 Hey folks, I'm Dave Atkley. You know, I'm old now, but I still remember as a kid how often adults were totally full of shit. I mean, it happened a lot. Teachers, my parents sometimes, assholes on the street, adults expected kids to believe whatever they said to them. And if you pointed out that something made no sense, they would just change the rules. They'd say, oh, that's different, that doesn't count, that's an exception, that's the exception that proves the rule. And you know, my personal favorite, you'll understand when you're older. But books were great. Books doesn't dumb it down, because books doesn't know who's reading it. So once you get into the adult stacks in the library anyway, there's just tremendous amount of stuff. You know, so I read a lot of stuff. I liked science fiction, you know, I found one of my original ones, you know, I think I got this on my allowance, 50 cents, winner of the annual Hugo Award, in case you didn't know. But basically, you know, if it had rockets or robots and genius kids in danger, you know, I would just suck it up. I was all over this stuff. And you know, I read the actual nonfiction too sometimes. And you know, part of it was, I was trying to find, you know, an understanding of things. I was trying to find an answer. So you know, beyond just looking for page turning stories, I was looking for something that explained everything with no bullshit and no changing the rules halfway through. So these days, I would say I was looking for a theory of everything, you know, something that would have satisfying answers to, you know, like the big questions, like, you know, why are we here? Where do we come from? What should we do? And the search didn't go all that well. You know, it certainly turned out that there were plenty of folks who write books that were basically BS, because a lot of people wanted to know this kind of question. But the end, you know, even in the good stuff, even in the science and so forth, there were always exceptions and little weaselings and so on and so forth. So I got through it all somehow and now I'm old and I'm supposed to be a freaking adult. You know, so great. But stuff has settled in in my head that seems really, really obvious. You know, like, I'm a computer nerd. I've been a computer nerd probably at least since since that guy, if you can count like, you know, plastic toy computers and stuff like that. And so I used, you know, computer concepts and language in the way my thinking works. But there's stuff that seems like so incredibly obvious. And so I keep trying to say it to people, at least to say it to other computer nerds. But I think it's actually more broadly applicable beyond that. And, you know, so far, I'm not sure I'm really getting it across. So I'm going to do it again today. I'm going to try to lay it all out. I've taken it that my job is to, you know, say it as best I can and to keep saying it until I hear it coming back at me. So, you know, I've got way too much to say and, you know, hopefully the technical issues aren't screwing it up too bad. Hopefully they're not screwing up the local recording. We'll see how it all goes. But the point is, this is for you guys, you know, I'm sorry I'm late. It worked out okay. So, let's see what you think. All right. So, yeah, eyes on the prize. Now, one of the things that bugs me about people that, you know, say they're looking for the big picture or trying to get a fresh start is it seems that they go ahead and they accept, you know, existing limitations and assumptions for what the everything, or in this case, what the everything might be. And that seems silly to me. I mean, I feel like it's like Star Wars, right? With Luke Skywalker going, you know, everything is more than you can imagine. And Han Solo going, I don't know, I can imagine quite a bit. And that's what I'm thinking, right? If we're going to have a satisfying theory of everything, then, you know, we should have, like, you know, whatever this theory, it should make everything make sense. You know, whatever happens, yeah, I see. That makes sense. That makes sense. We can't. Even something that hasn't happened, we ought to be able to predict what would happen if it did. If I did this, it would be this. If I did that, it would be this. And it would always be there. And basically, it would give us our best move in every situation. And, you know, spoiler alert, we can't have this. But my secondary demand is if we can't have this, we better have a damn good explanation. Why not? And we should have the best alternative. We should get as close to this as we can. But, you know, we're going to have to deal with the fact that the truly satisfying theory is not going to be available to us. And we're going to be kind of in a, you can't get what you want kind of situation and just deal with that. So here's my big questions that I've made up. We'll test, this is our grading rubric to test theories of everything for today. So where do we come from? Why are we here? What makes us special? And what should we do now? I mean, if we get practical, you know, working, trustworthy answers to these, that would be a theory of everything that I could get behind. So let's see how we go. All right. So first step is to take a look at existing theories of the big theories of everything. I'm going to arrange it as to take this huge hack job of taking all the concepts of humankind thought and clumping them together into two piles. Number one, that's, you know, mind and religion and consciousness and God's soul, free will, all that kind of stuff on the one hand. And on the other hand, it's science, you know, physics, chemistry, biology, cosmology, neuroscience, you know, machinery, levers, pulleys, incline, plane, everything, electrical engineering and so forth. And, you know, each of those is they're very different than each other, but they are sort of a complete worldview. So I want to take a look at each of those in turn. And, you know, so there's this germ theory of truth. I don't know, I sort of made it up at some point. I'm sure it's officially something else. But the idea is, you know, there's a germ of truth in every idea that's seriously proposed. No idea can capture it all because, you know, an idea is just one little thing. So you can't even really pretend you understand an idea unless you can say what it is, why it's good, and some kind of limitation on it. And, you know, I think the defined defendant attack is a useful technique. Well, for one