The Basement: Donald Hoffman | Consciousness, Math, and the Case for Letting Go

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He sat for years in a private consciousness club that Francis Crick co-founded. "France is Crick. The guy who discovered the building blocks life. I discovered you can't return underwear or target. Both took real courage." Then his own math convinced him that we've never once seen reality as it is. He seems very calm about it. Today we're covering the beetle that fell in love with the beer bottle and why that matters for evolution. "A beetle dated a beer bottle, huh? Yeah, I bet worse." Why Don says space and time are a headset we're wearing and what that means for UAPs and the entities people meet on DMT. Near the end Don tells a story that he's never told before. It's about the night he texted his wife goodbye from a hospital bed. You might know that part, but you don't know the rest. "Okay, no notes in that one. That one's real." Once we wrap up, I'll come back and break down the conversation, which is not going to be easy, but I'll be here. Let's go down to the basement. [Music] Professor, thanks for doing this. I appreciate you. Thanks a lot, AJ. First thing that kind of, I found interesting about your background is you grew up in San Antonio. I spent most of your life in Southern California. Where did you start ice skating? How does that even, how does that part of your resume? I think that that started when I was about 12 or 13 and we saw maybe an ice cupades, chalet, an ice cupades show or something like that. My parents liked it. We liked it and they decided to try ice skating. I was 12 or 13. My brother was a year younger. My sister was four years younger. So we went out there. I didn't like it at first because you just fall down. You get out there, you try stuff. Everything that you try to do is just wrong. All your normal reactions are wrong. So I fell, fell, fell and I basically didn't want to do it and they forced us to do it for several weeks and then all of a sudden one day it clicks. You realize you don't walk like you normally walk, heel toe, heel toe. You push with the side and you glide and when you really discover that for yourself it opens up a whole new world and once you then enter that world then it's fun to glide. And eventually I got to the point where I could do a double toe loop and an axle jump and so forth. So I actually did a double jump and a one and a half turn jump and so forth. So it was it was a blast and it's very, very good exercise and even now I'll go go back and ice skate. I'm not doing double jumps but you know I'm 70 so it's not not smart but if I'm careful and just you know just stroke and glide on the ice it's good exercise. I thought it was great. Okay so ice could pay it's not hockey. That's fine. Yeah it wasn't hockey and so I did figure skating and all of us did figure skating. I've never actually been on hockey skates. Wow. I'm picturing you in the whole Lycra outfit. You look great by the way. So dad was a fundamentalist preacher. Yes. What do you think he would make of you starting an institute that nothing is real? How would that conversation go? Well in his later years he did hear about the work I was doing. He did. We did have conversations about consciousness being fundamental. He liked that actually because that aspect of it is on board with his views. I mean he thinks he knows what that consciousness is and it's his god and not other people's gods and so forth but so he sort of liked the non-physical stuff so he was all on board with that but when it wasn't just directly into you know fundamentalist Christianity then he wasn't so excited about it. So I would say that he was glad and would be happy about the idea that consciousness is fundamental and he would like it to show that his denomination of Christianity was the truth and it doesn't show something like that. It just shows that there's a much deeper level of consciousness that I think the different religions, Christian, Buddhist, Hindu and so forth are all perspectives on a deeper consciousness and they all get a piece of the puzzle and they miss them as any perspective would. Is that what planted the seed for you to go into this research? You were getting one story on Sunday and a different one on Monday. Does this kind of reconcile it? That's exactly right. I got one, the story I got is pretty severe story from the Christian view. It was there at this only 4,000 years old and oh he was that? Oh no he was that. That's right and he had a master's degree in chemistry so it was really he had decided to choose that the religious view over what chemistry had shown and so that was quite stunning. So he was quite into it. So he took that point of view. Yeah, so he wouldn't have liked me going beyond the 4,000 years which I have. I think the earth is well over 4,000 years old and he wouldn't have liked. I think he likes that there was a mathematical model so he would have liked that but he also wanted it to come out that his particular brand of Christianity was the truth and all the others weren't the truth and so forth. So yeah, I got one version on Sunday but then I also had the Monday version which was there was all the science and I would like to, that says that more billions of years old and we evolved and he didn't believe in evolution at all. That was an aftermath to him. The notion of evolution was just off the table. I can't square the masters with chemistry with that. What drew him to the faith instead of the science? You know I think that it's hard to explain. It seems irrational to me. The science is very, very clear. The experiments are quite clear. If you're going to use the language of space and time and chemistry, in that framework the earth is 4 billion years old and not 4,000 years old. So I think he just chose to reject his master's degree, not just a bachelor's, a master's degree in chemistry and working at various companies in high levels in chemistry. So I had to, on my own, then decide between the spiritual view that I was getting, I'll say the Christian view, a particular kind of spiritual view, a Christian view and in fact a fundamentalist Christian view on Sunday. So can I still get a heaven then? Well a lot of other people, even in other Christian denominations might not be going to heaven. So this was, it was pretty austere, right? My way or the highway and bad thing about it was that God was not a really, they would talk about God being love, but in fact, you were trying to be a afraid. You had to be really, really afraid and cry every Sunday and repent, and it was quite a scene. So it was real psychological control. And when you're raised in it, that's all you know, right? And so it took me, it's taken me decades to recover from that. 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Just head to Ridge.com and use code basement and you're all set. One more time. You can find Ridge's power bank at Best Buy, or our listeners get 10% off at Ridge.com by using code basement at checkout. After you purchase, tell me, said you. So I decided as a teenager on age 17 that I had a specific question that I would try to answer. Are we just machines? That's my question. To do that, I would have to understand what machines can do. Is there anything that humans can do that machines can't? That was sort of the idea. I ended up ultimately trying to answer the question. I went to MIT and I was in the artificial intelligence labs, so that's going after what machines can do. I started in 1979 and had the good fortune of actually interacting with Marva Minsky. Took a class with Marva Minsky, the guy that one of the guys that founded the field. Jim McCarthy, the two of them founded the field. So I got to argue with him at his home. We had that class for a semester in Minsky's home and we could just argue about the foundations of the philosophical foundations of artificial intelligence. And so from '79 to '83, I was there in the AI lab trying to build, you can't just talk in general about AI. You need to pick a problem and try to solve it as a scientist. So I picked the problem of how do we see in 3D? It was machine vision I went after. How do we build visual systems that can see in 3D? The kind of stuff that we now have in self-driving cars. We were pioneering it back then. So I did that as my concrete mathematical, how do we see in 3D? And then I was also in the brain in cognitive sciences department. And there I was studying human neuroscience. So you can see I was studying what machines can do in the AI lab and what human neuroscience I was studying what humans can do and trying to piece the two together. And it wasn't until, so I was '79 to '83 and I kept working on the mathematical models of vision. And it was around, in 1986 to 1987, working now at University of California to Irvine with Bruce Bennett and Chaiton Prakash to extremely talented mathematician. I was very, very fortunate to have them working with me. They're geniuses. And I'm still working with Chaiton. He's brilliant. Let me stop you for a second. While you're getting your PhD, you're working at Hughes aircraft on vision systems for missiles and stuff, right? Yes, I did that. When I was an undergraduate at UCLA from 1976 through 1978 and then a whole year in '78 to '79, I was at Hughes aircraft full-time. What did the Hughes guys think of your work with computational vision? They liked it so much that they paid me the whole way to go through MIT. So I got a free ride through MIT. From Hughes? From Hughes. Wow, okay, I didn't know that. Yeah, and at the time there were no strings attached. They assumed that I would come back and I would be the director of the Hughes aircraft artificial intelligence laboratory in Malibu. And I was thinking about the same thing. I was about to be a very rich guy living in a very nice place in Malibu and directing the AI lab there. But my last year, I realized I knew what it was like to work at Hughes, and by the way, Hughes is a great place. Did you work out at El Segundo? El Segundo, that's right. Yeah, I worked out at El Segundo. I worked on fighter jet cockpit software for displays. So this was a new thing. There were all these old displays, mechanical displays on the fighters at cockpits. And it was a time to go digital, but the microprocessors weren't that fast. And so we had to program them in machine code. So I and two or three other guys were the coders. And we ran out. You didn't even have four train yet? Nothing like that. Well, I had studied four train, of course. I mean, I knew four train from. Actually, I did that when I was a sophomore, I think. Yeah. So I knew how to program in four train. But when I got to Hughes, they said, you know, we can't do four train on these things, not that. I mean, these are special purpose processors that are inter-op driven, and they have very, very special things. All what they had was the machine code that were brand new. So this is 1976. These are brand new. It was called the Anjuk 30, AN-UIK 30. Anjuk 30. So you can look that up. That's what I programmed. And it. So I knew all the ones and zeros. But I wanted to multiply by two. I didn't multiply by two. I shifted things like that. Sure. If you wanted to divide by four, you shift to the right and stuff like that. So you found all the tricks. We did an entire complete flight simulator in that Anjuk 30 in machine code. And because we programmed the entire machine code by hand, we got it all in 64K. Wow. You can't type one word in an email for 64K. We did an entire flight simulator bit by bit. We knew all the bits. And it was delivered to Wright Patterson Air Force Base in 1970. So to Wright Pat. So I was. And I actually, as an undergraduate, UCLA was being flown around to various military places and corporation places to help you know because I was one of the few, like three or four people in the world that knew how to. It was cutting edge for these new electronic displays for Frederick. So I was. I was a cold warrior. I was an undergraduate. And then in 1979, as well, for a full year. And then. So I took a year off from college and then went to MIT in 1979. And Hughes paid the whole way, expecting me to come back and direct the AI lab. But at the end of. Toward the end, I realized that I really had a choice between money or doing the research I wanted to do. Because I knew even though I was going to be a director, there would be directives from above. And I wouldn't be afraid to really explore what I wanted to do. And so I decided I wanted a complete autonomy to explore whatever I wanted to do, not just something that's going to lead to a product. And you know, it's not right or wrong, as some people are more inclined to do one thing or the other. I was more inclined to want to be independent and follow my own. So I decided I was just. So I took a pay cut. I made less money going to the University of California