Science & Technology Q&A for Kids (and others) [Part 112]

Hello, everyone. Welcome to another Science and Technology Q and A for kids and others. And I see we have a bunch of saved up questions here. And one that just caught my eye is are there nuclear reactions going on inside our bodies? Well, so the answer is probably a very few, but not many. But let's explain. So when we have an atom, there's a nucleus in the middle which has protons and neutrons all bound together very tightly. And then there are electrons far away from the nucleus, and the nucleus is a certain size and the kind of distance the electrons are maybe 100,000 times further away than the edge of the nucleus, so to speak. So it's a pretty. An atom has a lot of empty space in it. And most of what happens in biology, in our bodies has to do with chemical reactions. And chemical reactions have to do with the electrons in different atoms interacting with each other. So, for example, what can happen is there can be an electron that gets pulled from one atom to another atom. When an electron is pulled out, that means that the charge of the nucleus, the electric charge of the nucleus, is no longer completely cancelled by the other electrons. If you just have an atom sitting by itself, there'll be a certain number of protons in the nucleus, as well as neutrons and a certain number of electrons in the atom. And if there are, let's say, I don't know, I count out my elements. If there are six protons in the nucleus, that means it has an electric charge of plus six. And then if there's kind of just a separated atom, there'll be six electrons also in that atom, which, which contribute a minus six charge. So the whole atom is electrically neutral. But if you pull one of those electrons away, then there'll be a piece of electric charge that's uncancelled from the nucleus. And that will lead, for example, two atoms to perhaps attract each other or repel each other electrically. But most of what happens in us biologically is the electrons of atoms interacting with each other. The nuclei of atoms never really get near each other, and they have a hard time getting near each other because they have an electric charge. And the rule for electric charges is if you have charges of the same sign, they repel each other. So two positive charges will try and push each other apart. If you have a positive charge and a negative charge, then they'll attract each other. So nuclei all have positive charges, and so they're kind of shielded by these electrons. But the nuclei themselves, even though most of the atom is empty space, so most of the time when atoms are bumping up against each other and interacting and their electrons interacting, the nuclei are just, you know, these tiny bits in the middle. And if they were to get close, they would tend to push each other away electrically. That's what happens most of the time. Now, there is a tiny probability that these two nuclei. First, there's a small probability the nuclei will kind of be lined up so they'll be near each other. And the second thing is, there's a tiny probability that even though you might think these nuclei would repel each other, that in fact, they will be able to interact and essentially get very close to each other. And that happens because of. Well, it's because of a quantum mechanics phenomenon called tunneling. It's the main effect there. And I think. Let me think about this for a second. Okay, so what's the point? If the two nuclei in a nucleus, there are lots of protons, they all have positive charge, how come the nucleus doesn't fly apart? Well, the answer is there's this thing called the strong nuclear force which keeps the nucleus held together. But the strong nuclear force, while it can, while it attracts protons to protons, protons to neutrons, and so on, doesn't have any effect on electrons. But the strong nuclear force is very short range. So its range is about a thousand trillionth of a meter. So if you take these protons and you make them more than a thousand trillionth of a meter apart, then they'll just be electrically repelling each other and they'll be pushed apart. But if you can get them really close into that thousandth trillionth of a meter, then they'll attract each other through the strong nuclear force, and they'll get stuck together. And one of the things that happens is if you take two nuclei and you can get them close enough that the strong nuclear force takes over, those two nuclei will be just pulled together and you'll release a bunch of energy associated with the fact that the nuclei, when they're pulled together, there's binding energy that gets released when the things get pulled together and be in single unit. And that's the effect of nuclear fusion and so on. And that's what powers, for example, the sun and so on. But so the question is, does that ever happen in our bodies? And the answer is, there is a tiny rate of fusion reactions that happen when. Even when you think that in the sun, the temperature is 10 million degrees and all these atoms are traveling at very high speeds because that's what happens. The speed of the atoms is proportional to Their temperature, actually the square of the speed is proportional to their temperature. But the hotter the gas is, the faster things will be going. And when they're going fast enough, just their pure momentum will sort of overcome the barrier associated with electric repulsion and the things will be able to fuse. That doesn't happen that way for ordinary. In our bodies, our temperature is, whatever it is, 98.6 degrees Fahrenheit, 90, 37 degrees centigrade, whatever. @ that temperature, these atoms are traveling at speeds very low compared to the speeds they're traveling at in the sun that would cause them to be able to overcome the electric propulsion and fuse. So how do any of them ever manage to do that? Well, the answer is that in quantum mechanics, the main sort of feature of quantum mechanics is that many different things happen. It isn't the case that when you're, you know, aiming these two atoms at each other, that there's just one path that the two atoms follow. Instead, there are many different paths they follow. And those many different paths, there's sort of a whole range of different paths. They all have a certain chance of happening. And quantum mechanics is kind of the story of all those different possible paths. Well, there are some paths that will cause these atoms to, for example, end up with nuclei that fuse or whatever else. Those paths are just very rare. Those paths are exponentially rare. That the chance of getting one of those paths, it depends on sort of how much energy you have to overcome and things like this. But it's sort of an exponentially small probability. One can probably work out what it is. If I think about it a bit, I think that's the main effect that will cause a tiny number of fusion events to happen. I don't know how often they would happen. It'll be rare. That's one sort of type of nuclear reaction thing. It's, by the way, when people talk about making fusion reactions and so on, people say, oh, well, I made this sort of home. Home kit that's made by the sort of home accelerator of where I just making protons go at high speed or something by just having an electrical. Something like an old cathode ray tube with, with electrical, electric fields in it and so on. And they say, I made some fusion. Yes, they make a tiny bit of fusion, but not just. Not very much. Just not enough to be interesting in terms of releasing the energy you'd need to make actual power from fusion. There's one more effect I might mention about radioactivity and about nuclear reactions in our bodies, which is nuclear Decay. So most of the time when you have the nucleus of an atom, it'll just sit there happily for forever. But some nuclei are unstable. They undergo radioactive decay. There are different types of radioactive decay, but there is, there are some substances that. So, so if something decays very quickly then, then it will all have decayed in a second or something like this. So there won't be any of it around. But there are a few types of nuclei that last a really long time, like billions of years. So those nuclei, if they were created when the Earth was created, there's still some of them around. So that's the case with Uranium235, for example. It's the case with a few other radioactive isotopes. Those types of materials don't typically get in our bodies. Those heavy metals, the things on the end of the periodic table, we don't use those biologically. And those things are just a nuisance biologically. And they poison us if we get lots of them in us. So most of those things don't show up as, as sort of examples of nuclei that are self destructing in our bodies. There are some others that do. Radon is an example of one that does. Sometimes it's something where there are, there's a. Okay. There's actually another effect I could mention which is cosmic rays. Boy, I always think these questions that seem like they're easy will turn out to be easy. Those are always the ones that have all these stings in their tail. Okay, this question is more complicated than I thought. So, so another case is radioactive decay, of which radon I would suspect is the primary example of something which can get in one's body and then undergo radioactive decay, which means its nucleus is self destructing, which is kind of a nuclear process, so to speak. The