thing, because it separates define and defend. I mean, when you have partisans, when you have fanboys, they tend to smush together the defend and the define. But we'd like to pull that apart and have as neutral point of view discussion of what it is independent of why it's good. Similarly, depending on which side they all come out on, you know, the attack might be pretty weak tea, right? You know, damming with faint praise or praising with faint dams depending on whether we're attacking or defending. So that's the whole idea. Let's try this out on our existing theories of everything. So mind, religion, consciousness, God, soul, all that seeks to explain our origin, purpose, and identity. You know, where do we come from? We came from the God. We came from the gods. We were living on the back of a turtle. It's living on the back of a turtle. Whatever. Something like that. You know, Descartes is in here as well. You know, I think therefore I am, you know, it's in the morning, and he's having his breakfast and a little cup of coffee and a brioche, and he's like, you know, ooh, I'm thinking. Therefore, that means I exist. I'm actually in here. I'm having thoughts right now. I'm here again. And that's the way we all work, right? I mean, it's like, you know, we're in here. And if that proves that we exist, well, that's a great start. So all of this stuff all goes together. And this is, you know, this is the original theory of everything stuff. We've been having narratives, stories, explanations like this, as I assume, as long as we've been talking to each other. So there it is. What is good about the mind theory of everything? Well, it's ancient and widely held. Now, when I'm wearing my kid hat, you know what I'm saying, you know, ancient is a good thing. But widely held is really important, because it means if we can speak into that language, if we can fit into the framework of that theory of everything, then we could potentially have a lot of impact. We could potentially reach a lot of people. And, you know, in that same spirit, you know, it's got the soul built in. It's got the self-real built in. It's easy to get started with it, because it starts with us. And in fact, you know, just, I mean, in the same Descartes way, you know, I think, I think, I forget, they had their very first idea. And these things essentially are built for the rubric, which is, I mean, it's kind of like teaching to the test, which doesn't exactly sound like a good thing. But we'll come back around to it. And they all offer some kind of notion of free will. You have to decide what to do, but some kind of guidance about what good things to do are. So, let's take a look at the rubric. Where did we come from? Well, you know, it depends on exactly what tradition you're in. It came from the mind of God. We came from the eternal cycling of the universe. Why are we here? We're here to serve God. We're here to achieve enlightenment. What makes us special? Well, you know, we have dominion over the fish and the plants. And you know, we're supposed to name everything. In fact, you know, we're in charge. Or perhaps what makes us special? Well, you know, nothing good. We need to get over that kind of attitude. And, you know, what should we do now? Well, you know, we should be good, help out, pray, put money in the basket, stuff like that. So, on the other hand, one of the problems with the mind theory of everything is a lot of the stuff is pretty unrepeatable. You know, the stuff, the thoughts I have there, you know, they're buried in my head. They're like super secret. And, you know, how do I know my experience of the red color when the word attack is the same as your experience of the red word and the color attack and so on. And by a similar token, you know, the theories of ourselves, of God, of the origin of the universe are completely unfalsifiable. They're unprovable in the sense that there's nothing that necessarily would absolutely make this thing be true. But they're also nothing that could ever say it's not true. And, you know, it's finally important because it's not falsifiable. All of these things require faith. Now, that's not necessarily a bad thing, but it means at some point we start saying stuff. We start repeating what we've heard. We start repeating our learnings, even if they don't sort of completely make sense. You know, and a lot of religions are pretty internally inconsistent, you know, and that's just one of the mysteries. And certainly, you know, different religions are extremely inconsistent. And, you know, in the history of our species, that's occasionally caused a little problem. But the problem I want to talk about here is that once we have faith, once we just said, you know, I believe I will say it, you know, whatever it is, it's turtles all the way down like that, then we are, you know, we gave over a certain amount of our agency, a certain amount of our critical faculty to be faithful like that. And that can be misused. That can be corrupted. And so that's a problem with the mind. It's a problem with anything that's based on faith. Okay, number two, science, cosmology, all of that. This is the challenger. Physics, TOE seeks to explain all the forces of the universe in one master theory. Preferably they would like to get it down into one equation that shows how everything relates to each itself. They've gotten it down to two, which is pretty amazing. The theory of general relativity deals with big heavy stuff. The theories of quantum mechanics deal with small light stuff, and they each do really well in their specific areas, but they don't quite talk to each other. And, you know, this is the much younger theory of everything. And in fact, you know, this is partly where the phrase theory of everything came from out of physics. And it was, you know, as often as the case, it was originally used, you know, sort of sarcastically, but then eventually it was co-opted by the fanboys. What's good about the theory, the physics theory of everything? Well, it works. It's got huge explanatory predictive power, and it has this interlocking aspect. It's sort of a mutual truth fact that if you accept that the things fall because of gravity, well, that also means that you can predict how a ball is going to throw an arc when it's being tossed, and a rocket is going to shoot up in the air, and so forth. And if you try to make an alternate explanation for any one of those things, you're going to come up against the fact that all the theories interlock. And so