to Irvine. Of course. And I was making as an undergraduate. Of course. At Hughes. A huge pay cut. So I made maybe a quarter or a fifth of what I voted made at Hughes. But it was a good decision because you could have gone back to Hughes anytime. I could. That's right. But once I got going on the research, then it really took a life of its own. I realized I really wanted to pursue this all the way. Let me go back to Young Don for a minute. Yes. And because maybe this is the the seat of getting interested vision. But the story of your five years old and you're late to kindergarten because something grabbed your attention. Yes. Yes. Yeah. That was a real wake-up call to me. So I was. Yeah. Magic. Right. Yeah. It's the butterflies. The butterflies. So I was walking to kindergarten. And I'd learned how to walk there. And so I was confident that I could get there. But when I was walking, I saw this beautiful bush that was in bloom. It was about my eye level. So I could really see stuff. And it was covered in butterflies. And it just was obvious to me that kindergarten was nowhere near as important as enjoying life. I mean, this is a miracle right in front of me. It's just obvious that the right thing to do is to relax and play. Relax and enjoy and explore. I mean, nature is showing you something that's amazing. You're here to enjoy it, to observe and to learn. And that's. I mean, I was saying I was intellectually saying that way. It was just my emotional childish reaction. This is a whole thing to explore. So it's not like I was intellectualizing. It was just obvious. Right. But to do this. But you decision to leave use. This is an analog of that. Yeah. It was really. Life is about exploring, going where your heart wants you to. And having fun. So it's really, it's really a play. It's really. I really do think that way about reality. And that is that we're here. It's not that serious. It's like the Hindus have the notion of of Lila that it's a game. And I think that that's a really deep insight that the, in some sense, the greatest insights and even technological insights come when you just play. And somehow I think reality rewards that. It's sort of like only when you let go of your optiteness, do you start to relax into new dimensions of reality where that you can explore? So it's, and so for me, it's been a bit of a journey because that five-year-old butterfly chaser got strangled. It, I got in trouble, the kindergarten teacher, instead of rewarding that my parents know that I was late 'cause I was, and I was punished. - Did you tell your teacher what, why you were late? - Oh, yeah, I brought a butterfly in. I was trying to share it with everybody. - Of course. - And I didn't really understand that that was not good for a butterfly. - You didn't mean any harm. - I didn't mean any harm. - I was only five, but it was just obvious that this was a joyful thing I should just share it with all of my friends in kindergarten. That's just, of course. And to find out that that wasn't accepted was a, and so you get slapped down, I got slapped down. - That's how you create a heretic right there, that day. - Yeah, eventually, I mean, I was shaped into that mold for until I was able to leave 17, 18 years old, and then it, those are the formative years. So, informing the formative takes, so I'm still in the process of decompressing from it, but in the decompression process, I really have come to the point of view that I was trained to be afraid and to just go by the rules and so forth. And now I'm realizing that true intelligence is play. True intelligence is not, it's assuming that I don't know anything. - Something interesting is happening with gold and silver right now, and it's worth paying attention to his buying. Central banks just bought a record 289 tons of gold last quarter. JP Morgan is telling clients, gold could reach $6,000 an ounce. Well, city bank predict silver could hit $90. At the same time, the national debt is approaching $40 trillion. And treasure your officials is talking about growing away out of it. So while the people running the monetary system are stockpiling physical metal, it might be worth asking why. That's where gold crest metals comes in. 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So I see in meditation, I just see myself having to face that old programming, follow the rules, God's mad, and so forth. And buckle under. And you could observe that when you're meditating? Yeah, I see the pain of that. And I just-- and all the crap. So really, it's a closing up. What that does is it closes you up to reality. You're tightened up. So what I find is as I'm opening up to reality, all that tied up energy flows out. And the old tied up person is afraid of that. So that's why it's painful is that old person is dying. That's really a death of that old. And it is a birth of someone who's ready to play, to relax into life, and to then have intelligent exploring. Because that's only then can you get outside of your box. The only way to make something new is to let go of the old. And you have to be able to let go of everything that you know or sometimes to take what you know and leverage it, put to go into new places. You have to go into new places. So it's not like old knowledge is bad. Often old knowledge can take you to the frontiers. And then you have to, once you're at that new frontier, then you have to let go of the old knowledge. So it did its thing. It got you to a new frontier. And then you have to dive into the unknown. And so that's fun for me. I think we've all seen you live this, because my audience has followed your work since the TED talk. We've never seen you lose your temper. In a debate, I mean, you've released papers that have had 10 rebuddles. And you've said, maybe they're right. I mean, it's just very open to criticism. Yes. And I think that most scientists would agree that that's the way to do science. I think that's, I mean, we are humans. And so some people get rattled and they get personal about it. But I would say that most scientists, when they're not emotional, they're just dispassionate and looking at science, they would say theories are just theories. Don't be identified with them. Of course, do your best. Be as clean and rigorous as you possibly can. Get all the evidence you can. Give us strong a presentation of your ideas possible. But then I have so many good friends who disagree with me and they're brilliant. And we'll disagree. And it does not have to be at home. And I mean, it's never at home on a mic part, because these are brilliant people. Why would I want to get upset with them? They disagree with me. Often, even if I think they're wrong, they've pushed me in a new direction that helps me think out of the box for my own stuff. And often, sometimes I'm wrong. And they point out something where I'm wrong. And hey, you know, good to drop it as soon as you can. So, yeah. It's funny. You mentioned theories of just theories. Something I wanted to talk to you about is David Marr. The great. Yes. I guess he basically launched computational neuroscience. He died very young. You got to study under him at MIT. Yes. He said, unless there's math behind it, a theory is just a theory. But he also said that vision is designed to bring you the truth. Yes, he did. So you've taken that premise and then used your theory to kind of knock that down. So just from a relationship perspective, how do you think that argument would go between you and David? Well, so David changed my life. I was a senior at UCLA taking a class on artificial intelligence. And one of the papers we read was his paper with him and I think Tommy Pojo on vision. And as soon as I saw that paper, I was electrified. I realized that's it. This is really rigorous. They're doing neuroscience. They're doing mathematical models. And they're not waving their hands. They're saying we need to build a working system. And if it doesn't work, then we're wrong. And it's sort of like, there is no nonsense here. This is all serious stuff. This is how you make progress. I said, where is this guy? And so I looked at it and found out he was in what was then called the psychology department at MIT. And they didn't have anything else. I didn't even think of psychology in MIT. I'm thinking engineering and math and so forth. But it's now called the brain and cognitive science department. And then he was also in the artificial intelligence lab. I thought, well, wow. This guy's got it. It's a long shot, but I need to see if I can get in there. So I applied and went out there. I'd never been to the East Coast before. And I had no idea how cold it was. It was like February. And I brought just a light jacket. Oh, it was like jacket. On New York, one trial learning. But David-- so they accepted me. David-- take me to that day because I've been to MIT. Were you just blown away when you got on the campus and saw these legendary buildings, these names? Well, it's a who's who. Yes. I mean, I took a class with Noam Chomsky. Jerry Foder was there. Thomas Kuhn was in the class. I sat in in the class, given by Thomas Kuhn. But there's this one class where Jerry Foder and Noam Chomsky were the instructors. And Thomas Kuhn was in it. And the graduate students ended up being a who's who in the field. It was then in about 50 or 60 graduate students. Sorry. It was truly a stunning situation. And Wally Nada took a class with Wally Nada. I mean, it was-- What an experience. I had no idea how lucky I was. You didn't know at the time? All I knew was David Mar was there. And Whitman Richards was also my co-advisor. They knew when I came there, that David was sick. You finished under Whitman. So, yeah, so I had David for, I don't know, maybe a year and a half or something like that. I was able to work with him. He had leukemia. Yes. And then Whitman Richards was an absolute gem. He encouraged me to think out of the box. He treated me as an equal. and we bounced out. ideas back and forth. We, of course, didn't hold any punches, but it was all very, very friendly. So he really taught me how to be a gentleman and yet a researcher that doesn't pull any punches. And with David, he had assembled such an incredible group of people around him, Bertold Horn and Eric Gremson and Ellen Hildruth and many, many more on Hollerback. So I got to take a class with Bertold Horn. It was truly stunning. And it was tragic to see David die over those 18 months or so that I was there with him and he kept teaching while he was sick. He did. He would come to our research meetings. He would have to hold something over his mouth because he was bleeding. He was heartbreaking. And at one point, there was a time when one of the graduate students, I won't mention any of them, but I knew him not well, but I certainly knew him. He defended his PhD and then committed suicide the very next day. And so that was, it was a real shock to all of his graduate students. And I was like, "This guy worked so hard. Why did he commit suicide the day after he got his PhD?" So I was in the Artificial Intelligence Lab going to one of the list machines probably to do my research. And David Marr saw me. He ushered me into his office and waved me in and said, you know, you knew about, of course, this guy that had just committed suicide. The David Horn said, "Look, if you have any feelings about doing that, life is worth living. Come talk with me first." And this was him at the edge of death himself. He was facing me. And he was only, he died when he was 35. It's tragic. I mean, the guy was a complete genius. When you sat in a room with him, he was the intellectual leader of the room. He was the one who knew the neuroscience. His PhD was a model of the cerebellum. But he knew the AI. And he commanded the room. Everybody just looked up to David. So I was very, I was his last student, his last cohort. So there were, I think, one or two of us in the last cohort. Imagine what he could accomplish with another 30 years of work. Oh, can you imagine? Yeah, no, no. So it really makes me, I feel very, very lucky to have known him. He got me into the field. If it weren't for David, I would not have gone to MIT. Would have gone to UCLA or something like that. Which UCLA is a great school. Nothing wrong with UCLA. But that was MIT at that point, was unique in the world. That AI really took off there. And so your learning had to argue, tell me about the Helmholtz Club. Well, so David died. And I graduated a year to year, year and a half later, I guess, maybe two years later. And that's when it took the job at UC Irvine, instead of going to Hughes. And when David was dying, Francis Crick, with Watson and Crick, the guy that did the Nobel Prize work on the DNA, everybody's heard of him. He was at UC San, well, at the Saw Institute by UC San Diego. And so he knew David quite well and had tried to save David's life. He was, Francis was using all of his connections, which