other thing that could happen is cosmic rays. So the Earth is constantly bombarded with, by particles that are coming particularly from the sun, but also from actually all over the universe. They're mostly protons. They mostly have an energy. Let's see how to explain the energy. The energy, well, it's about equal to the rest mass of the proton, which means that there, going at a significant fraction of the speed of light, these protons hit the upper atmosphere. They typically will produce a shower of other particles at sea level. It's particularly muons are particles that get produced. If you go up to higher altitude or on a plane or something like that. You'll see more of the kind of primary cosmic ray protons. And that, that, that's the. So, so anyway, these These cosmic rays are coming at a rate. So if you have a little going through something the size of us at sea level, you'll have a cosmic ray going through you a few times a minute. If you go on a plane, you'll have cosmic rays going through you every few seconds. And those cosmic rays have particles in them which are energetic enough that if they hit a nucleus, they will cause a nuclear reaction, a nuclear. They'll cause something to happen to that nucleus. They'll make the nucleus self destruct. They'll have other reactions in that nucleus. So that's another source of kind of nuclear processes in us. And as I say, I suspect that, well, it's a little different because a proton hitting us is very likely to have a nuclear reaction. By the time you get to sea level, most of the protons that arrived in the primary cosmic radiation have already interacted at least once. And when the protons interact, they hit protons, they hit nuclei in the air and the oxygen and nitrogen in the air. And they'll produce a shower of other particles, maybe 50 other particles, 100 other particles. Sometimes, actually the ones at the peak of the energy spectrum will probably only produce a couple of other particles. The higher energy ones will produce many more particles. And so they'll produce these particles. And when you hit a nucleus like that, one of the things that comes out are things called pions. Pions are the particles that are being exchanged between protons and neutrons and protons and protons and so on. They. They're the primary carriers of the strong nuclear force. And they're particles that have a mass of about a tenth the mass of the proton. And they have a kind of a. They're constantly being exchanged inside the nucleus. If you kind of bash a nucleus with another proton, you'll typically sort of knock some pions out of the nucleus. And pions are unstable. They decay the most kind of. Well, there are three different kinds. Positive charge, negative charge and neutral zero charge pions. And the positive and negative charge pions decay in 100 millionth of a second. And the neutral one decays in a 10 billionth of a second. So they decay very quickly. And they decay into these particles called muons, which are kind of like heavy versions of electrons. Electron muons are also unstable. They decay in about 2 microseconds, 2 millionths of a second. But those muons, they typically reach the Earth's surface as the prime, as the main cosmic rays that hit the surface. They are, as I say, like heavy electrons. They have an electric charge they don't participate in the strong nuclear force. And so when they hit things, they can have sort of an electrical effect on those things, but not directly a nuclear effect on those things. They can disrupt a nucleus, but they can't do so by using the strong nuclear force, so to speak. They're just doing it by using electromagnetic electrical forces. And as I say, muons decay in about 2 microseconds. Just to make things even more complicated, because the muons are traveling at high speed As a result of having been produced by a particle that hit the atmosphere at high speed, the muons are typically going at a significant fraction of the speed of light. And there's this phenomenon of time dilation, which causes things that are going faster to kind of think that less time has passed for them. And so the 2 microseconds lifetime of a muon is actually extended for a muon that's traveling fast. If the muon was traveling right at the speed of light, its lifetime will be infinitely extended. But it would also be infinitely hard to get the muon to travel that fast. But in practice, the lifetimes, the muons in cosmic rays are significantly more than 2 microseconds, which is why they survive getting down to the surface and make that kind of cosmic ray, the flux of cosmic rays at the surface. But anyway, that will be another effect that causes some kind of nuclear reactions to happen inside our bodies. Let's see. All right, there's a lot of questions here. Sorry, I thought that one was going to be easy. Gosh. Kat asks here, do you think it will ever be possible to replace damaged brain parts with computational parts as another form of prosthesis? Well, the answer is surely yes. Our brains are essentially electrical devices. We have about 80 billion neurons in our brains, 90 billion neurons in our brains. Each neuron is connected to maybe 100 or 1,000 other neurons by little tiny fibers. And what's happening is each neuron, maybe a thousand times a second, a neuron will produce an electrical pulse. And it'll send that electrical pulse to other neurons. And that whole collection of electrical processes is what eventually builds up to make our thoughts. And those electrical signals are eventually amplified effectively to make our muscles move and things like this. So the brain is really an electrical device. One of the things we don't know is going from that low level, individual components, individual neurons, the 90 billion of them or whatever, to things that aggregate up to complete thoughts and saying the next word I'm going to say, and things like this. We don't really understand that Stack of how that works. And so we don't really understand exactly what's important about that collection. Electrical activity. For example, we know that a single neuron, if you make the neuron, if you kind of get it really excited, you might think, oh, it'll produce more electrical. It'll have a sort of a bigger electrical voltage or current or something like that. That's not how it works. Instead, the neuron produces a series of spikes. It'll have. It'll kind of produce an electrical pulse, another electrical pulse, another electrical pulse. When a neuron gets really excited, it has a spike train that has this whole series of spikes. So instead of a neuron sort of increasing its voltage or something like that, it instead just fires more often. And for example, when you look at those spike trains or you listen to those spike trains, they'll have a lot of complicated structure. I mean, it'll go. And nobody really knows whether the details of kind of the sequence of times when those spikes occur, whether that's important or not, or whether all that really matters is there's a spike train going on from that neuron, or there isn't one. Or the neuron is just sitting there doing nothing. So that's an example of when you want to sort of plug into the system. You kind of need to know what about the system is important and what's not. But the question of, can we make something which is kind of like a pretend neuron that connects to a piece of the brain that's something that we can expect will happen? And I think that there have been for a long time kind of basic things like deep brain stimulation devices that produce electrical signals that affect neurons. Now, sometimes they'll have very tiny wires that will try and kind of get to the point where they can poke at one neuron at a time, so to speak. And that will be increasingly possible. People have built arrays that are implantable arrays that go on like the surface of the brain or can be implanted inside the brain that have kind of arrays of places where electrical activity can happen and where, when they get small enough, you can expect to have each one of those touch a single neuron. Now, the problem is the inner language of the brain. We just don't know what it is. It's like we know individual neurons. Oh, that neuron is firing. And sometimes we know for some neurons, we know that neuron fires when this particular thing happens. So, for example, there are neurons in our primary visual cortex at the back of our heads that are connected to particular places on the Retinas in our eyes. And so if you say, if you have a spot of light at that place on the retina, that will cause a particular neuron in your primary visual cortex to start firing, or more complicatedly, if you have a certain pattern, if you have something which has black in the middle, white on the outside, there are particular center surround cells in the primary visual cortex which will say, oh, yeah, I care about that, and will start firing. Similarly, they're ones where if there's motion in particular directions, they'll start firing, color at particular times, they'll start firing, and so on. And so there's a certain amount where we know what is the meaning of that individual neuron. But most of the time in the neurons that deal with kind of higher brain function, we don't really know. There's just a complicated set of neurons firing. And the end result is that we have a thought of some kind. Now, if we look at the same thing for a computer, we'd probably conclude more or less the