it becomes, it's like a viral license. You know, the whole thing, you know, now there's plenty of mushy-gushy stuff in science writ large that we haven't made any work there since, but there's a tremendous amount that's really well understood. And, you know, science writ large, physics writ large to include mechanics and chemistry and electrical engineering and all the rest, underpins most technology that we depend on, that we live with today. And, you know, not to put too fine a point on it, but in the history of our species, you know, physics writ large has made some people a tremendous amount of money. There's huge unbelievable, you know, world-changing innovations in medicine, in weapons, in computers, and so on. On the other hand, if we try to take the physics theory of everything and say, how well does it do on the rubric, we start to get into trouble. Now, I found a couple of quotes to give us the flavor of how physics comes at this. The first one, this is from Steve Weinberg's book, The First Three Minutes. This is basically the tail end of the whole book of the end of the epilogue. The more the universe seems comprehensible, the more it also seems pointless. Okay, kudos for honesty. But as a philosophy of life, it's kind of a drag. The effort to understand the universe is one of the few things that lists human life above the level of farce and gives it some of the grace of tragedy. Okay, you know, and this is a real problem. You know, as I was growing up and I was reading the science and trying to figure stuff out, you know, I got to this. I don't know if I had it stated quite so clearly. But you know, it's a big bummer. There's also another one. I got this just from a popular science article when I was searching for stuff about the theory of everything. And the journalist says, you know, if we finally crack the theory of everything, will that be the end of physics? Duff disagrees. That's Michael J. Duff, who is a physicist, a string theorist that actually was working, he's done a lot of stuff a little bit controversial on unifying all this stuff. And he says, you know, after we learn the rules of chess, we can finally start playing the game. And that seems to make sense, right? You know, they've gotten it down to two. And if we want to get it to one, we just have to wait until they finish the job. And then we'll have the answers, then we'll be able to, you know, tear everything down to its final ultimate pieces, whatever they are, you know, Posit, Gravitro, Bazon, Bangers, you know, whatever they end up being called. And then we can put them back together according to the rules, and we can answer our questions. We can figure out what we want, except we can't. And this is where computation just comes right in. And it's because of chaos and computational complexity, which I'm calling C3 just to sort of sum it all up. So chaos, the technical notion of chaos is there are certain setups in the world. There are certain physical situations where, you know, you see stuff, they're all set up in some position, and you'd like to predict what's going to happen, where they're going to go from there. And it turns out that, you know, if you have any error at all, no matter how tiny, in how you measured the original setups, then over time that error will get bigger and bigger and bigger until you have no idea where anything is. That's chaos. And that's really bad, because, you know, we have no ability to measure anything truly exactly to the infinite precision, whatever that would be. And it's even worse than that, because, you know, well, now, to understand, it's not that everything in the universe is chaotic. There are plenty of stuff in the universe that's very well behaved. But if we're going to be dealing with everything, then all it takes is one chaotic system in the world, in the universe, and we're screwed, as far as the theory of everything is concerned. But put that aside, even if we manage to say, no, there is no chaos, computational complexity is going to come and kill us anyway. The idea is, you know, there's just too many combinations of things. We're building up these micro, you know, coolatrons, whatever the particles are, we're putting together according to the rules, and there's just too many ways to put them together that might work, might be what we want and might not be what we want. And we're going to, the universe is going to burn out before we even try the tiniest little fraction of the possibilities that there are. So, this is a little bit of a sidebar. No, we're okay. But I wanted to go into it. There's, from the outside, there's a couple of phrases, you know, computational complexity, you know, that's word, and there's another word, computability, that sounds kind of similar. But from the inside, they are very, very different, as different as good and evil. Again, not to put too fine a point on it. And why are they so different? It's because computational complexity takes into consideration the resources that are required to do something. Computability does not. So, you know, things like, you know, people that have a, you know, computer science education, yeah, they all know about Big O and Peagles and Peas, all these famous things. And they know about Turing machines and universal computation, undecidability and stuff as well. But these things are totally, totally different, and we need to tease them apart. And, you know, so basically, you know, computability has two kind of nifty little results. And, you know, nifty little result number one is that you could build a single machine, and just by giving it a different program for the exact same machine, you could compute anything that is possible to compute. And that's the universal computation idea. And the second idea is that, you know, you'd think if you had, someone gave you a particular machine with a program, you ought to be able to look at it and see what it's doing and figure out how long it's going to take to finish. And say, okay, yeah, I see that that's going to stop, you know, eventually, or it's not going to stop eventually. But it turns out that you can't do that. You can't figure out whether a program in general is going to stop any quicker than just running it until it does stop or running it indefinitely like that. And these things both come from the same side. You know, how can you be a universal computer? You can be a universal computer if it doesn't matter how long it takes. If it doesn't matter how much space it takes. If you