were substantial, to try to get the latest technology, medical technology to try to save David. So David got the best that was available at the time. Clearly the right thing to do because he was inventing modern vision science. Sure. He reinvented the whole field. So, Francis knew David quite well. And he knew that I was David's student. And when I came to UC Irvine, he almost immediately reached out and invited me to visit him down at the Saw Institute. So I went down and spent some time with Francis, and we talked. I didn't know at the time that he was interested in consciousness. And at the time, it wasn't really kosher to talk about consciousness, right? So this is 83, 84. It wouldn't be another six or seven years before it was kosher because Francis said it was kosher. But he hadn't really come out and said it was kosher in a big, big way yet. So, but has Wheeler talked about consciousness at this point yet? Wheeler had talked about observers, but he didn't talk about it from bit yet, right? That was 1989. So just after. The 1989 was as it from bit pay. Right. Right. He may have talked a little bit about observers and the fundamental nature of observers before that paper. But that 89 paper was the one that everybody knows about. Yes. So Francis then invited me to be part of this Helmholtz Club. It was a private group that happened to meet at UC Irvine. And the reason it met at UC Irvine instead of where Francis was is because Irvine is sort of in the center of Southern California. So there are universities north of Irvine, so USC and UCLA. There are University South, but like UC San Diego and the Saw Institute and so forth. And Irvine is right in the middle. So I was lucky. I was right in the center. And so everybody came to me to UC Irvine. So they met actually literally a five minute walk from my house because it lived on campus at UC Irvine. You could walk to the club. I could walk to the club. So Irvine was had to drive. So it was a secret club. Not for any nefarious reasons, but simply because Francis was there. And if anybody else, if anybody knew publicly that Francis was on campus, we wouldn't get any work done. Right. People would want autographs. You know, he was as big a scientist as they come. And so we met in private at the University Club on Tuesdays, one Tuesday every month at one o'clock. And we would have lunch together. And Francis and there may be 10 or 12 of us that were the core members of the club. And we could invite one person ourselves if we wanted to, but as a group would invite someone two people from anywhere in the world whose work was of interest to Francis and the group. We'd fly them in. So there'd be two different speakers each time, but they have a lunch with us. We'd then grill them all afternoon. It was, it was no holds barred. They would present our stuff and they couldn't get through their talks. We would, Francis would, we would just go at it. It would always feel like when he, when he disagreed. Well, Francis was a gentleman all the time. He was absolutely a gentleman. I never saw him in polite. But what I did see was he would never count his fools. And he would never, he, he wanted answers. Life is short. He was, he was an older man at the time. Right. I don't have much time. Let's get to it. That's right. And, and the goal was consciousness. He had demystified life with DNA. And he wanted to demystify consciousness. That was a clear goal of the Helmell's Club. He wanted to know the latest neuroscience because he wanted to understand what neuroscience would break open the door to consciousness. Just like the double helix broke open the door to understanding life. So he, he was on a mission. He was polite. He was a gentleman. But he was not going to have anybody getting his way. He, I mean, if he had a question, it was going to come out and we were going to, you know, we were going to go after. So this was really bringing it, bringing the best and brightest and, and really grill them in a, in a respectful way. But we're trying to understand the best they know to see if there's some clue there. And it was fun because there'll be, you know, maybe the dozen of us, 15 of us in the room. All, I mean, to be sure flying that wall. Yeah, sure. It was unbelievable. The conversations that that went on there. And, and it was really a good thing for me to see how Francis was focused. He had a goal. He was looking for any clue anywhere and he was bringing in people from all over the place, trying to go after it. So, and I remember in 1992, he then, one of the meetings, he, he told me about his book. He was writing the astonishing hypothesis. So I got to hear him talk about that. Wow. Talked about that book. So that's when he sort of, you know, made it really official that, you know, serious scientists can talk about consciousness. Now, it was a very physicalist approach, right? So he's, he was saying that somehow neural activity is going to be the cause of conscious experience. Or some aspect of neuroscience is going to be the cause of conscious experience. It's kind of inverted from your hypothesis. Completely inverted from mine. But, but I would say in line with what 99% of my colleagues in neuroscience and, and computer science would say, well, it's a lot easier to, as a scientist to wrap your mind around that than what is consciousness creating? That, that's right. And there's good reason to go this direction because the physicalist approach since Galileo, at least, had done quite well over the mathematics and a physicalist ID, you know, ontology had worked very, very well. Spiritual ideas have been around for thousands of years. All of our technology came from physicalism with mathematically precise models. And so there's no reason until the spiritual traditions can come up with their own mathematical model, there's, there's no beef for a scientist to go after. And unless the scientist is going to try to take the ideas of the spiritual traditions and turn them into math. But the bets were we got the secret to life, physically, AC, G and T. Yep. We got the secret to life, the story. I'm not I'm not saying this is right, I'm just saying this was the story. We got the secret of life, ACG and T, from biology and from the mathematics of that. And the bets were that we would get the secret of consciousness the same way. There's probably probably some kind of nervous system process, a neural process that some let we have to figure the level and how big a system is it and so forth that causes consciousness. So that's what we were after and it was fun for me to see the pros go after it. But you know we never got it, never got it. And to this day, still the hard problem of consciousness. 30, 40 years of now good, hard neuroscience, artificial intelligence, computer science, information, theoretic attempts to start pen-reson, hammer-off, and bone-reson, and hammer-off. And I know most of the players, they're brilliant, they're my friends and colleagues. And the fact is there are several theories out there and there are trillions of conscious experiences to explain. And there is no physicalist, neuroscience, AI, computational theory, none of them that can explain even one specific conscious experience. And that's truly stunning, like the taste of chocolate or the smell of mint or something like that. I mean there's just, and that's pretty stunning, I mean just to really put that in perspective, I'm a cognitive neuroscience and a scientist. Suppose I went to a bunch of physicists and said, "I've got a new theory of particle physics." Imagine? And they said, "Really?" "Really?" They'd be, you know, they'd smile and so, and a natural question would be so done. You've got a theory. So, well, let's check this out. So what specific particle interaction does your theory explain? And how does it do it? Like, photon-electron interactions, what is it? And if I said to them, "Oh, no, I have a general theory of particle interactions. I can't explain any specific particle interaction." Would I be taken seriously? No! I'd be kicked out of the. They might pat me on the back, say, "Let us have a beer and then go your way, man." They might be kind to me, but they're not going to take me seriously. And that's where we are with neuroscience, and physicalist approaches to consciousness, AI and so forth. There's not a single specific conscious experience, and some people will say, "Well, and I actually said this two or three weeks ago at a meeting in Venice." Okay, here's something most guys don't know. 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And the way to write down rigorously what the causal structure is, in any case, is to write down a Markov matrix. And so matrix, you could say the square matrix, it has N columns and N rows, and it basically has a probability measure in each row, that is a technical thing. And so that's the way to do it. Later we'll do the traffic light if you don't mind. Sure, yeah. We can do that. That's right. So, they say, for every conscious experience, there is a causal structure, and you will know that you've got the causal structure when you write down a Markov matrix for it. And so, when you look at the paper that Tunoni and Koch published, there is no Markov matrix. So what I would want is, okay, what is the matrix? It has how many rows? Is it like a hundred rows? Okay. And it's got a hundred columns. Yep. That means you have 10,000 numbers. What are those numbers and why? And why is it that those numbers must be the causal structure that must give rise to the taste of mint or whatever it might be, or to, in this case, you know, the perception of space. So there's nothing on the table. Of course not. And there never will be. There never will be. There never will be, and it's, so again, I know the players, they're my friends. They're brilliant. Yes. They're not done. They're absolutely brilliant. And they're doing, by the way, they're doing good work, the work they're doing, even though they're not solving the problem of consciousness, they're, they're getting a lot of good information about neuroscience and the structure of neuroscience and so forth. So, so it's not like their, their work is wasted. We're learning lots of stuff. We're just not learning about consciousness except what we're learning is it doesn't come out of neurons or physical structures. We're really learning that very, very well by geniuses trying their best to get consciousness out of physical structures or computational structures and failing. I think it's, I think it's better that all these scientists disagree because truth is not a truth until it's known, right? That's, that's really true. So, this gives us real acid tests. Right. If we're going to try to show that consciousness is fundamental, it's good to show by the failure of geniuses that the physicalist approach, you, you just show that that won't work. And, but then also they're going to be my harshest critics, which is what we need. This is not about, you know, patting people on the back and say, oh, they're there, they're there. No, no, this is hard no stuff. If you're going to come up with a new theory, you've got to take, you've got to take whatever comes your way, you've got to listen to their arguments and you've got to respond. So if I'm going to put a theory forward in which consciousness is fundamental, of course the, the physicalists are going to come after me and that's as it should be. And then of course, we'll go out and have a beer afterwards. Sure. Nothing personal, but, but, but on the other hand, professionally, no holds barred. They should and they do do everything they can to take down and often I learn something from them. I'll say, oh, wow. Didn't think about that. I need to go look at that. So it's all good. It's all good. It really is. Physicalism, a lot of, I probably most of the audience knows you from the TED talk, which was titled something like Don Hoffman proves there's a simulation, but that's not exactly right. Because simulation is still physicalism to the back door, isn't it? Right. Right. So Nick Bostrom is well known for the simulation theory. And in Bostrom's approach, we're quite likely in a simulation and that simulation is probably being written by some teenager at a lower level who's got their own computer and is, and does code us up, and but that teenager and their computer is probably a simulation from an even lower level and you keep going down until you're going to hit some bottom. So, and so there's two things that I disagree with on Bostrom. First, I like the idea of a simulation in general, right, that this, the aspect that we're not seeing reality as it is, that this isn't, that space and time aren't the final reality. I like that aspect of it, but there's two aspects that I disagree with. The first is, at the very, very bottom level, the assumption is, by Bostrom and most everybody, that it's again, some kind of physicalist