same kind of thing. If you look from the outside at all of those different transistors and which ones have a firing at each particular time, and so on, It's a very complicated pattern of stuff that's happening. In the case of a computer, not a thousand times a second, but more like a billion times a second that these transistors are active. Although a computer typically many things computers do, a smaller fraction of its transistors are active than the fraction of our neurons that are active in a typical moment in our brains, at least that's probably true. But if you tried to look at the computer from the outside and say, what's this thing doing? It'd be really hard to tell. We're in the same situation with the brain. We have one big advantage about the brain, which is that the brain learns. And these neurons, the typical way in which they seem to learn is when they have seen a firing pattern. Let's say they're connected to a thousand other neurons. They see a certain pattern of firing of those neurons. They see which neurons fire together with each other neurons. They kind of learn, oh, this firing, this is the way it usually works. Okay, I will enhance that way of making it work. That's a simple form of learning in individual neurons. And so these neurons, they kind of learn their activity based on the things that they see happening. And so one can potentially make use of that. If you say, I've just got this electrical connection to these neurons, I don't know what it does. Well, the neurons the other Neurons to which it's connected can potentially learn from the things that are going on. And so, for example, one can expect that just as people learn, I mean, you know, we all learn, you know, at. We all learn to make use of our, of our brains and our nerves and so on. And we have to kind of learn that separately. Each person has to learn that separately. I mean, you learn kind of how to see by the fact that there are pieces of your brain that are sort of wired up to be connected to different parts of the retina. But when we're, when we're in the first, I don't know, a few months of life, we're noticing, oh, these pixels on our retina tend to be lit up together. And so that causes our brain to kind of start being able to recognize objects and so on and start saying those pixels are together, they represent an object and things like this. And for example, people who for one reason or another, they have vision issues in early life, that part of their brain won't be properly connected. So for example, a common thing is this condition called amblyopia where one eye has some just as very short sighted or whatever else and nearsighted or whatever else. And so sort of all of the, all of the seeing is going on in the other eye. And if, you know, people typically don't notice that until kids are a few years old. And then when what will happen is the eye that was just not optically very good won't, you, won't, won't be being used. All the seeing will go on through the eye that is working well. Well then, you know, the fix is you patch the eye that's seeing well, you fix the optics of the eye that wasn't seeing well, and then the kid and their brain learns to see. And the fact that that's possible to learn to see and one can tell that's what's really going on. One's learning to see by recognizing these sort of correlations between different things in the visual field and so on. And so that's the way that you've now got the sensor data coming in correctly through the eye when you fix the optics of that. And now the brain has to kind of learn to process that data. And I strongly suspect that when it comes to kind of neural prosthesis, putting in sort of direct connections, electrical connections into the brain, it's the same type of thing that you'll get this thing that's there and you'll gradually learn how to make use of that thing. Now in the Case of a vision, we know there are these sort of correlations in the world. There's a blob of pixels here, and there's usually pixels nearby that are the same color or whatever else, because there are objects, extent of extended size. And so, in a sense, the responsibility of that sort of thing that's connected directly to the brain is to provide something about which the brain, which can make sense to the brain. If you say, I'm going to feed into the brain this stuff that the brain's never going to understand, it's not going to work. But the, you know, what. What if. If it's something where the brain can learn that stuff, then you have a better chance to be able to have something where you can make that connection to, to that kind of electronic device. Now, what it's going to feel like when one's able to do that, I don't really know. I mean, I kind of feel like we have a certain sort of symbiosis with our computers now where kind of, you know, there are lots of things that I rely on my computer to do, including remember certain kinds of things for me and so on. But my form of interaction is I'm typing things with my fingers and I'm looking at things with my eyes. Now, if there was a direct connection into some part of the brain, you know, what would that feel like? I think the answer is one would learn to be able to make use of that, just like one can learn to make use of, you know, if one is driving a car or something like that. You learn to take this thing that is not part of your body, but yet control it in a way that kind of feels a little bit like it's an extension of your body. And I suspect that that's the same type of feeling where it would happen if one had something sort of directly connected to neurons in the brain. In fact, I suspect it will be a very similar feeling to that. And the question then of. To what extent can you take the things the brain is otherwise doing and outsource them to a piece of electronics? It's a good question. I don't think we know the answer to that because we don't really know that well what the brain is actually doing at a level that's intermediate between what the individual neurons are doing and the sort of psychology of thoughts and so on. But I would suspect that this is something we will learn to do. And at that point, you know, what will it feel like to have some part of one's thoughts, so to speak. Sort of able to be executed electronically as opposed to through neurochemistry and so on. Well, I think it will be interesting because some of those things that can be executed electronically will be able to be done vastly faster than the things that happen in just our standard biological brains. And so one can imagine it's like, well, let me think about what's this long number multiplied by this other number? Oh, as I think about that, just like I might say, the thinking about that might cause me to type it into my Wolfram language notebook or whatever else. So the thinking about that might just send it to my kind of sort of onboard piece of electronics, hopefully with a. A nice Wolfram engine thing running in it or whatever, which can then do those computations. And then you get the result back. And it's like, oh, I know the answer. It's this. It'll probably feel a little bit like retrieving things from your memory where you don't really know how you retrieve it from your memory. It's not like, oh, go fetch that from, you know, hippocampus segment, some segment number, such and such. You just remember it, and it's something that pops into your memory. My guess is that the feeling of something that comes from a sort of direct brain connection will be something very much like that. And so, you know, I would suspect that that is something that will. Will become possible. I mean, it then becomes a very tricky issue because, you know, when. When it's a question of programming people, the main. The only real way we have to program people is through education and through kind of, you know, explain things, get people to train, do training of various kinds, all this type of thing. It's. It's a very. It's that kind of process. If one gets to the point where one can, say, just load in that software and it's kind of direct to the brain, that becomes a different story in terms of how that sort of education process works. Now, the thing to recognize is every brain is different. So just like when somebody tells you it can be a whole class of lots of people that are being explained something the same way, but the way that explanation will play out in those different brains will be different. And so similarly, when you're talking about connecting kind of an electronic device to a brain, the way that whatever that electronic device does plays out in that brain will be different for every brain. And no doubt there will have to be some sort of interface layer that kind of specializes whatever is being delivered for each individual brain. Now, you know, then the question arises, well, okay, if it's sort of the direct brain connection and you're kind of, you know, it's feeding you the thought to think, so to speak, how does that, you know, what is the mechanism by which you decide or what software do you load in that will make you think these thoughts? And that becomes a very tricky thing. I mean, it's, it's, you know, one can complain already about the fact that, you know, somebody's getting people to think the wrong thoughts by virtue of the education, the, the kind of, the, the media, messaging, whatever else it is, by the time it's kind of, that's being delivered direct to the