had any limit on how much time or space or energy you have, then there's no such thing as a universal computer. It's a silly idea. So, bottom line. Computational complexity is useful. It gets used all over the place in real and implicit terms. And, you know, in libraries that we just get to use indirectly, we don't have to actually do the work ourselves. Whereas, computability has these two cool little ideas, and maybe a couple others, but that's about it. It's a dead end. And, you know, so it's a little unfortunate, right? Because, you know, people can get caught up in thinking computability is cool. But then really you end up kind of with a dead end kind of science instead of trying to focus on how things work in computational complexity. So, but still, even just focusing on the computational complexity part, we're still screwed from a theory of everything point of view. There's, you know, 10 bits as 1,000 possibilities, 20 bits as a million possibilities. The possibilities just grow up way too fast. Computational complexity tells us that. So, we're never, we're never going to be able to compute by taking, tearing things down to the tiniest little pieces and then building it back up according to the rules. And be sure that we found the best move in any reasonable situation. We are screwed from the point of view of a satisfying theory of everything. So, how does the physics theory of everything actually handle the rubric? You know, well, where did we come from? Well, you know, we came from the Big Bang. I'm okay. Why are we here? Them's the brakes, buddy. We're here because it's a lower energy state than us not being here. It's here, you know, I mean, there's this one principle called the anthropic principle that says, you know, if we weren't here, we couldn't ask, why are we here? Which seems a little bit of a trick, right? You know, so given that we are here, it doesn't say much more than that. What makes us special? You know, absolutely nothing. Screw you. Or, you know, from more in the sort of Buddhist tradition. What makes us special? Nothing. And that's good. So depending on how you look at it. Now, you know, if we read between the lines on Stephen Weinberg's comment, you know, the only thing that made us special was that we did physics. That's what got us to the level of tragedy instead of force. What should we do now? You know, whatever. Knock yourself out. And again, you know, obviously we should do more physics to try to put those last two theories together, you know, got the eyes across the teeth. So the mind theory of everything, the physics theory of everything, we're going to put those together in the living computation theory of everything. And now once again, you know, all of this stuff is, you know, it seems to be, you know, incredibly obvious. So, you know, forgive me if it seems totally boring. But like I said, I don't hear it coming back at me as much as I think it's worth. I think there's some value to it. So let's give it a shot. So the phrase living computation I've been living with for a couple of decades now. And this was the little tagline for it. In the end, living systems and computational systems turn out to be the same thing. They may not seem that way now, but that's because we've got some wrong ideas about what machines and life are really are. Now, I've come up with lots of different ways, lots of different takes on this. But one of them that I used fairly recently is this circular definition that I want to go through quickly. Life is a physical system that works to preserve itself using computation to decide the work. Well, what's computation? It's a physical process that selects meaningful actions in context. Well, what's meaningful? It's a physical action that tends to preserve life and that closes the loop. Life uses computation, computation is meaningful and meaningful. Things are meaningful because they help preserve life. Now, you know, so it's completely circular. So, you know, it's like completely pointless, right? So I want to come back to that in a little bit. But I also want to notice before we go on the fine print here, life is a physical system. Life is how we describe a physical system, okay? And so there are these two very strangely related ideas. There's this, you know, life is a physical system. And people say stuff like that all day long. At this point I call that living in the land of is. When you're talking about this is this, that is that. And people are saying this is A is B and someone else says no, A is C. And you're having all these arguments about the, in the land of is, about what the is-ness of A, B, or C is supposed to be. And that's fine. But that's different than saying life is how we describe a physical system. At that point, we are talking about language. We are talking about a string of sounds, a string of letters, a string of marks of ink on a piece of paper, whatever it is. It's not an actual living thing at all. It's code. It's a program. And having those two views of an idea that on the one hand we could be in the land of is, life is a physical system. And on the other hand, we could be our wearing our developer hat saying, no, life is how we describe a physical system. And so forth for the other ones. So, bottom line, based on the germ theory of truth, wait, the germ of truth theory. Wait, did I get that wrong last time? I probably did. We are not one specific thing. We are many things. And among the many things we are, one of the things we are is not near machines, not fixed rigid machines, but programmable machines. And the physics TOE talk, it describes our hardware and the mind theory of everything is talking about our software. And if we are going to make sense of who we are, what we are, how we act, what we're going to do, we have to have both. Like that, you know. So, and that's it. That's the idea, right? All details of what kind of programmable machines are, you know, to be determined. But, you know, if you are any kind of computer nerd, seeing us as programmable machines, you know, right? And, you know, I feel the need to emphasize this, right? I mean, you know, so there's software that's got, you know, things like culture, books, education, parenting is all full of software. We've also got hardware that has our bodies and the world around us, machinery, performing, building, work, and so forth, right? Hardware, software and hardware, culture and embodiment, software and hardware, control and work. Yeah, you know. Now, merely being