space time reality at the bottom. And I think that that's not going to work. I think that space time is doomed, and we can talk about why space time is doomed. So that's one place where I disagree. The bottom is not physical, it's not a space time. The second is that, to the extent that Bostrom and others think that there are conscious experiences at our level, for example, those conscious experiences must result from the programming at a lower level. You'd be either the computational aspect of it or physical or something about the physical or a computer. But since the simulation is really only computational, right, it's not really conscious, is it? Well, and the thing is, I wouldn't want to say it's not really conscious. I would just say, we have no theory yet that could explain how they could happen. We have, this is one of those theories that, computational theories for building consciousness have yet to explain a single conscious experience. And I think it's principle. The failure, again, is principled. So I think that Bostrom is wrong to say that the bottom level is a space time level if he says that. If he doesn't say that, I'd be interested to see what he does say. And I think it's wrong to say that computational systems can give rise to conscious experiences. Or I would, by the way, some people, like Michael Grasiano, would say, oh, well, there are no conscious experiences. There's only the illusion of conscious experiences. - Okay. - That's unfossifiable. - Well, it's still, well, someone who says the illusion of conscious experiences as a scientist, I would then want you to give me, and you want to say that so computational systems can give rise to the illusion of conscious experiences, not not real conscious experiences. I'm happy to go with that game. - Sure. - I mean, that's what we always do in science. We make high policy. But if you're gonna play that game, then to do the scientific thing, you now owe me a scientific account. What specific computational system, for example, must be the illusion of the taste of chocolate and could not be the illusion of the taste of mint. Now, there are no candidates put on the table so far. So the idea of saying that there's the illusion of consciousness does not get you off the hook for giving me specific examples, and there are zero. So the illusion hypothesis has no empirical evidence for it, whatsoever, and I think that it never will. So just moving from consciousness to the illusion of consciousness doesn't get you off the hook. And you have to put up the scientific experiments and the scientific theories for specific cases, and there are none. And I predict that there will never be any. So illusionism gets you nowhere on this. - Very interesting. Have to be hard on those. You can see, again, it's not at hominem. I'm the first to say, Graziano is a brilliant guy. All these people are brilliant. But you know, this just won't work. (laughing) - But I love this disagreement. That's the only way forward. - You mentioned I wrote your, I wrote Observer Mechanics in '89. - Yes. - So you, the two of you made a bet pretty early, and you're kind of out in the wilderness for 20 years? - Yes. - What was that like to just have no one really paying attention? - That's right. So we published a book, Observer Mechanism, it was three of us, actually Bruce Bennett, who was a genius mathematician. - Is he gone? - He died in early 2000s. - And Che Tom Prakash, who was also a genius mathematician, is still alive, and we still collaborate, and he's a good friend. We really worked hard in the '80s, we was probably four or five years of hard work to put out that book. And by the way, when we published it in 1989, Wheeler cited it, and it was it from BitPaper. So if you look at his paper, one of the citations is to Observer Mechanics. So he read our book when he published his paper on it from BitPaper. - That's a fun phone call to get. - Yeah, it really is. So he was aware that we had some cognitive scientists and mathematicians had really taken the idea of consciousness, conscious observers, being fundamental, and we're trying at the time to show how we could build up space time from it. So Wheeler was aware of. I, when I came from MIT to UCI, I was on the fast track. I mean, I was getting grants left and right. - I realized. - I was at the head of AI research at the time in vision science and so forth. But when I started moving into this, what was really interesting to me now, when I realized in 1986, '87, that we're creating everything that we see. I mean, you can't walk away from that. The whole physicalist, in one moment, when I realized, I don't know if I told you, but when I realized that, it was at a certain moment. When I realized what the mathematics was saying to me, there was a one point where the mathematics all of a sudden just slapped me in the face. 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Now at McDonald's. - Refreshers contain caffeine. - Let's assume everyone's senior TED Talk, just give me the dinner conversation sort of summary of the theory. - Right. - Give me the 60 second on the beer bottle beetle. - Right. - Tell me about denim jeans. - Right. Right, so the TED Talk really took on a deep belief that we have, that evolution shapes us to see the truth, right? So Darwin's theory says that evolution shapes us to be fit. Shapes, organisms to be fit. And it shapes their sensory systems to make them fit. And most of us, sort of technically, that means it shapes sensory systems to make you good at reproduction. In evolution, the payoff, the fitness payoff is how many offspring you have. The more offspring, the more fit you are in some sense. And most of us assume informally, and even formally, experts, that sensory systems that are shaped by evolution to be more fit do that because they've been shaped by evolution to show you the truth. Clearly, it would seem sensory systems that show you the truth will keep you alive longer than sensory systems that don't show you the truth. And that's a deep, deep intuition. And it's wrong. It's, so very, very brilliant people think that, and it's wrong. And I can, in my TED talk, I gave some explanations about why, and I also gave some examples. And maybe I should start with an example, though I'll explain the deeper principle behind it. So it's, and the examples aren't new, but they really make a point. So one example is the, are beetles. So there are these beetles in the outback of Western Australia. The jewel beetle, it's called. And they're dimpled, glossy and brown. The males fly, and the females are flightless. And the males will go flying around looking for a female, and if he finds one that's, you know, looks right, he'll alight and mate. And, but in the outback of Western Australia, there are some men who were drinking beer and these things that called stubbies, that were also, these bottles were dimpled, glossy and brown. And apparently the right color around, they tossed them out into the outback. And the jewel beetle males would fly down onto these, these, these stubbies and flock all over them, trying to mate. Now, it's remarkable. It's, it's not like, you know, they flew down to it, realized it wasn't a female and took off. They fly down, they're crawling all over, full body contact, as much contact as they can have, and they, they persist in trying to mate. - Until they're, until they die. - Yeah, that's, that's right. So they, they, they do not give up. And this could make the species go extinct. So, so what's interesting then is, what this shows is that the males don't know too much about what a real female is. They don't have a real understanding of a female. A female is anything dimpled, glossy and brown, the bigger the better. And, and, and that's, that's as much insight as they have into females. And some females might tend to agree that their males don't have much insight into it. And, and so that, that really shows you that when evolution is shaping sensory systems, what is doing is giving you a solution that's good enough for reproduction. And in that niche, in their niche, what was good enough apparently was dimpled, glossy, and brown, the bigger the better. You don't need to know anything more about a female because you weren't going to be fooled. There were no stubbies at the time. And so that was good enough. So it's what you call a satisfying solution. It's good enough, it's just not the best, you know, possible thing. - This is, don't worry about the baby behind the curtain, right? That, that, yeah, right. So, and, but that's not just a one-off now. It's repeatedly we see that there are all these tricks and hacks. If someone wants to read about this, look online, you know, do an AI on super normal stimuli, okay? Super normal stimuli, and you will find all sorts of things that are fun about how organisms can be tricked by wisdom. And we use that all the time in designing, for example, makeup is super normal stimuli. When you put on lipstick, the red of your lips, is super normal in nature, no woman, whatever, almost no woman would have lips that red. So it's not natural, and yet in men, there is a program for sexual attractiveness. And up to a point, redder lips, tickle that algorithm, and make you more, of course at some point, then you go into your clown material, right? So you can push super normal to a point, and then you go clown of all of a sudden you fall off. So what you see in evolution is that our sensory systems, in these particular cases, have not been evolved to show the truth, they're tricks and hacks. Now, David Meyer was quite aware of this when I was a graduate student, and he knew, for example, that flies had tricks and hacks for their sensory systems. Maureen Pogil looked at the fly visual system, and so Maureen Pogil would say that the fly, yeah, had tricks and hacks, but David said, the human visual system, though, is estimating the true shapes of surfaces. So we, with our more sophisticated visual systems and all the billions of neurons that we have, can do something that the fly can't. So we have been shaped by evolution to see the true shapes of real objects in space and time. So he was very much a physicalist. But he was wrong. I think that he was wrong, and the argument, now I'll give the technical argument, I'll try to make it as accessible as possible, but there is a nice clean technical argument that I think takes us apart very, very quickly. In evolution, there is a mathematical model of evolution made by John Maynard Smith. So Darwin was not a mathematician, his theory was deep and brilliant, but it wasn't mathematical. John Maynard Smith and others made a mathematical with evolutionary game theory. So we can now actually take Darwin's ideas and state them with mathematical precision, start to prove theorems and look at the details of his theory. That was in the 70s that the evolutionary game theory came out. And in game theory, there are things called payoffs, right? If you're playing a game, if you take certain actions, you can get certain rewards, right? There's payoffs for who your opponent is, what the situation of the world is, and what action you take, you'll get different payoffs. This is just standard new game, you think about it. There are payoffs for being in a certain state and taking certain actions. So these things are called payoff functions. And so the idea that we're shaped by evolution to see true structures in the world can now be stated very, very clearly. There must be payoff functions, that actually know about the structure of the world, because they don't know anything about the structure of the world. If the payoff function does not depend on the structure of the world and it doesn't communicate the structure of the world somehow, then it can't possibly shape you to know the structure of the world. So it's all about these payoff functions. So the nice clean, so they might show you things about the world like the metric structure of the world or orders. So there are different kinds of mathematical properties of the world that you can add. So topologies, metrics, partial orders, all sorts of technical things that you can ask about the true structure of the world. And so there's a nice clean technical question. What's the probability that a randomly chosen payoff function knows about the structure of the world? And whatever structure you want me to, again, topology, metrics, partial orders, whatever it might be. Now, we can actually answer that question. It's not just a hand wave question. We can answer the question, what is the probability that a randomly chosen payoff function actually could possibly shape you to know the truth of the world? And the answer of the probability is zero. Zero percent of the payoff functions hold information about the structure of the world. Fit wins. So fitness loses. What loses? Well, if you're going for, if you're going for truth to give you