neurons, that becomes an even more extreme version of the same kind of thing. Although, Although it really is the same kind of thing because as I say, the way a particular message sort of plays out will be different for every particular brain, but it's still something where it's sort of closer in and it's not something where it's just. It feels much more direct than just, oh, well, there's this book and it says these, these, these wonderful, terrible, whatever things, people should read it and absorb it. It's more. There's this thing that is directly digitally connected. But again, there's going to be this layer of kind of interpretation that's different for every brain. It's different for every brain for two reasons. One, because our brains are structurally all different. Our fingerprints are a little bit different. The foldings of our brains are very different person to person. And the details of how brains fold and the level of the embryo is determined by local environment and is not something which is. There's a few genetic determinations, but it seems to be mostly it just happens to fold that way. And so that's one thing. The other thing is we've all had different experiences and we've all built up different memories. And even given exposure to the exact same experience, the memories that will be built up will be different. Even if there were two sort of identical twins who were exposed to exactly the same things, which wouldn't, you know, which is not really a realistic thing to have happen, it's still the case that undoubtedly the way that those memories will actually be encoded in the brain will be different. So, you know, sort of each brain is different and will interpret that data, even if it comes from a sort of onboard digital device, in a different way. All right, actually, the question here was about damaged parts of the brain with various forms of prosthesis. I think one of the issues there is if you've damaged a Part of the brain, what did you lose? Did you lose something that was a unique memory that was just stored in that part of the brain, for example, or is it something which can be filled in from other things in the brain? So we know that there's a certain degree of specialization in different parts of the brain for different people. The language center of the brain is in slightly different places, or there are particular structures in the brain that. That seem like they're really important for recognizing faces, for example. One of the things that I think is true about the brain is whenever people think, oh, it's very localized, it's kind of just laid out in an engineering way, like a machine, where there's this particular function that occurs in this particular place. It usually turns out that the story is more complicated than that and that there's some focal point, but there's other things that are affected by it, et cetera. But so the question is, if some part of the brain is damaged, is it possible to, you know, what have you lost? And, for example, you might have damaged a part of the brain that is, in a sense, very procedural in what it does. It might be a part that is responsible for signaling to muscles to do this or that thing. It might be a part that is the direct feeding in of visual images or something like this. I think those parts become easier to imagine, just replace that functionality. But obviously, in the brain, one thing that is sort of uniquely in the brain is our memories. And it's not clear to what extent the memories that we have are localized. They're not completely localized, but they're probably not completely delocalized either. There's some sort of complicated way in which some whole collection of billions of neurons store what will turn out to be a coherent memory. For us, one of the surprises is that even though we have all these separate neurons, that we have a coherent sense of what's going on, and we have have coherent memories. And that's something there's more to understand, and maybe even some of the ideas from our physics project, the formalism that's developed there, will be relevant for understanding kind of this process of. In neuroscience, of kind of going from the incoherent bundle of stuff that's stored in all these neurons to coherent thoughts, so to speak. But this question of, okay, if you damage a piece of the brain, how does it affect these coherent memories that you have? That depends on sort of how distributed the storage of those memories is and whether you can kind of fill in, oh, you know, I more or less remember that oh, I've stored that same thing a hundred times in my brain. I lost 20 of those times that it was stored because of some piece of damage to my brain. But I've still got 80 of those things left. And oh, those 80 that are there, as soon as I re remember one of those things, it'll generate another sort of follow on memory and I'll gradually fill in those 20 that I lost and maybe I'll even fill those in not in my own actual brain, but in some digital piece that's been added to my brain, assuming that interface can be built in the right way. But yeah, so I think, I think this question is, I'd be pretty hopeful actually about the ability to kind of replace eventually parts of our brains with digital things and be able to kind of take the memories and have them kind of spread out into those digital parts. But this is still all some distance away and lots of technology has to be built to make that possible. Plus, there are some more basic science questions about how do brains really work that still need to be addressed before one can really do this in an effective way. Let's see, There's a question from Madoff here asking what ethical implications will become relevant when, when we combine machine learning and brain sensors and effectors and so on? Yeah, I mean, I think that the thing that's always relevant to understand about sort of ethics and machine learning and AI and all these kinds of things is there's no right answer for ethics. It's not like when we do math or something like this and we've set up a bunch of definitions and we just say, what's the right answer? It's not even like physics where we say, how does our universe actually work? Ethics is a story of what we humans want to do. Now to some extent that's determined by how we are constructed biologically. And to some extent that is what we sort of societally choose to be the way that we want to have things work. And when people say, well, I'm going to get my machine to decide the ethics of this, that's ultimately kind of a doomed proposition because in the end one has to. The machine can execute on certain kinds of ethical decisions, can decide, oh, I'm going to put this particular, you know, this particular thing in the, in the news feed for that social media platform. And you know, it's. The AI will decide it wants to do that because that's what the humans like or whatever else. It will make those, the machine can be made to make a decision, oh, don't put that type of content in that newsfeed because it's ethically a bad thing, but it can execute on that. But deciding what's ethically a bad thing, the machine can't do that. At best, the machine might be able to show you some of the consequences of a particular type of decision, but even that there's a limit to how far you can go in working out those consequences. I mean, that's even a theoretical thing. Thing I figured out in the 1980s, this phenomenon of computational irreducibility, that even though you know the rules by which a system operates, to know the consequences of those rules is sort of irreducibly hard. You have to actually run the system and see what it does. So you can't expect that. See, now this is a great example of an AI in action at exactly 4:13 local time. For some reason, the kind of light control system that I have suddenly switches on a bunch of extra lights. Who knows? It seems to happen every single day. And the machine has a mind of its own. And it's sort of interesting anyway, just always good to actually experience the AI in action. And no doubt, perhaps it does that because at some point ages ago, there was some optimization put in for something that was supposed to happen every so often, and now it turns into this. But anyway, I was talking about AI ethics. And the thing is, you say, I want some kind of. You. You want the machines to do the ethically right thing. Question is, what is the ethically right thing? Well, you can see what people actually do. Okay, great. Then most people would say that what people actually do, you know, to store information on what the 8 billion people on the, on the, on the Earth actually do in different ethical situations and so on, is probably not what we want the machines to do. Because we want the machines to be our best selves that might not be our actual selves, so to speak. But then the question is, what does it mean to be our best selves? In what direction do you want to go from what we actually do to be better? And obviously, in the course of history, people have had all sorts of cultural traditions, religious traditions and so on, where people have defined what it is like to be the better us. But that's the challenge, is to bottle up what the better us is and have that be the sort of the constitution, the rules for the machines. But that's a thing to realize that it is a choice. It's sort of an arbitrary choice that is. I mean, it's arbitrary up to a point. If the ethical