obvious doesn't make it useful. So there's certainly a question, you know, what good is it to use all this computer nerd jargon? I mean, you know, sure, you can do it. It's cute, maybe. But what makes it any different than any other theory of everything? And so part of the answer to that is our last major topic, although we're sort of kind of wound into the still going through the defined defend and attack on the theory of everything. But it's about the importance of being obvious. So let's deal with that now and then come back to other topics and about the theory of everything. So one way that I'm going to try to defend the theory of living computation theory of everything is by attacking it from various directions and then fending off the attacks or at least I'm going to try. And so the first one is attacks from traditional computation, you know, the sort of button down, you know, the people that somehow always end up being reviewer number two whenever I submit a paper. And from their point of view, the trad comp viewpoint says, you know, hardware must be digital and deterministic, and software must be perfectly unambiguous and precise about what it's going to do. And if you don't have that, if the hardware isn't deterministic, if the software is ambiguous, you don't even have a computation at all. You just have some kind of garbage. As far as the trade comp folks are concerned, but live comp takes a very different viewpoint. You know, yes, digital and deterministic is a way of doing computation. But that's just a beginning that's just one way of doing it. It's training wheels in computation. It's the cradle of computation. And live comp says the destiny of computer science is far beyond determinism and deterministic execution. And, you know, I think it's exciting. But, you know, if when you're stuck deep, deep, deep in deterministic execution, you know, this kind of ideas is threatening scare. So there is a natural question that comes up that, okay, if we're going to throw out digital and deterministic execution, you know, how much of computation still means anything. I mean, that that's the implication that trad comp says, no, we can't do that. But my feeling is, is that a lot of concepts more general ideas of familiar computational ideas, maybe not completely traditional carry over. They just have to be kind of reinvented a bit. And one big area is software engineering software engineering interpreted generally writ large definitely remains in the living computation framework. So there's a thing called an application program interface. And again, this is this is bread and butter for computer nerds, but for people on the outside, it's, you know, just more jargon. Typically, when people are talking about application program interfaces, they spell it out API, I am trying to get myself to pronounce it instead to say happy, an application program interface isn't happy. And but what it is, and you know, I'll probably screw it up and spell it out, but I'm working on it. What it is, an appy is is like a mad lib, or it's like a cookbook of mad libs, you know, take one unit of vegetable and, you know, one unit of spice like that, you can fill these things in. So an appy is this combination of fixed parts, and these sort of variable parts where you can plug in things and come up with them. And, you know, the important point for me here, the importance of being obvious is that, you know, when scientists are doing scientific research, they want to figure out an experiment to do that's going to have the most surprising result that, you know, you would have expected that if we measured the heavier one would fall faster. Haha, no, they both fall at the same speed. The most surprising result is what scientists are after. But developers, code designers are not looking for that. When their developers are developing appies, they're looking for the least surprising design, the least surprising mad lib, the one that other developers would be easiest for them to use. And that's why being obvious is so valuable. So, oh yeah, and another little point is that appies are typically circular, you know, like there's a definition of a binary tree. In computer science, a binary tree is a node connected to zero, one or two other binary trees. And you go, wait, a binary tree is defined in terms of a binary tree. It's circular. And it goes, yeah, it absolutely is. And that's very useful. And in fact, this is the same claim that I'm going to make here. Our core relationship, life, computation and meaning, this isn't happy. It's a blend of requirements that life is. It's got to be physical. It's got to work. And an optional stuff where it can be, you know, sort of any computation. And, you know, my claim is, and my belief from sort of living here for a decade or two, is that, you know, beyond determinism, you know, appies with all of these kind of properties, this combination of flexibility and control, you know, they're everywhere. You know, laws, human laws are appies, parent and kid roles are appies. You know, the idea of the rugged individualist is an abbey. You know, and, you know, in a lot of ways that's kind of a crabby app. So for flavor here, we can, you know, take a minute. We're doing okay. To look at a few consequences of this incredibly obvious idea that we are programming machines. So for one thing, natural language, what I'm doing now is programming language is a form of programming language. Why? Because we are programmable machines and how do we get programmed? We hear language or we tell ourselves language or we think it in our head, whatever it happens to be. And, you know, pseudo code is real code. I love this. When, you know, computer programmers, developer software folks, they, when they're explaining how something is going to work, they can leave out lots of the little nitty gritty details of how any particular language would do it and just, you know, get the gist of it. And so it kind of looks like code, but it wouldn't actually run. And that's called pseudo code. But now that we are programmable machines, we can say that that pseudo code is real code that runs on developers, runs on software engineers who get it. And if somebody, you know, is missing some little key bits so they don't understand some bit of the pseudo code, then it won't run on them. So once we move beyond determinism, instead of saying this is code and this is not code, we have more of a notion of like, you know, the ecological range of this code. How viral is