fitness, that version of fitness loses, right? You're saying to see the truth is to make you fit, that version of fitness loses big time. So, and now Yale ran this with different payoff functions in fitness one. What do they get wrong, or what, or right? Right, so in the Yale study, there are now, when you go into, so they didn't actually address this question that I'm raising, right? So, and the reason I'm going up at this deeper, when you try to go into the weeds, you can find little cases where you can, in this particular situation, get something to happen nice. Sure, you can. So, you can always find a case where, so that's why I wanted to go to the big picture here, because I've gotten a lot of little papers out there where people say, well, in this particular case, yeah, sure, you can make a case like that. But the big picture is this. Evolutionary theory does not, in its current form, restrict the class of payoff function. It says, any possible function right now is a legitimate function. Now, it's perfectly fine if someone wants to come up with a new version of Darwin's theory, an evolutionary game theory, that says, only these classes of payoff functions are permissible, and these are the principled reasons why. But we do not have such a theory right now. So, the current theory, as it stands, does not restrict any payoff functions. It doesn't eliminate any payoff functions. So then, the argument is very, very simple. When you look at the set of all possible payoff functions, and you ask, how many of these, the technical term is homomorphism? How many, what fraction of them are homomorphisms of total orders, partial orders, metrics, topologies, whatever structure you might want. And the answer is, let me catch them up. Homomorphism is a subway map against a subway. - Right, right. - The stations on the map correlate to the real world. That's what homomorphism is, just a projection. - Okay. - Yeah, the map is a faithful representation of the structure of the subway system. Exactly, that's a great way of talking about homomorphism. I'll use that in the future. I just gotta catch them up. - Perfect. - It's hard to keep up with you. - Yeah. So, the stunning answer, so the whole, all the arguments that I've given and so forth, all you need is this one argument. Tons of payoff functions, what fraction of them actually could shape you to see the truth? Oh, zero percent. So, what's the probability that we've been to shape to see the truth? Zero percent. It's that simple. It's just, the whole argument in one 30-second clip, the set of payoff functions is big. The ones that are homomorphisms, the probability zero, therefore we don't see the truth, just that simple. So, all the other arguments that people have, now here's an argument against me though. So, some people will say, look, Don, this is all high-flute and math. It sounds really great. But here's the fact. You've shot yourself in the foot, logically. Right, you started off with Darwin's theory of evolution, which assumes that there are physical objects like organisms and resources in space and time, competing with each other. So, it's a physicalist framework. And then you're using Darwin's theory to show that there is no such thing as organisms in space and time. And so, you've used your theory to refute the foundations of your theory. So, you should just learn some logic, Don. - I've seen this. - I've seen this. Oh, yeah, I've seen this. I've gotten it in publications. - Sure. - In philosophy journals. And I get it in almost every, that's where I saw them in the journals. - Yeah, in the journals, but I also get that all the time in comments on YouTube videos and so forth. - I don't read that. - Don't read that. - Yeah, stick with the journals. - Yeah, the journals. - No, absolutely, absolutely. So, the reply is very, very straightforward. Meet new groupie setting mist from Mavily New York. Gel to mist technology locks in your look for up to 24 hours with flexible all day comfy grip. Just plump, dewey hydrated skin that still feels like your skin. Try new groupie setting mist from Mavily New York. - Maybe it's Mavily. - Olen Shannon Maldonado. So, the new groupie setting mist from Mavily New York to mist technology locks in your look for up to 24 hours with flexible all day comfy in your look. So, the new groupie setting mist from Mavily New York to mist technology locks in your look. And that they don't explain. it's limited scope. It's not arbitrary scope, it's limited scope. But a great theory will give you the tools to actually understand the limitations of the assumption that sells. So a great theory will actually tell you that the assumptions that themselves are not the final word, which we knew altogether. I mean, we knew that before, that the assumptions cannot be the final word. There's going to have to be a deeper theory. So I'll give you an example. Einstein's theory of space time together with quantum mechanics. So quantum field theory. That theory among its assumptions are that space and time is fundamental. Quantum fields are defined over space time. And then Einstein plus quantum, then when you look at the mathematics, it turns out that space time itself falls apart at what's called the Planck scale, 10 to the minus 33 centimeters, 10 to the minus 43 seconds. So here's the case where the theory says we're going to start with quantum fields in space and time. That's the assumption. And then it proves that space time itself cannot be fundamental that it has in fact no operational meaning at the Planck scale. So no one comes along and says Einstein should have, and the quantum guys should have learned some logic. They can't use their own theory to prove that space time isn't fun. They assume space time is fundamental, and then they prove it's not those stupid guys. They should just, you know, they should go and learn some like no one says that is this is actually viewed as a breakthrough. This science is so rigorous, so mathematically precise, that it can show you the limits of its own assumptions. That's how we make progress. We knew that the assumptions could not be the final word, but a theory that tells you exactly where those assumptions fall apart is exactly the kind of tool for the best rigorous science. And so what I'm saying about evolution is that yes, Darwin started with physical objects, organisms, in space and time, fighting for resources in space and time. And when we look at this, Darwin's own theory with John Maynard Smith's mathematical version of it, we see that his theory is brilliant enough to show that the very assumptions of physical objects inside space and time is not fundamental. He was able to show that that cannot be the final word. So it's a brilliant theory. So that's the way science works. We will never have, if there's infinite job security and science in principle, there'll always be deeper assumptions. What we don't want to do is to fall into the trap that Max Planck pointed out, which was that science tends to move forward or progress one funeral at a time. It's better for us to let our theories die, to know up a priori, our assumptions are just assumptions. We don't have a theory of everything. In fact, my own view is we are 0% always 0% of a theory of everything. That's all the science know. And yet that's an important to have that 0%. It's rigorous and it's 0%. So it should be very, very humbling. And it means that the next generation does not have to worry that the older generation did it all. No, no, no, no. You will always have plenty to do. There's always new opportunity to do some science. You want the new generation to just start with theory of everything is 0% and go from there. Well, I would like them what the new generation has to do, of course, is to take the current theories very, very seriously. You have to study them. You have to do your homework. You have to know them backwards and forwards. There's you don't have a prayer at this level of sophistication in science. You don't have a prayer of doing something new until you've really spent several years really mastering what we've got and then allowing yourself to think out of the box and say, what are the new deeper assumptions that we could bring to this thing? So, so, so I get emails all the time from people who haven't done their studies and they've got their new theory. And you look at them and you and you realize they have no idea, but I mean they're they need 10 years of study before they can even begin and using an AI is not going to help you. You can't make this gap up. You have to know the theories. You have to have really grok them yourself. Otherwise, you will be misled by the AI. You'll be misled to think that you've got your new theory of everything and it's unfortunately a waste of time. Now, if you've done your homework, if you spent the years and really mastered the theory, then it's safe, I think, to use AI's as an assistant as you're trying to develop, because you can then step back and evaluate what's going on and you can have the AI push you around. But if you don't actually yourself know the current theories, then you can't know when the AI is taking you down the dead end. That's right. AI is great for pattern recognition, but there's no intuition there. You have to already know the subject matter. That's right. That's right. So, but if you do it, then it's a helpful tool. Of course. Before we get into trace logic, photons, the aha moment, let's kind of build a foundation with conscious agents. What are those in your framework? Yes. So, if I'm going to say that consciousness is fundamental, and I want to be a scientist, I've got to have a mathematical model. And that's no small order. The idea that consciousness is fundamental has been around for thousands of years. And there has not been a single mathematical model of scientific merit anywhere. It's truly stunning to think about that. The consciousness has been around, the idea of the consciousness fundamental has been around for thousands of years. And do you think it's stunning? There's no model for that. It seems. Everyone's surprised that you have one. Yeah. It's stunning because the model that I have is so simple. It's truly, to me, it's stunning that the in retrospect, the model is simple. And but of course, even in my case, I just discovered a big step. And it just five months ago. So, I've been at this for 40 years. So, that, well, I want to get to that moment because it helped me understand as well. When I finally was able to grasp it, it took a little bit of reading to kind of get what you meant with the math and with trace A implies B and all of that. But I finally got it. Oh, good. A lot of sense. Oh, great, great, great. And the way the universe ticks at different rate, at ticks at a certain rate, all that stuff is very interesting. Yes. Well, so, yeah, so I'll just say that that what I had to do, and what my team had to do, so Chetan and Bruce and others that have been working with me now, many others, is we have to have a mathematically precise model of consciousness. And so, what we, what you want to have the simplest thing that you possibly can, you don't want to have a Rube Goldberg device, you want to have the most cut down. So, ultimately, the idea that we have is this, what's the, for just a conscious observer, we'll do agency in a minute, but just for conscious observer, what's the minimal, minimal thing that you would want? Well, observers have certain experiences that they can have. I'm maybe like, I can see red, green, or blue or something like that. So, I want, I'm going to list the experiences that this observer can have. And the other thing that seems necessary to say, those experiences can change. I'm seeing red now, maybe I'll see blue next or red next or green next. And that's the minimum I could imagine. They're experiences, and they change. And what's the most general mathematical object that you can use to do that? Well, you list your experiences, you know, like a column, and then for, and then for each row, next to each experience, you say, what's the probability of having this experience? I'll go to that experience, or that, you just list all the transition probabilities. That's it. That's called a Markov matrix. That little thing I just talked about is so simple, it's just called a Markov matrix, and it was discovered by Markov in 1905. So, let's use the traffic light example, because that helped me understand it. Okay. So, with the traffic light, you have red, green, and yellow? Yep. In this particular case, it's a very simple matrix. If you're seeing red now, probably that you're going to see red next, zero, but you're the next, and probably that you're going to see green next as one, right? Probably that you're going to see yellow next to zero. Right. So, this is our building matrix. So, that's right. So, the first row is zero, one zero. Now, for the green row, the probability