Choices are such that it will cause the species to go and attack each other and just self destruct and go extinct. It's kind of a bad set of ethical choices. It's kind of a sort of, one might say an existentially bad set of ethical choices because it will cause the species to go extinct and then there's no more ethics to be done, so to speak. And presumably we don't want the species to go extinct. I mean that's a complicated thing because you could say, gosh, gosh, we really like the way that nature is and we really like this or that aspect of the natural world. Who are we humans to come and disrupt the natural world? Wouldn't it be better if we were extinct? You know, as a human doesn't seem like a good deal to me. But you know, from a sort of overarching ethics point of view, you have to kind of decide what you want. I don't think that the, I don't think the universe does not have an ethical position. The universe is not out there saying, gosh, it would be better if the humans didn't exist because the universe doesn't have ethics. Ethics are a human construction. And so it's. But it's something where, you know, beyond the statement, oh, you know, we don't want, you know, we might have some overarching ethical principles. And certainly in the course of human civilization and history, there are some pretty universal ethical principles that have emerged. Although when you get beyond the very coarsest level, you start finding that different cultures have very different ethical belief systems and choices and so on. And so that, you know, then the question is how do you, for machines and so on, it's really, how do you capture those things in such a way that a machine can have this set of ethical principles? Those are what it's operating according to. And now when it's confronted on a daily, on every microsecond basis or something with particular ethical decisions to be made, that it can follow that code of ethics that it's been given. But the thing to understand is there is no ultimate right answer code of ethics, so to speak. It's a question of what one societally chooses. Someone's asking, are the mysterious lights sunset related? I don't think so because I actually think that I've noticed that at exactly 4:13 this has happened and it's happened for enough weeks that the. And it's also that it isn't the. It's not tied to the moment when the sun is going over the horizon. Let's See, Brady is commenting. Suppose a rule creates a memory in our brain, then it could be an irreducible problem to make a true brain interface for any individual which could interpret a memory or concept in terms of pre existing ones. Yes. I mean, this is a. What we have to provide in sort of a digital interface to the brain has to be something we can understand. There's a lot we can't understand. There is a lot that is computationally irreducible. There's a lot that we can't reach with our thinking or our science or whatever else. And so I think one of the challenges is it's the ultimate user interface problem. You know, kind of one of the goals of a standard piece of user interface technology, ux, or language design for that matter, is set up the things on the computer so we humans can understand them. So we humans just looking at them with our eyes, we can, you know, see, oh, there's that piece here, and move that and we press this button and so on. Now imagine the UX problem when you're directly interfacing to the brain. You know, we have the notion of graphic design where we're saying, oh, this is, you know, these are the kinds of structures that people have recognized are good for feeling natural in terms of graphic design. And for people to be able to pick out the information they want in graphic design, there will be a whole nother generation of capability that we need for essentially neural design, where the question is, you know, how do we present that interface in such a way that our brains can understand it? And it's not that different from user experience design, language design, I suspect, I suspect it'll be the same kind of thing. But for example, what is, I suppose, interesting about it is in graphic design we're leveraging the kind of typical experience we have of the world where if we had graphic design where there's random pixels lighting up on the screen, it's probably not going to look very good or be very easy to understand. But we're kind of doing things which imitate things we've seen in the real world. We have buttons that imitate things we can press in the real world. We have kind of lines that imitate things that we see in the real world. And so we're kind of our experience of the world is being played into this graphic design. Similarly, with language design, computational language design, we're playing into our experience of human language. We've got sort of words in the computational language that are kind of a riff on words in ordinary human language where we're playing into the fact that we already have kind of a vernacular way of just talking about things in terms of language. When it comes to direct brain connection, we don't immediately have that. We don't know we haven't, because we haven't been able to sort of externalize the language of the brain. We don't know what the kind of what there is there that we should be plugging into, so to speak. I mean, perhaps one step that may happen from direct brain interfaces is being able to display what's happening in the brain and be able to get it into something where we can, for example, use our visual system to try and interpret that. But that's, I think it's kind of the new generation of user experience design is neural design not ready yet to have happen. But that's a thing that I think will be sort of the story of what has to, What has to be, what has to be done there. Let's see. Paul is commenting that if we could completely understand the human brain, we could probably make a copy. Essentially fork the brain into multiple copies. Yes, probably so. I mean, this is one of the challenges is can you, you know, could you ever expect to scan a brain and say now fork it and get another brain that's able to do the same thing as that brain could do? I think that's a question. You know, for example, with a computer it is comparatively simple to fork a process running in a computer because the memory of that process is right there. In digital memory you just get to, you know, read it out, copy it. And this operation of copying is a non destructive operation for human brains. We don't really have a ready copying readout mechanism for memories. Maybe there'll be one one day. Maybe one day there'll be a mechanism that is completely non invasive that reads out human memories where you don't have to go in and you know, in principle you go and look at those neurons, the memories. We don't really know how the memories are stored, but probably they're stored in things like calcium channels that exist in the synapses that are the connections between neurons. It's literally more little dots of calcium channels on those synapses that form as a result of sort of a memory being created. At the smallest level, the memory is sort of the connectivity of those neurons and that's determined by those things like those calcium channels. And potentially if we just had the neuron right in front of us, we might be able to, even with some powerful microscope or something, take it apart and Say what was the connection to that neighboring neuron? Now the question is, is that something that we can do without taking apart all the neurons? There's sort of some hope that with things like optogenetics, where you get to add things to the sort of genetic setup of something that like jellyfish can produce light, then you can start to do things where, when this is happening and not only is it metabolizing, doing chemical kinds of things which we can't immediately detect, but it's also doing chemical things that produce light which we can, which we can see and use and have sensors that detect that. And so that's one kind of approach. But I think it's not, it's by no means out of the question that one day there will be the possibility of completely non invasively scanning a brain and saying, here are the memories in this brain, particularly if we understand how the memories are encoded. One of the things that's been sort of a feature of the development of technology and science has been a lot of effects where we said we'll never be able to measure that. It's just too small an effect. Eventually one's able to measure it. I mean, I always find it remarkable in for example, archeology that it's possible to start saying, you know, this meal that was eaten, you know, 5,000 years ago, what was in that meal? Well, we've got a few DNA molecules here. We know the type of sheep it was, that it was in the stew. We know, you know, the detail of what temperature this was cooked at, et cetera, et cetera, et cetera. That, in other words, that one of the features of the progression of technology is the ability to read out sort of more and more finer and finer detail of things. And so I don't consider it by any means impossible that there'll be a time when it's possible to kind of read out, sort of read out all the memories of a brain. Now, you know, once you have that, then then you can potentially have sort of a digital clone of the brain. You know, I have to say one of the things I've, I've certainly thought is that, that well, there are