it? How infectious is it? How big a population of people, machines are there out there that could run the code? And so, you know, we take, you know, I give you pseudo code, you give me pseudo code, I write it down, interpret it in Python or whatever, and now computers can run that. And so now the ecological range of that pseudo code that got translated into Python by me has become much larger. But the same thing can be true with people. Someone says something complicated to me. I say something complicated to somebody else. And we think of a simpler way to do it, a simpler way to explain it that can run on more people. So, bottom line, most of the code in our society is shared APIs. Everybody has, you know, little bits of unique code, but we have just these boatloads of libraries of, you know, roles and obligations like org charts. And again, none of them have to be completely crisp in order to be useful. All we need to do is be able to recognize if perhaps we're in a circumstance of parent and child or we're in this circumstance of a rugged individualist who needs help, whatever it happens to be. We are a distributed computation with programmable machines. We're sharing code. We're a distributed computation, which, by the way, is why the rugged individualist API is so kind of silly. And within that, the key operation that we just need to always focus on, not because it's always the only important thing, but because it's the most basic thing, is we want to look at the system in terms of the acts of code transmission, the facts where code moves from A to B. Because that is a form of copying. That is a form of amplification. I mean, we can erase the code where it came from, but typically that's not what happens. Why? Because code is representative. Software is very light. It's down at the quantum scale. Just a little few collection of atoms, a few collection of magnetic domains, a few tiny little punches and a punch guard, whatever it happens to be. And a key metric of how the computation is going, for any particular piece of code, how many implementations are out there in the machine population. And we can understand this stuff. And we can understand mass media. We can understand advertising. We can understand tons of things very naturally, very consistently in terms of these are acts of code transmission that are trying to maintain a population of particular bits of code. And the way they assess that is by somehow figuring out how to count how many implementations are running out there. I'll leave that as a topic for another time, but you get the idea. I think there are useful things to be had here that are particularly, you know, this is a sort of a very neutral way to say it. It doesn't have a particular moral judgment on it in one direction or another, which, you know, is another important topic to come back to. But it avoids a lot of the baggage. I mean, all of this stuff can be expressed in other ways. You can talk about it just in terms of, you know, natural language or Chomsky and language stuff. Focus on that. And, you know, languages, code and so forth. They're all related. And we want to be as compatible with as many of them as we can so that we can speak into the largest population. Okay. More attacks. Got to move along. So, physics, objections to living computation. The second one is easier to deal with. So, you say we are programmable machines. Well, okay, if you explain us as programmable machines, that's not much of a theory of everything now, is it? It's a theory of we. And the response to that is, yeah, yeah, just because we understand, we accept, we choose to represent ourselves as programmable machines, which means we have a place to plug in hardware. We have a place to plug in software. That's the mad lib of the api, the core api of living computation. That doesn't mean we have to use it for everything. So, things that are not programmable machinery, we're going to delegate to physics. Physics can handle it. We love physics, again, meaning science writ large to deal with it. But that does mean that we are going to have this kind of a distinction between if is this particular thing an example of programmable machinery, where we're going to use our programmable machinery api with the hardware and software, or is this, you know, sort of mere matter? Is this mere matter and energy where we're going to use more basic physics apis? And there could be little strange things happening in there that we have to make sure we get them right. I mean, kind of just like general relativity and quantum mechanics don't really fit quite right either. The tougher attack, as far as I'm concerned, is the first one. So, physics says hardware and software is irrelevant. The entire machine put together is still a physical object. So, its behavior is all physics. And, you know, if you want to know where the software came from, well, then you just look upstream. What's up there? More physics. You know, there's a programmer. Why did the programmer do it? Because of physics. The idea of hardware and software adds nothing. Takes is this particular view. But have to push back on that. That that really isn't true. That, you know, that leads us to the, you know, the programmer didn't have any choice in writing the code because it was just physics. And therefore the programmer didn't have any choice in being a programmer. And in fact, it leads us to this idea of super determinism where, you know, the entire universe has all been laid out ahead of time. The fact that we think we are stepping forward through time is complete illusion. It matters not at all whether we decide we need to get out of bed and go get our coffee and brioche or just stay there and mope because it's all been decided ahead of time. So, you know, super determinism, you know, is the last refuge of the deterministic scoundrel, I'd say. You know, it's so utterly useless. And it not only does it not give us a reason to get out of bed in the morning. It says you can't get out of bed and whatever it is, it already have. But on the other hand, if we embrace the hardware software distinction, because they are quite different hardware is big. It's massive. It has energy software really small really tiny easily changed. Then we can start writing all kinds of theories that have tremendous predictive value. You know, a person runs up to a number pad and pushes nine, one, and we say, what's going to happen next? You know, they're going to print another going to push the one