that you're going to see red next is zero. Probably you're going to see green next to zero. Probably you can see yellow next is one. So, that row is zero, zero, one, and then for yellow, probably you're going to see red next is one, and then zero for green and zero for yellow. So, that's it. So, that's the matrix for that simple case, and that's a very interesting kind of matrix. It's cyclic matrix, but most Markov matrices aren't cyclic. They're more complicated than that, but that gives the idea. So, but now, just imagine we're just going to make this following statement. All possible observers are represented by all possible Markov matrices. So, these Markov matrices could have maybe one has a thousand experiences, some tastes and colors and smells and other things. Some might have a trillion, some might have a Google, and it goes off to infinity. So, you could have infinite matrices. So just imagine if you can, it's hard the space of all possible matrices of all possible dimensions. That's the space of all possible observers. So the idea is very, very simple, but when you say we have no reason to exclude, right, I don't have any reason to exclude any set of observations or transitions. So I'm just going to say that all possible observers are all possible matrices and it's an infinite space. So that's what we do. But so each matrix now, think of it as, is an observer window. It's, it's just a way of looking. It's a way of seeing, like the traffic light. That's a way of seeing. And if you look at the traffic light, that's what you see, it's spinning around. But other things are much more complicated in this room. Now, now we probably need trillions, right, we need matrices of trillions and the probabilities are quite complicated and so forth. So that's a, but all of those are passive observers. You know, if you're, you're just sitting there, you're looking through this window and you're not doing any action, you're just watching. What about agency? How do you get the notion of agency? Well, the idea would be, suppose, a clean way of thinking about agency is I'm looking through this window, but now I want to change and look through that window or that window or that window. So how do I want to model that mathematically? Well, remember what I did with observations. I said, here are the possible observations I could have. And I'll just talk about how I could move around on those observations. You know, I'm seeing red now, now move to green now. So I moved around on observations and I wrote down the matrix for how I moved around. Well now I want to move around on windows. So I have all these observer windows. There's an infinite number of them. So I'm going to have a policy about, I'm looking through the world, at the world through this window. Now I want to move, look at the window, that through this window and so forth. That's what I call that a policy. And what is this another Markov matrix because it says, here's the probability, if I'm looking at this window that I'll look through this window or that window or that window. So it's another Markov matrix. And I can then say, well, what's the set of all possible policies? What's all the different ways I can move through all these windows? Well, it's an infinite, an infinite collection of Markov matrices. It's also another matrix, isn't it? Well, it's not itself a matrix, it's an infinite collection of Markov matrices. And then I could say, well, now I want to change the policies. I mean, I have this policy now and I want to change to this policy so I can now walk around on policies. So you can see this goes off to infinity. This is what we call recursion. So that starts to get us the notion of agency now because the passive observer windows are a very, very minimal notion of agency. There is some notion of agency that you can get there. If you take a Markov matrix that's ergodic, anywhere, anytime that you change the start state, it will always go to the same long term behavior. And so in some sense, that's a weak notion of agency. It's always trying to get to the same place, but that's a very weak notion. But now with the policies, you're moving around on these windows, that's a little bit more agency. When you can change the policies, that's even more flexibility. Now I'm changing how I'm moving around. But then as you go meta, meta, meta, you're getting ever more sophisticated agency off to infinity. So this gives you a way of unpacking the notion of agency from the most trivial, namely the observer windows, which are mostly passive, all the way out to infinity, which is infinite flexibility of agency. So for me, it's so beautiful because it means that we don't have to take on all of agency at once. We can go through the recursion once, really understand just the policies, understand what they can do. Really master that. Once we've done that, we can then go on and do the meta policies and so forth. So it gives science a way to really go through this from the least complex to the most complex. But now the thing that's really quite interesting about this, I haven't told you the most fun part. That's the recursion, but the most fun part, well, first I should say that this idea, I should tip my hat to Leibniz, who around 1700 in his monodology was, was basically saying something like this. I don't want to put words in his mouth, but I suspect that he might like this approach. Imagine setting your makeup, then forgetting it's even theirs. Meet new grippy setting mist from Mabelie, New York. Delta mist technology locks in your look for up to 24 hours, with flexible all day comfy grip. Rightness, no stickiness, no residue. Just plump, do we hydrate it skin? That still feels like your skin. Try new grippy setting mist from Mabelie, New York. Maybe it's Mabelie. [MUSIC PLAYING] Leibniz said we need to start our science with perceiving entities, observers. He called them monads. And we need to, he was quite religious, so we need to have some kind of preestablished harmony. He was thinking about God having set up this preestablished harmony so that they are coordinated somehow. They're not just random observers, completely disconnected from each other doing whatever. There had to be some kind of coordination. And at the time, of course, Newton was also trying to get a mathematical model to found science. And Newton also was quite religious. He wrote more theology than he wrote physics, but more alchemy than physics. More alchemy than physics. That's right. And so I think that he would have liked to have a situation where he could put consciousness and observers fundamental, but the math just wasn't there. And so I think what happened was that Newton said, look, we've got to go with what we can do. So he can write down f equals ma and f equals gm1m2 over r squared for gravity. We can do that kind of stuff and we can get going. So that set of equations gives you a more physicalist machine kind of universe. And so science got started in a machine kind of universe, because that's what we could do with the mathematics. I think Liebner's was right, and I think Newton would have liked to go that direction, but the math just wasn't there to do that. But now I think I can show you something that looks like this preestablished harmony that Liebner's was looking for. So I got this whole set of observer windows. So we'll forget the agency for a moment, just the observer windows. Suppose that I'm looking at, say, 10 colors. And there's a matrix that's governing how I see those 10 colors. So that's why window. But suppose as I'm looking through that window, someone somehow shuts off 7 of the colors. So I can't see those 7 colors. So I'm still looking, trying to look through the window, but I can only see 3 of the colors. Well, now I'm going to get effectively a 3 by 3 matrix on those colors. That's induced by the big 10 by 10. So there's all sorts of hidden stuff going on in those other 7 colors that I can't see. But they're there. But they're there. They're hidden. I can't see them. But they do influence what I'm seeing in the 3 by 3. So that's a good way of explaining this. Yeah, that's it. And so that thing is called the trace matrix. And for those who are more mathematically sophisticated, I do not have to make a clarification with matrices, there's another notion of trace that's even more common. You take a matrix and you add up the diagonal elements. So 1 comma 1, 2 comma 2, 3 comma 3, n comma n. You add up all those numbers and that's called the trace. So that's, I'm not talking about that trace. That is, of course, a notion of trace. But that's not the one I'm talking about. This is more sophisticated. The one I'm talking about for mathematicians is called the Sure compliment, a CHUR compliment. So you take a big matrix and you do some matrix on a subset that you can see. So I'd like a trace element, a small part of it. That's right. And so this small part is in effect reflecting the whole, but just through this smaller window. It's almost like the smaller one is observing the whole, but through the smaller window. And that's your trace. And that's the trace. And here's what I discovered about two years ago. I realized, so by the way, I should say, the trace is not me. This notion of trace has been known for maybe 50, 60 years. So I didn't invent that. What I discovered a couple of years ago was that that gives us, the trace relationship is a partial order on all Markov chains. It gives you a logic. For those who know a little bit of mathematics, it's not Boolean. So Boolean logics are the ones that we are more, most comfortable with. You can take hands and oars and compliments and so forth. So this, Boolean fits into your theory at the local level, doesn't it? It does at the local level. So this logic, I call the trace logic, it has, it's not Boolean, but it has an infinite number of Boolean sublogics. So you take any matrix and you look at all of the matrices that are traces of it and all of those matrices together form a Boolean sublogic. it's really, really pretty. - It's elegant, so unbelievable. - It's unbelievable. the local Boolean is the base of all of it. - That's right, you have an infinite number of these local Booleans, but how they get tied together, we're still trying to understand this is nasty math. We're still trying to grok this, but I still remember two years ago, when I, working with Chetan per caution, I said to him, "Chetan, I believe that this trace relationship will give us a logic. It's a partial order and it gives us a logic." And his response was done, that's too pretty to be true. But then he went off and proved it. What he had to do was to prove that it has a transitive relationship. And so he proved that and we had the logic. - Transitive, so the trace A implies B. - That's right, so the trace of a trace, he has a trace. So I have a big, so I have a 10 by 10 and I trace it under five and then it trace the five down to three, I get the same answer as if I went from 10 right straight to three. - What did he say when he called you from Heathrow after he proved it? - Well, I think it was fairly a matter of fact. Yeah, it's true and I was, I believed it was true, I believe it was true, but when Chetan says it's true, then I know it's true because Chetan is brilliant and he doesn't usually make mistakes. So I was really quite pleased. So it's this beautiful logic and now you can see that it applies to the observer windows, but not just to the observer windows, now it applies to the policies, the first level of agency 'cause there, that's a whole set of Markov kernels. So there's a trace logic on them and then there's a trace logic on the meta-polices and the meta-meta-polices and so, so you get a recursion of these trace logics all the way out to infinity. And I want you to propose that this is the pre-established harmony that Labanus was looking for. Wow, so there's all these observers and they're tied together by this beautiful recursive mathematical logic. So we are still trying to understand this logic. This is, there's a lot of mathematics to be done on this. And what's the establishment responding to this? Well, it's, the theorem is true. So yeah, so there's no problem with the theorem. But a chaton proved this, that means others can. That's right, but in fact, for a mathematician, this is falling off a log. Right, to prove that theorem is, I mean, chaton was due to Heathrow, while he was waiting in the, you know, he had Heathrow for something, he proved it. So it's the kind of thing where a brilliant mathematician like chaton can prove it pretty quickly. So that's just logic is just logic. So what, right, how do we bolt your philosophy onto it that makes it controversial? Right, so one way to look at what I've just said is that I just did discover this new structure and recursive structure on the set of all Markov chains. So that's a contribution to mathematics. And as a contribution to