memories that are internally stored in the brain, but there are our experiences and the things we do. And I've for the last 30 something years been storing lots of my kind of experiences. You know, every keystroke I type and all those kinds of things, and all the messages I send and all sorts of other, all sorts of other things that I've sort of stored about myself and plus, you know, I do things like live streaming and so on, where I'm sort of externalizing things that are in my brain in some sense. And so it is not obvious to me the extent to which all of that sort of digital exhaust that I've been producing of keystroke logs and all this kind of thing, to what extent will be able to say, it doesn't matter whether you scan that brain, there's still enough externalized stuff that one can reconstruct everything that that brain would do, so to speak. And so that there's enough stored that given a thing with the same capabilities as a brain, that one could just sort of feed in all those things and have that brain, that sort of copy brain, be able to be in the sort of same state as the original brain. So let's see. A question here from Spare asking. Do you think neurons do that signal processing based mostly on discrete states or on the temporal difference between states? People are always making claims about this, and I've never really dug into this deeply myself, this question of to what extent what matters about a neuron is does it fire or not? Does it have that little electrical pulse that it generates or not? And does it do that in a particular millisecond? Does it do that in a particular hundredth of a second or whatever or not? But then people say, well, actually, what's important is that inside the. All the little dendritic dendrites, dendritic spines and so on that exist, all the little places where there are connections to the main body of the neuron, that there's a lot of complicated sort of signal processing and information processing happening in that whole tree of connections. Some people say that that's important. I don't know. I don't think we really know. Some people even say that the molecular details of, well, for example, the microtubules on the surface of the cells and so on are important in doing information processing. We certainly know that when neurons do their thing, they initiate protein synthesis, so they're actually producing molecules. Does it matter what's happening at the level of molecules? Or is that mere part of the process of cementing, in some rather direct sense, a memory in a neuron, for instance, we just don't know at what level these things are operating. We don't know whether kind of the time sequence of those spike trains is important. There are places where it probably is. So, for example, in our ears, where what's happening is, we have these hair cells in our ears that are being wiggled by sound waves that are coming into our ears. And there is. Well, actually even there, maybe, I don't know, you might think that the way a brain would do it is there's a sound wave when we talk, we maybe have a few thousand vibrations per second that are the relevant frequencies for human speech, for instance. And you might think, well, why doesn't the brain just make use of the fact that neurons can be firing 1,000 times a second or whatever. It's just like just take that directly in and just ingest that direct time series of when did the hair cell wiggle in the cochlear inside the inner ear. That would be strategy number one. Strategy number two, which is the one actually used, it seems by us, is arrange the hair cells and arrange the inner ear so that different frequencies kind of excite hair cells in different places on the cochlea. So you're kind of making something. It's kind of like an inverse piano, so to speak. A piano. The keys are laid out, so the higher frequency ones are on the right hand side and so on. What you're doing is the inverse of that. You're having something where the place where sound comes in and the hair cells on the, on one end are the high frequency ones, the hair cells on the other end of the low frequency ones. And our, at the level of the sort of hardware of our ears, we're doing that kind of frequency analysis to turn what was otherwise sort of these compression waves or whatever else happening thousands of times per second into something which is a spatial layout of different kinds of frequencies. So that's kind of a piece of evidence that the brain, at least in that case, isn't choosing to use just the straight compression, go straight in, sequence of compressions and so on, go straight into the brain. The brain is doing an analysis, a frequency analysis before doing that now, sort of analogous to what happens with, let's say, radio. In the case of back in the day when people had sort of ordinary radio receivers, you would tune your radio to be able to detect a radio signal coming from a radio transmitter that was operating at a particular frequency. In modern times, there's the idea of software radio where you're really just ingesting the whole signal and you're letting the processor of the computer take it apart and say, oh, there's a part that corresponds to this frequency and that frequency and so on. That will be more something where you're really directly using the sort of the sequence of amounts of energy coming in onto your antenna or whatever else that will be like the brain from our ears directly, using the wiggling of the eardrum or whatever, we don't actually do that. We spatialize it and feed that into different nerves in the auditory cortex in the brain. So that's kind of a piece of like circumstantial evidence that our brain is not set up so much to use the particular time sequence, at least on the level of what's happening in speech now in terms of whether it matters what that time series is of you go click, click, click now and then a few milliseconds later you're clicking differently. I don't think anybody knows whether that's important or not. And like most things in biology, one of the frustrating things about biology, sometimes less so molecular biology, but biology in general is that it's always more complicated than you can possibly imagine. There's always more different effects going on. And, well, it's mostly this, but there's a little bit of that and so on. It's funny because I have friends who are into biology, medicine, things like that, and they sometimes they're confronted with questions that are really questions of physics and they just don't have the same. They have an intuition that always says it's going to be complicated. There isn't just a slam dunk answer. And in physics there often is a slam dunk answer. There is no signal propagating through this particular, you know, copper box or something. Zero just doesn't. There isn't any. It's not like in biology where you say, well, there isn't really any way in which some genetic information can go back from the organism to the DNA. Well, when we say there isn't any, there is some, it's just not very important. And in biology there are often these kind of exception cases. And so I think when one says, oh, it never matters what the temporal sequence of the spike chains is, I bet that's not true. I bet there's a case where it matters or some little way in which it matters. You know, if you, if you change it too much, something will go wrong and so on. The, Let's see, question here about. William comments. Even though brains are different, don't they all implement the same underlying ideas? Doesn't this point to some platonic realm of reality? Oh boy, lovely philosophy question. I mean in to what extent is there a sort of a there there for concepts? To what extent is there a robust notion of a concept independent of its implementation in the brain? One of the things we learn from computation is that there is a robustness to abstract things. That transcends the details of how they're implemented in hardware. It doesn't matter that one person has a Mac and one person has a PC. They can still run the same Wolfram language code. They can still be doing the same kind of computational, have the same, represent the same kinds of computational things, even though the underlying hardware is different. And I'm sure the same thing is true with brains, that this universal computing idea, that even in different hardware you can implement the same ideas, that's what's happening in brains as well. That's why we can have a common set of abstract ideas, is because our different brains are all sort of universal machines that can all implement those same abstract ideas. And the choice of which abstract ideas to implement, well, that's where it gets interesting. Because that's where kind of civilization and knowledge and sort of paradigms and things come in. Because that's what determines of all the infinite things we could implement with our brains, the actual concepts that we choose to represent in our brains are the ones that are the ones that we've sort of culturally learned we care about. And so that's the place where we're kind of commonizing. That's the place where things are becoming in common, is that thread of kind of shared cultural knowledge and interest in things, even though the underlying hardware implementation will be different for every brain in a very abstract way in what we've studied with this thing we call the ruliad, which is kind of the ultimate limit of all of physics and mathematics, the ultimate