again because they're making an emergency call. Physics is never going to predict that next one. Hardware software, it's natural. And that's the point. If we're going to have a satisfying theory that's going to help us, it's going to predict stuff for us. It's going to help pick our best move in situations. That's what we need. Okay, now one more. Here we go. Jeez. The mind attack, the mind's objection to live comp. Also, start with the second one. No mirror machine could ever feel pain or beauty or love or you name it, whatever it is. And, you know, so the living computation reaction to this is going to basically have to be, you know, talk to the physics hand. Because, you know, if physics is going to have this reductionist approach, we can tear it all down to the inverted bozo trons. Then the things are going to, everything is going to be mechanistic. So we're going to be mechanistic. So if we can feel pain and beauty and love well then your machines can too. So we'll just push that one off the table. We'll delegate that to physics. But this first one is more substantial. Mind says, but your terms, software, code, they are just as subjective as mind or soul. Who knows if my code is the same as your code? It's just more words. Why not stick with stuff that we already know, ancient and widely held things like mind and body? Good attack, right? And in fact, it's a great attack. And the living computation theory of everything is going to respond to it by taking out an IOU. And what I say we need is it's incumbent upon the living computation theory of everything to provide a second implementation. What does that mean? You know, so you and I are talking or we're talking and listening or we imagine that it could go both ways. Code is flowing. And I'm making the claim that, you know, that feeling that you have inside that secret feeling that's running in there, the secret place where you have feels and you exist just, you know, like, you know, I think therefore I am. I'm claiming that that's importantly the same as the one that's going on in my head. You know, I think that's a reasonable claim, but it's a fair objection to say you have no evidence. You have no evidence at all. It might as well be mind and body. It might as well be turtles all the way down. But if we could build a machine out of stuff that isn't us, you know, like out of electronics or silicon or waterfalls or, you know, whatever we want, that we can connect together, I would go with silicon, you know, that could respond to the same stuff. We could send our code to that. And that second implementation would do something. Then we could use that as a reference implementation. And software engineering does this all the time when it comes up with a description of how something is supposed to work, like living computation, life computation and meaning how it's supposed to work. Well then, you know, in addition to that language, to that way of describing, you build a physical machine and you say this is an example of something that doesn't. And that's what the living computation theory of everything needs to do. It needs to come up with a second implementation that in principle at least can run the same code that we are running. And the reference implementation, you know, it might do something different. It's not like it has to be magic or it has to be, you know, restrictive, you know, if the reference implementation reacts to some particular piece of code in a silly way. We don't have to now do that, the minister of silly walks and stuff like that. We can just say, well, geez, you know, the reference implementation kind of has a problem there. And we can agree on it. But the important thing is the reference implementation, the second implementation is objective. I can build one from the recipe for reference implementations. You can build your own separate one from the recipe for second implementations. And we can both try them out and we can both compare notes and we can say, well, you know, this might not be exactly the same thing as what's going on in my head or what's going on in your head. But it's the exact same thing that's going on inside these two machines. And that's what makes the living computation theory of everything special. That's why we want to use computational terminology to describe all of this stuff because we're sort of incrementally in the spirit of pseudocode gradually becoming code to come up with an account that can go both ways, that it's natural language, but it's also programming language that machines can understand. And we can make it all make sense. We can make it all be clear. That's the hope. Now, how are we doing on our second implementation? In fact, in my mind, in my heart, the T2tile project is working on a second implementation. But, you know, how far is the T2tile project from being able to respond to code like this and do anything? It's a zillion miles away. And so, you know, that's why it's an IOU. And so there's this basic principle, right, that when you say something, you say, you know, wouldn't it be cool if whatever? Then on the one hand, we have something that we want, and then we can look around at what we have to work with. So we get, let's see, where do we go here? Oh, that's an interesting and complete slide, but it's sufficient to do this. So we have our want, and then we have our have. And there's this implementation gap in between them. And so for different wants and different halves, the implementation gap might be bigger or smaller. So the implementation gap is bigger in this case. Or, you know, if we reduce our wants or we make some improvement in our have, we can have a smaller implementation gap. And once we manage to actually eliminate the implementation gap completely, then we have a machine. Then we have something that will actually do whatever it is. And the T2tile project has an implementation gap. It's absolutely gigantic. But most theories of everything, most philosophical theories are not even defined. They don't even really make an attempt at saying what a second implementation might be. They just appeal to your thought experiment. They just appeal to what's inside. And therefore, I think they kind of fall off the rails. They kind of end up spinning their wheels on lots of little stuff that sort of makes sense from a sort of syntactically linguistic point of view. But it doesn't really get us much closer to anything that's implementable. And that's the underlying message of all of this stuff that, and