mathematics, it's not controversial at all, I don't think. But now I'm interpreting this as applying to consciousness. And that's very controversial. So, so, and here's the kind of thing that gets publicly stated about this. So, so there will be, there was, I don't know if I'll mention the person's name, but some very, very prominent person with YouTube said about this that this is complete nonsense. Of course, Markov chain are fine, but to use them for consciousness, this person said, you know, see, Markov chains are used for standard stuff, like predicting the weather, predicting stock markets and so forth, nuclear fission, nuclear fission, the page rank, that's right. So, exactly, it's used for all this stuff. And to say that it applies to consciousness is nonsense. There's nothing in the mathematics that says this is consciousness. So, the mathematics doesn't care about consciousness. So, for Hoffman to even say that it's about consciousness is just a rookie mistake. So, a lot of people have said this. And my, I've seen that, but I haven't seen them explain how you're making a mistake. No, they just say that. They just say that that is a mistake. And they don't say how that is a mistake. And I'll explain how it's not a mistake. Okay. The math never tells you what it can be applied to. So, the fact that, I mean, you could also say, you're using Markov chains for stock markets. There's nothing in the Markov chains that said they can be applied to stock markets. You're using it for weather. There's nothing in Markov chains that this should be applied to weather. So, as soon as you see that, you really, the claim you can't use it for consciousness is silly. It's just plain silly, 'cause you could apply it to any other application. The math does not tell you any applications. They said, this is a structure. When you use it in science, what you do is say, I think that this scientific arena might profitably be modeled by this structure. Maybe it's stock markets, maybe it's weather, maybe whatever it might be. In my case, I'm saying consciousness. And now, I think what's really going on is the argument that the giving is out the real reason that they don't like it. They just don't like consciousness. So, what they're really saying is consciousness is nonsense. And so, you're trying to attach nonsense to Markov chains. And you could be right. Maybe consciousness is nonsense. We'll see. Right now, physicalist approaches cannot explain the single illusion of conscious experience, much less conscious experience. So, you know, if in 50 years, we're still batting zero, I would say it's over for physicalism, it's over. And if we can start with the theory of consciousness, modeled by Markov chains, and we can do some real work with that, and we can talk about the work like building up space time. Yes. Then I would say, it doesn't prove that consciousness can be modeled by Markov chains, but it sure makes it a pretty interesting scientific hypothesis, certainly not nonsense. Well, let's build that bridge. Let's go from the chains to consciousness, because we haven't really built that bridge yet. How we get there. Right. So, the idea, the reason that I was intrigued by using Markov chains for consciousness is that we do just have at the very, very most elementary level, the experience of colors, shapes, and even more complicated, I think, three-dimensional objects, and so forth, and they're changing. So, at the very, very minimal level, this Markov model works. Now, one objection might be, Markov chains have a finite history. I mean, they have a finite memory in the sense that the next transition is determined by the current state of the chain. Yes. So, some people say, well, that's a finite memory kind of thing, and that's just way too limited. But it's not, because it's well-known in Markov chain theory that you can easily create bigger, more complex states. You can take a series of 20 states and make it one state. So, as much history as you want, you can build it into states. So, it's really, there's no limits. And you can have an infinite number of states and make your histories as long as you want. And you can make the individual experiences quite complicated. I mean, it could be not just something, I use red, green, and blue, because it's very, very simple. But it could be a particular three-dimensional shape, your sphere, or a cube, or so forth. And then you can go even more complicated things. So, the kinds of experiences that you can have can be arbitrarily complicated. So, it seems to me that it's a good hypothesis to use this Markov chains in the-- what I call the recursive trace logic, the recursion of Markov chains policies, and metaphols, and so forth, with the trace logic. As the theory of observation and agency, because it's the most general and comprehensive, the least assumptions, there are experiences, and they change. It's amazing. That's all I assume. There are experiences, and they change. That's it. Literally, that's it. Everything else, and then I say, the best way to do that is to model it with Markov chains. That's all I assume. The recursive trace logic just falls out of that. It's just a theorem. So, I love that in a scientific theory. You make a minimal assumption. I'm going to start with consciousness. I'm going to model it as experiences that change. The minimal model I can give is Markov chains. Oh, by the way, no one noticed it, but there's this partial order, the trace logic, on all this, and it's recursive. And this gives us a theory of agency. It's just that simple. So, consciousness is just a state that can change. But it can change, but the policies and meta-polices are doing it in sort of an agentic way. And in some sense, they're saying, given that I'm looking at the world through this window, now these are the different ways that I want to look. So, that brings in a notion of agency and a notion of time, which is quite interesting. Because you can't choose what next window you're going to go to until you have a current window. So, it brings in a very observer-centered or agent-centered notion of time. And someone might say, well, these are just Markov chains. You're not showing any deliberation. You're not showing any irrational reasoning here. Or like, what are the goals that you're in the payoff functions that you're trying to minimize or maximize in your choice? And I would just say that these are different levels, different ways of describing the same thing. If you give me. A decision-theoretic description of an agent that says, "I have these goals. I have these kinds of actions that I can take. I'm modeling these kinds of worlds and so I can then model what these actions would do toward my goals in these different worlds." And you can write it out that way, but ultimately, when you write it down, you'll get a mark of change. It says, "What's the probability given that I'm in this world that I'll go and do this thing and go to that world?" So there are just different ways of describing the same thing. So I like the mark of change because it has this recursive trace logic. And I think also because it's looking to me like we'll be able to show how we can build space-time and quantum theory from just this recursive trace logic. So I should say, "I've been very, very hard-nosed in this interview about the physicalists, right?" They start off with space and time and physical objects as fundamental, then they owe us a precise physicalist account of conscious experiences or the illusion of conscious experiences. No hand wave. Show me how we get the illusion of the taste of mint from neurons or whatever you want. Show it to me, or why should I believe you? So turn around. Now what my colleagues will say to me is, "Don, great. You got this nice mathematics and you're claiming it's consciousness." Great. Where then the space-time and quantum field theory and the born rule and all this stuff come from? You've got all this nice stuff of consciousness. What you owe us is show me Einstein's special theory relativity, general theory relativity, quantum field theory and eventually quantum gravity, give us non-locality, give us the born rule, give us the big bang. Can you give us this? Well, I just gave my colleague, NIFA and Chaitan tentative proofs of getting special relativity and general relativity. It looks very, very plausible to me and I've got a working on the born rule. Geldermist technology locks in your look for up to 24 hours, with flexible all-day-gum v-grip. No tightness, no stickiness, no residue, just plump, dewey hydrated skin that still feels like your skin. Maybe it's Mavily. So are you integrating time dilation and space dilation? I am and I can give an intuition about why we might expect that this would work. Please. So one thing that Einstein taught us is for special relativity is suppose that you're on a train and you're going past me. I'm sitting at the train station. I'm watching you. You're going past me and you have a clock and you have a meter stick and I've got a clock and I've got a meter stick and I look at AJ's clock and for me it looks like your clock is going too slow and your meter stick is too short. And you on the train looking at me, you would say, "Well, no, no, no, don's clock is going too slow." And don's meter stick is too short. And that's pretty stunning. I mean, that was stunning that Einstein came up with that and very counterintuitive and wasn't accepted right away and so forth. But experiments have shown that that's correct. The meter stick changes side. Is there a calcium spacetime factor into this? That is where men, calcium spacetime comes from. This is where, when you don't have gravity in volume, when you don't have gravity. So this is just men, calcium spacetime. So Einstein did this in 1905. It wasn't until 1915 that he came up with curved spacetime. It took him 10 years to really master the mathematics for that. I was at all. Well, it was a herculean job, truly impressive. So how do I do that in this Markov chain theory? Why should we believe that I could get Einstein? So one thing I haven't mentioned is that it's standard to Markov chain theory to have a little counter for a Markov matrix. So every time you have a transition of state, you just increment the counter. So like with red, green and blue, I see red, one, oh, now I see green, two, oh, now I see blue, three, and you just keep counting as things go. So that's called an enhanced Markov chain. So we call it an enhanced Markov chain. This is standard stuff in Markov textbooks, that's not our invention. So notice what happens. If I have the 10 by 10, every time one of the 10 colors changes, my counter is going. So red, green, yellow, blue, whatever it might be. The counter is going. But only state change. Only for a state, for each state change, right? Every time a color changes from red to green, or red to red, right? So you could have red changed to red. Sure. So now suppose we go back to the three by three sub window. Yes. Notice that say it only has red, green, and blue, and not the other seven colors. So it is only going to up, it's counter when red, green, or blue happen. But it won't catch yellow, purple, pink, or the others. So notice it's counter isn't going to go as fast as the big counter. The big matrix, the 10 by 10, is counting every one of the 10 colors changing. The little three by three is only counting three, though. So it's only getting 30% roughly of the counts. Well, let's, let's help, help people understand. Yes. Let's have the colors changing. Give me, give me color glasses. And let's, and let's take, let's click our counters together. Right. So, so suppose I have, let's keep it simple to like, then just three versus two colors, right? So I have red, green, and yellow. So we're at a traffic light. And so every time it changes from red to green, green to yellow, and then back to red, you, you click your thing, you click your counter. But now suppose you don't see the yellows. So all you see is red and greens. So you only get the red, anytime red changes to green and green changes to red, you click. But you don't get any of the yellows. So you're missing a third, right? One out of three counts. Right. You're clicking your counter every change, but I'm missing a third of them. You're missing a third of them. And so one clock is only going at two thirds, the speed of the other clock. And that is where we're going to get Einstein's time dilation. From there so time is moving slower for me. Because you're counter. You're seeing my counter slower. That's right. So the reason I think, the reason I think AJ's counter is going slower is I don't, my Markov chain has a, is not completely intersected with yours. So I'm not counting all the stuff that you see. Right. I'm not, my counter is not going, of your stuff is not going as fast as your counter does. So your counter is going faster than, from your point of view. But