limit of all possible computations and so on. Maybe I'll. One of the things that happens there is one is asking. Different points in this ruliad correspond to essentially different points of view about how we think the universe works, different ways in which we represent the goings on of the universe. And so one question is if you want to travel from one place in the ruyad to another, you want to sort of change your point of view about how things work in the world. How do you do that? And what kinds of things can transport from one place to another? And what seems to be the case is that particles, we're used to particles traveling in space, like electrons and photons and things like that are these kind of lumps of existence that travel unchanged from one place to another. The electron starts here and it moves somewhere else. The structure, the underlying structure of the universe, the underlying structure of space might be very different in those two places, but yet there can be an electron, this lump of existence, that can go from one place to Another, in some sense, unchanged. So when we think about the ruliad and we think about all these different minds kind of embedded at different places in the ruliad, and we imagine what can be transported from one place, one point of view to another. What can be transported unchanged. What's the analog of a particle in rulial space? I think the answer is a concept. That is a concept. The concept of a cat, the concept of happiness or something. These are things which are represented differently in each individual brain, to each individual mind, but nevertheless, they are transportable. They are like particles that they can move to a different brain and be interpreted in that other brain. And so I think that's kind of the analog. That's the thing that. That it is. And the fact that there is this world of sort of a particle physics of ideas, that's the thing which I suppose transcends the. The, you know, that's the thing that is kind of like the Platonic realm of pure ideas. Now, what's interesting to understand is just like we imagine there's a particular way physics works with photons and electrons and all that kind of thing. What are the global rules of this kind of conceptual world of how can concepts interact, how can we make a description, so to speak, for that? And I think what we'll discover there is that a large part of that story has to do with how our minds and brains actually work. That is that it isn't the case that sort of anything goes into the types of particles, the types of rule particles, the types of concept particles that we deal with are ones that for whatever reason our brains are set up to be able to detect. You know, it is the case that we're very familiar with photons. We didn't know that they were made of, you know, that light was made of individual element pieces of energy like that and so on until 100 years ago. But the fact that there's light and we detect light and so on, that's very familiar to us. If there was some strange kind of particle, that's some dark matter particle or something, that, although I'm decreasingly convinced that dark matter is a thing, but that's a different story. But in any case, if there's something like that, where it's just some completely different sort of sector of physics, we don't happen to have detectors for that that emerge from our biology. And so we completely don't know about that kind of world, that's sort of a separate possibility from the things that are part of the net of concepts. That we already know about. Let's. Yes. So Tiny is commenting. One of the issues of being able to read and decode a memory is that someone will have to. Will have the ability to write artificial memories in a brain. Yeah, well, you know, it's a funny thing because, you know, people watch movies, people read books of fiction, people have dreams, for example. These are all things that didn't really happen in some sense, and they are going into our memories. And somehow we managed to deal with that and not get sort of irreducibly confused about what's real and what's not. I don't know what will happen when kind of there's sort of artificial digital memories, and it's kind of like, well, that seems like a memory. You know, is that real? Is that a thing that was something that happened in a dream, for example? I don't know whether we'll have an easy time distinguishing those or whether whether it will be possible for the digital memory to kind of masquerade as a real memory and then what consequences that has. And that's a very. You know, this is a very complicated ethical thing because it's kind of like, well, I want to remember. You know, the nature of us is based on our memories. If you start messing around with what those memories are, you no longer have an us, so to speak. You no longer have the same person in some sense. And. And so what does it mean? And at what point, you know, how do you kind of. Well, you know, people make all kinds of decisions about themselves. Sometimes they're ones that from the outside, look sensible, and sometimes the ones that from the outside, look completely crazy. But, you know, the decision to kind of change, you know, the kind of sort of make a change. Oh, I don't want to remember that. Let's just erase that forever. See, again, I don't know how that will really work, because there's. There's externalized versions of memories, and, you know, you'll kind of remember that you remembered it. And it's. It's all complicated. I mean, some of this has been addressed in. In science fiction. I noticed Prabh is commenting about a Turing test for memories like in Inception. Yeah, there's this movie Inception, about, you know, dreams and dreams within dreams and. And things like this. I found that movie super hard to understand. I. I may be. I may have the deficiency that I'm one of these people who very rarely remembers dreams that I have, which I consider in some ways fortunate, because then I don't have to have this confusion of did it happen for real or did it happen in a dream? I don't have that question. Anyway, I think that the, but this question of is it a real memory or is it not a real memory? Very interesting thing to wonder whether, whether one will be able to tell. Is that memory a memory? Was that a memory? It's just like, you know, you see a, a piece of text that's been written and somebody says, oh, it's written by one of these neural nets that is a, you know, a text generator. And you say, really? Or was it written by a person? And you kind of look at it and sometimes you can really plainly tell, and sometimes it's a little bit harder, at least to tell. Or, you know, this piece of artwork, was it made by, was every step of it made by a human artist or was it all aggregated by some neural nets or something like this? And I suppose you could ask the same thing about. And you could say, can we tell, can we, can we tell the difference? And you know, the, the bad part for us humans is, look, there are places where we're not going to be able to tell the difference. There are places where it's just kind of, it's kind of leveraging, it's following the way that we humans do things. It's saying, look, I've seen a million things that are what you humans produce. I'm going to make one that's just like what you produce. And you'll look at it and you'll say, oh, that looks like something a human produced. Because the neural net, the machine learning system, learned from a million things that humans had produced. So, yeah, I think it's something where, unless. Where it's like when you're showing things that are just like humans produced up to a point, it's going to look kind of like it's going to look just like what the humans have produced before. Now, when it comes to things like memories, it's an interesting question whether there'll be sort of small scale pieces of memories that have the right texture, that say, oh, that seems like a real memory. I think our dreams, for example, are probably, you know, there are small fragments of memory that kind of look right. They have the right texture. But globally, the whole thing may make no sense. They're things that come from sort of random excitation of the brain and we've excited some particular memory. And right around that memory. Oh, yes, it's coherent enough that we can tell that's a, you know, that's related to a memory of some you know, some giant tortoise we saw when we were 5 years old or some such other thing. And the, the, you know, and it's, it's coherent up to a point, but somehow the tortoise then segues, and we tend to make these, these connections, you know, then segues into. Well, it's actually an airplane type thing or something like this. And, you know, our brains do pretty well at kind of, you know, putting that merge in there. And so will the AIs do well at doing that. And so locally, the thing may make sense now when you say, is there a big picture? Is there sort of a big. There. There. There may not be. That's, that's the thing that is much harder and that relates much more to the thing. That is really not what AIs intrinsically do. I mean, AIs intrinsically are a piece of automation that takes kind of human goals and tries to sort of fill in how to actually execute them. But if you say to the AI, hey, what do you intrinsically want to do? You know, you're just a computer. What do you want to do? And the computer is either somebody programmed it to