sort of seed part of the planet to the cats. Harry comments that their guess is the cats have just become even better at training their supposed masters. Yeah, that's a cute comment. I mean, it's kind of like the AIs we progressively get. We progressively. We think we're training the AIs. But it's a common feature of people who design computer interfaces that it's easier to train the humans implicitly in using the computer interface than it is to have the user interface adapt. I mean, it's a very common kind of joke in this area that people say, well, we have this adaptive interface. Actually, it turns out it doesn't adapt at all. The only thing that adapts is the people using it. So I think some comments about cat GPT. Yeah, that's a nice thing. It's a thing. A number of people are doing experiments right now on using kind of large language models for things like whales and so on, and what can one do from that? But it's a little bit difficult because we don't really know how to associate kind of the whale song with what that represents, what the meaning of that is. We have a sense because we get to have an internal view of human minds. We get to have an internal sense of what meaning of things is. Yeah, I think that this question of, I mean, my guess is that there isn't enough of a driver for, in the current state of the world, We humans are in charge enough that there isn't enough of a driver for sort of the up. Intelligencing of other species, so to speak, for that to happen by natural selection. But it certainly could happen by artificial selection. And oh boy, the consequence of that. I mean, there are so many of these very complicated ethical issues. I mean, whether it's. You talk about AI and you talk about, can you switch off an AI, Is that a problem? And you say, well, it's just a computer, who cares? It doesn't feel anything. But then you say, well, maybe that computer is actually a neural net that is not a digital electronics neural net. It's an organoid that's been grown with human nerve cells. Do you feel differently about switching it off? Do you feel differently about kind of throwing it in the trash or whatever? Well, I don't know. It's complicated. And that's, you know, there are a whole collection of these kind of almost sort of transhuman ethical dilemmas that we haven't had to address yet. And I don't know whether we have a great framework for thinking about how to address them. Anyway, with that said I'm not yet seeding my role here to to a cat, but I have to go and do something else. So. Well, thanks, thanks so much for joining me. Thanks for a lot of interesting questions and comments and I look forward to continuing this and the next one of these. Q. And as and thanks to somebody for asking about computational language. And you know, I do have to say that, you know, it's look, if you don't know our tech, you should learn our tech. It's the future. Even if in by natural causes it might be a hundred years in the future. But if you can deliver that to today, it's pretty cool to get that sort of artifact from the future and make use of it today. So something to be encouraged and also helps us make a living and do more R and D and make more interesting things. So. Okay. Well thanks very much and bye for now.