again, this goes back to computability versus computational complexity like that. So, you know, this is my hobby horse. You know, don't make me tap the sign. What does the sign say? For me, the sign says, only the implementable can exist. That's the point. And so we have to frame things in terms of something that's implementable. And the basic game is that when someone suggests an idea, I think we're living on the back of turtles or whatever the rule, whatever the idea absolutely is. You know, there's some kind of implementation gap. They can't actually show us a demo of the turtle back right then and there. They can't bend down and say, see, this is a turtle scale or whatever it is. So they have to say, you know, they would have to take a trip to the turtle spot, you know, whatever it was that had to do. But that's their implementation gap. And the idea is that if we are listening to their stuff and we find the stuff incredible, like I did when I was dying, and adults were saying ridiculously stupid things to us, then we can call the loan. We can call, so another name for the implementation gap is slightly different. It's technical debt. And at any point we can say, okay, you know, tell us about the implementation. Tell us what you would have to do. What's your best theory about what you would have to do to get from an idea like that to a runnable machine? And the living computation theory of everything is based on making that effort, going from want to have less implementation gap. Okay, so that thing, I don't know what's that there. Okay, wrapping up, going to go just a couple minutes long. To attack the living computation theory of everything, which is now me attacking it, opposed to strawmen that we fend off. You know, so obviously the biggest attack is that, you know, we still have to choose. And that's a big drag, you know, because, you know, behind the scenes, when I wanted a theory of everything, what I kind of really wanted was an excuse to shift the blame. That I wanted some set of rules that I could just apply mechanically and be sure I was right. So that I didn't have to take responsibility for it. I didn't have to make a judgment call that might be wrong or that I might get called out for it. And so the live comp fails at that. It says, sorry, you still have to choose. In fact, it may even make things worse because now we have all these spectrums of how life-like is a particular piece of machinery. How programmable machinery is it? How much does it have a sense of computation and how much does it have a sense of meaning that we might in principle need to evaluate before deciding whether we could eat it, for example. And certainly another attack on live comp is it all seems very cold and calculating. I talk about, you know, the theory of satisfying theory of everything would bring us great profit like that. And, you know, from one point of view it is, but from another point of view it should be. I mean, in our secret internal fortress of solitude, we always are making these cold and calculating calculations. That's why I say we'll find out when we look at the reference implementation and we can pop the hood and say, look at that and that embedding vector, clearly there it's deciding what's best for it. So that may be pretty cold and calculating, but then we're basically saying, we're now basically saying suck it up. That that's the reality of the world. And that doesn't mean that, I mean, we could be warm and calculating as well. We could be calculating and collaborative as well. So, you know, where's the second implementation? Well, like I said, earliest days, earliest days working on the TT tile project for me is steps towards the second implementation. And then, you know, I'm just sticking this in because, you know, people make all this, you know, about AI being so smart that it could just, you know, kill us all in a moment. Actually, I don't think that's an attack against the living computation theory of everything because it's going to turn out that intelligence is vastly overrated. And once we understand that we are distributed computation and it's deeply, deeply built into the system, not just pasted on like we pasted on passwords onto a typical traditional Tradcom program. It's not going to snap its fingers and kill us all for the same reason we wouldn't do it. I guess some people might do it if they could. And that's because they're rugged individualists instead of respecting the distributed machine that we are. So, okay, final, the final answers, and then we will wrap this up, not too long. So, what does London Computation say about our questions? Where did we come from? We came from a flawless, unbroken chain of successful ancestors all the way back to the origin of life. So, Liv Kopp says, you know, screw the big bang, focus on the origin of life. And, you know, it's interesting if you still Google this stuff, there's two big theories called metabolism first theories of the origin of life and information first theories of the origin of life. And metabolism first is physics. Information first is software, hardware and software, because, again, they have to come together to make life. Number two, why are we here? We are here to preserve our patterns, whatever we conceive them to be. Number three, what makes us special? It's the code, stupid. What makes us special is our shared code base. It's the code that we run. That's what makes us special. That's what makes us so vastly different than even animals that are quite similar to us in some way. What makes us special, it's the code base. And what should we do now? We should carry on if possible, and we should improve the code base where we can. That's it, right? One last point. How do you improve the code base? Well, so the living computation approach says, you know, we need to work on the code that we are all running collaboratively and collectively. And the way we do that is we want to collaborate with each other as if we're developers, also known as talk like adults. We would like to figure out, you know, okay, is this thing true or is that thing not true? Yeah, that's all fine. But that's what ultimately is going to happen is we're going to have to say, well, the code is going to try to go this way or the code is going to try to go that way. And then we're going to distribute it. And so what we should try to do is work for consensus on the key code base maintenance question, which is, what do we tell the kids? That's it. Tell me you got this.