say, you know, I want to go to the moon or something, or it's just going to sit there. And it's a computer. And we humans, by virtue of both our biological construction and our experiences, end up with these. And I really do want to do this or that, whether it's go to the moon or something else. And it's, you know, I think that that is something where that's not intrinsically a machine AI kind of thing to know sort of what's the, what the purpose is. And I think when you get to these sort of larger scale structures, it more relates to what purpose is going on. And I think that's the place where you start to see kind of almost the Turing Test for memories and so on. I mean, I suppose that in some sense, and I don't know to what extent a lot of the sort of Turing Test ideas and people who use WolframAlpha to connect to Turing Test bots and things like this, a lot of what's going on there is pretty small scale, is the texture, right. Of answering individual questions. But when it comes to the big picture, did this make sense? I just had a half hour conversation with this thing. Did it really make sense? Or is it just a bunch of random texturally correct pieces that were stuck together? That's probably where the, where the test of kind of something real comes in. But yeah, it's an interesting question. What would one be able to tell with a digital memory? What, you know, does this look real? It's just like, you know, when you have sound effects in movies, you know, things can sound really real, even though, you know, it's actually just somebody knocking two pieces of wood together and so on. But it just sounds real as, you know, I don't know, a horse, you know, galloping around or whatever else it is. And you know, there's the question. And when we have sort of visual things, there are things that can look really real. We happen to be very sensitive, for example, human faces where it's been really difficult to make a realistic looking human face that is produced sort of in an AI way, although it's getting, getting easier to do that. And I think that's a question of what will it feel like for digital memories? What will we say, oh, that's really crummy, that's an artificially made thing versus that has the texture to be a convincing memory? I don't know. Let's see. William is commenting. Perhaps the only difference between dreams and reality is a matter of degree. Perhaps it just depends on logical coherence. Once the coherence is larger than what the brain can be aware of, it is considered real. It's an interesting claim. I mean, the claim would be that the world is a coherent place and we recognize that kind of larger scale coherence, whereas when we're having internal thoughts in a dream, we're not being driven, that's not being driven by the external coherence of the world. That's an interesting thought. And I think one of the things that is obviously the case is that our experience of the world and the world as world as we experience it is a fairly coherent place. You know, I've been, been sitting in one place for the last hour or something and nothing dramatic has changed. You know, it's not the case that, that the, the walls of the room have disintegrated and been replaced by some flowing, complicated, you know, configuration of this, that or the other. And you know, the world is, is kind of maintains coherence. Now if we were in an environment, let's say we're in some kind of virtual reality where there isn't that kind of coherence. I wonder what that feels like. I don't know. I think that a lot of what's done right now in VR is in sort of the metaverse type direction is, let's emulate, let's have sort of a slight tweak on experience as we currently have it. But not. Let's just go crazy and have something where there are these just these what seem to us like random pixels. Pixels being generated by some algorithm that is full of computational irreducibility. And we're just being in. You know, we're being submerged in this kind of artificial world that does not have the coherence that we associate with the physics of physics as we perceive it. An interesting question. What that will feel like. My guess is it will feel incredibly disorienting. And my guess is that it's kind of a. That it's not good for your brain to expose it to that. Actually, I'm surprised people haven't done those experiments. Maybe they have, and I'm not aware of it. That to try and sort of live in an environment that just doesn't have coherence, where just random things that seem random to us are happening all the time, where we can't make sense of what's going on. My guess is that one kind of loses it very quickly, that it's really hard, that one will get very disoriented, very confused, almost kind of not capable of maintaining sort of the consciousness that we normally have. I think it's an interesting question, actually be an interesting experiment to do. I'm not sure I'm the one who's signing up to go and hang out in the incoherent virtual reality. That seems difficult. All right, well, I think I need to get going here, But a lot of interesting discussion here, I have to say. Somebody's mentioning dark matter, dark energy. I've been studying. I think I said this too many times. I've been studying the second law of thermodynamics, law of entropy increase, for the last several months, actually, because I've realized that some things we've done in our physics project kind of open up a bunch of things that people have been confused about, including myself. I've been confused about these things for 50 years. The world in general has been confused about them for 150 years. But in any case, one of the things that I'm really struck by. In the early days of the development of ideas about thermodynamics, there was this idea of the caloric theory of heat, where the idea was that heat is a fluid that kind of suffuses all substances. And that's what heat is. As we know now, heat is, you know, the motion of molecules and so on. But I just have this tremendous image of dark matter is the caloric fluid of modern times. That it's not what you think it is. It's not something which is described. You know, at the time when people are talking about caloric fluid, people knew there was air as sort of a fluid and there was water as a fluid, and fluids were a thing that was a sort of a description for how things work in the world. They didn't think of the idea, or some people did, but mostly they didn't think of the idea. It's motion of molecules. And I think the same is happening probably with dark matter and so on. The people say, well, it's, you know, what we know about is particles, it must just be other particles. But it's actually probably something which takes a bit more creativity and imagination to realize. And our physics project should be able to tell one what kinds of things might be out there that are not what you thought were there. And so that's one of the things I hope to work on soon. Parker is commenting here. We've co evolved our environment so it should be coherent to us. But if we inject things into our environment that we haven't co evolved with, we'll get confused. Yeah, it's a good point. And just to finish on this, I mean, we build our environment and then we kind of, you know, we decide windows are rectangular usually or whatever. We don't. When we. And this is one feature of, for example, modern architecture is this idea, you know, for a long time in architecture, for example, we built things that were kind of the way that it was easy to make the construction work and the way that the. So the physics of the thing would not cause the structure to fall down or whatever. And sometimes we built things that would be kind of reminiscent of features of human form or the natural world or whatever else. And then we have kind of modern architecture and modern materials where you can make any shape you want, you can make it work any way you want. And it is an interesting experience because that type of thing, I think the general experience people have is it's a bit disorienting sometimes. You're, you know, there's a certain set of things you're familiar with and they're not disorienting partly because of familiarity, but partly because they are. They are the things that are part of the natural world. And things like this, when you go kind of off the reservation and you're kind of in this, in this world where anything goes, it tends to be. The experience that we tend to have is one of disorientation. Now some people say that's good disorientation because it kind of gets you to think differently. Other people say that's uncomfortable disorientation and so on. But I think it's and it is true that we we tend to create things. I mean if that some particular kind of modern architecture with some particular kind of swirly thing in it became the standard we would then get familiar with that and that would become the thing on which we base our thinking, our language, et cetera, et cetera, et cetera. And I think the and yes that sort of it's an interesting circle of the things we come up with to think about are the things that then become things that we work with and that we build into our environment so those become familiar and that that becomes the thing that is our sort of comfortable experience and so on. All right. Lots of interesting topics. Thanks very much for for all those questions and comments and I look forward to doing this again and thanks for joining me and bye.