the same way is, that's why it's, it's, it's symmetric. From AJ's point of view, my counter is going to slow because you're missing some of the stuff that I see. Right. So that's why our counter, we get the time dilation. What's the minimum unit? Is that a plank time? Now that would be a universe frame rate. Well, in, in the, in the recursive trace logic, there is no minimum. There is, so the notion of time, the notion of time is a space time notion. There's no unit at all. Right. There's no, there's no, in the notion of seconds. Right. Right. Right. So if we, if we're talking about like the plank time, that would be 10 to the minus 43 seconds. But the very notion of second is, is alien to the recursive trace logic. It only has counters. It doesn't have the notion of time. But what I have to do is show that I can use the recursive trace logic. In fact, to you, I can use 0% to the recursive trace logic to build Einstein's special relativity. Don't you need some type of base measurement in order to get your counters, you have to be counting something. Well, so there will be a, like a fundamental clicker in the recursive use logic. But it, we won't have the notion of seconds tied to it at all. It will, it will. I guess it doesn't need it then as long as it's there. Well, and as long as it's there, it, it could be instead of 10 to the minus 43 seconds. It could be 10 to the minus 43 trillion seconds. In fact, 10 to the minus infinity seconds. So it really can be as small as you wish. So, but our spacetime is stuck at 10 to the minus 43 seconds, which is actually, if you think about it, why not 10 to the minus 43 trillion? So what? And also spacetime falls apart at 10 to the minus 33, we might think I was pretty small. Well, what about 10 to the minus 33 trillion? Why should spacetime fall apart at 10 to the minus 33? That's a fairly shallow data structure. So, so what, what, what I have to do is to show how I can use the recursive trace logic, which doesn't even have the notion of seconds. It just has Markov chains with counters and I have to show how we can create a, what I call a headset. I was going to ask you about that. VR headset because, because you can still make this work, this is, this could still be physicalism with the Markov chains. Oh, sure. Absolutely. It's only with the headset, do we now make the leap to consciousness? Well, it's only with the headset that I'm able to make the leap from saying that the recursive trace logic models consciousness to say, and here's how we get what we call the physical world. So that's what, when I'm building a headset, I'm saying, I'm starting with this universal consciousness, the recursive trace logic, mathematically described with the, the pre-established harmony that, that liveness wanted. Yes. So that's what, you know, that's what liveness wanted, I think. Now I have to show you how we get Einstein's special and general relativity, how we get quantum field theory as a special model within the recursive trace logic. And what I have to be very, very careful about this, I don't want to prove that the recursive trace logic forces us to see the world like through Minkowski space or general relativity or quantum field theory. It doesn't. All I need to do is prove that it allows us to build those structures. In fact, I would be disappointed, bitterly disappointed if it forced me to build those structures, because I want the flexibility to show that our space time is one of an infinite number of headsets that consciousness can build. Consciousness has the flexibility. We have, I think, my view is ours is the one of the most trivial and simple space time headsets that's available. We have the training wheels version, really dumbed out. So our view that we're like the top of the food chain and then we're top of intelligence. My view is, no, no, our space time headset is one of the most trivial ones that could possibly be. And we can show, I plan to show, and I think I've got a version of the proof right now, but it's not real until it's published. So I've got I've got a proof that I like. Chaiton likes it. Chaiton is looking at it and NIFA are looking at it. So Chaiton and NIFA are two mathematicians that I'm working with. So it's not real until they say it's real. And in fact, even then, it's not real until we do peer review publication. So the headset is how we perceive reality. If ours is is very basic, that implies that there's something more advanced. The mathematics makes it very, very clear, but that there's an infinite number of far more interesting headsets than an infinite number. Infinite number. There's unbounded. So ours is one of the most trivial. You can think about ours as being a trace of much, much more interesting, bigger headsets in a way. But even among the 3D headsets, right, there are human kind of 3D headsets. Presumably, mice might see in three dimensions, some birds might see in three dimensions. And their headsets are going to be a little bit different from ours. It's still three dimensional, but it's going to have different features than ours. So what we're going to want to do is I want to first prove that I can get a generic space time headset, a generic one. Not, not, not human. It's not mouse. It's not bird. It's just a generic one. And then what we want to do is then look at like the neuroscience of humans. If there's an infinite number of headsets above that must mean there's an infinite number below. There could be quite a few below, but it's hard to go below three dimensions and one dimension to four in terms of number of dimensions. You can three, two, one dimensionality is important. Well, for that kind of measure of headsets, if you're going to have dimension, now you could get rid of dimension as well. There could be headsets in which you just have topologies and not dimensions, for example. Right. That would make every headset a mean then. No matter where you are. Well, yeah, there's a, you can't think big enough. There's infinite number of different kinds of headsets that you can so humans don't like infinity. We don't like infinity. We like to think that what we're seeing is the truth and what I'm saying is that from this point of view, space time, which science thought is the final reality and everything is inside space time is, in fact, one of the most trivial headsets that you could build out of the recursive trace logic. And there's an infinite number of more complicated headsets than what we've got. And I think that we are the consciousness that's capable of understanding those headsets. I mean our species, our species, our species is a headset representation of the consciousness that is actually able to do all of this stuff. And so part of our joy here is to enjoy this headset, yes, to wake up and realize it's just a headset. And to realize the lila thing, this is a game. We thought we let ourselves get lost in this game. And we can smile once we wake up and realize, oh, we thought this was the whole thing. Oh, no, no, this as beautiful as this is, as complicated as this is, as completely engaging as this world is. It's trivial compared to what you can do. There's infinite. Yeah, that's the idea. That's the lila kind of thing. Let's play with this. Let's enjoy this. So you know, relax and play with this. See what you really can learn from this. Be open, explore, and then realize that you infinitely transcend this. And the recursive trace logic puts that out mathematically. You can infinitely transcend this in the sense that there are an infinite number of other headsets that you can build. Is there a way to practically describe what those headsets can see? Well, there's a monkey brain. Well, there's one one way of thinking about it, just one simple way is to go from three dimensions of space to four to five to 50 to a billion and so forth. So that's one way. Dimensions are infinite as well. Yeah, why not? Why not build dimensions off to infinity? Okay. And that's just one direction. And then you can let go of the notion of dimension altogether and just try different topologies and so forth. So there's a soon. See, that's the thing you cannot think big enough here. Right. And the mathematics really helps you. All these structures that mathematicians have discovered open us up to realize all the different possibilities and the infinities. So, so I study mathematics because it really helps push me out of my little boxes, out of my little, you know, dead ends, thought dead ends. So I've heard you say you know enough math to get into trouble, not enough to get out. Who gets you, who gets you out? Well, so my, my good friend, Cheeton has worked with me since 1984 or something like that. So it's been 40, 42 years he's put up with me. And no, we're, we're, we're, very good. He's, he's brilliant. I was, I've been very, very lucky to, to work with him and Bruce Bennett worked with me until early 2000s. And, and Bruce was brilliant on now, now working with NIFA, Hermanson, who's, he's, he's a, he's an expert in Markov chains, in fact. So this is his area. And at the Trace Institute, we're, we're looking to get some more math petitions now to, to, to work with us on this. So you were, you were building up the better, you're building up a nice, a roster over there. Which, which, what's the Tuesday like at the Trace Institute? Well, um, right now it's, it's distributed. So we, we meet by Zoom and so forth because NIFA's in New Zealand and Cheeton is in, you know, he's about an hour and a half away from me. So it's just the, the normal thing. So our meetings are, you know, on a Tuesday would be, um, uh, so Robert Prentner is in, um, Shanghai. He was a former postdoc of mine. He's now a professor of Shanghai. He's working with us. He's going to be the leader of the, of the, of the Trace Institute. He's a younger guy that I'm 70. He's in his 40s. So it's, it's time for me to make sure that someone younger is in charge. What's the mission statement for Trace? Well, the mission statement, um, I've forgotten the exact mission statement. So I'll just, I just mean generally, trying to accomplish. Yeah, the, the idea would be to really explore this recursive trace logic, get it completely understood mathematically. And then prove we have nine conjectures that the Trace Institute has published on, on the site. The first is that we can build Minkowski space, Einstein's special relativity. That's the first conjecture. Second one is we can build general relativity. Third is that we can get the born rule. One of them is to, we can get the big bank. Another one is that we can get quantum non locality. Um, you can get non locality out of this? Absolutely. That's the, that we can get non locality out of this thing. So we can get everything from, of quantum mechanics, if we can't them were wrong, by the way. So I, I'm saying these conjectures are things that anybody would require me to do. Didn't Tristan give you a challenge? Didn't you ask you to derive the Schrodinger equation from using this? Well, yeah. So we have, that would be cool to solve that. Exactly. So we, that's one of the conjectures that we can get all of quantum field three. So, so not just Schrodinger equation, but quantum field three completely out of this. Uh, no bell is probably listening. You can get that working. I mean, is this something that practically you can release like, well, hey gang, we solve this. Conjecture four is done moving on. That's right. That's, that's, that's our goal in the next two or three years is to get these nine conjectures proven. That, that's the first quantum field theory within three years. Yeah. That's, that's our goal. We're trying to show. So we don't have to show that, um, recursive trace logic uniquely gives us quantum field theory. All we have to show is that it can give us quantum field theory. But then we want to show that it could give us infinitely many, uh, other kinds of, of structures that are probably much more interesting than that. So, so, so that's what we're up to right now is, is, but we have to get this headset. The idea is that for our scientists, what's going to impress them is this, is the mathematics and the space time physics that we know. So, Einstein's general and special relativity, quantum field theory, the boring rule, big bang, and so forth. If we can nail that down, um, and here's one just real, brief reason why, um, I'm sure we can do it. The, the set of, the space of all Markov chains is computationally universal. Anything that can be computed by any throwing machine can be done by Markov chains. I mean, the math makes complete sense to me, the jump to consciousness. I can't get my mind around yet. Uh-huh, in what, in what sense? Um, I don't know why consciousness is fundamental is even required for this to work. I feel like this could work with, with physicalism just fine. Well, what you could do, of course, is to say, "I don't like the consciousness stuff. I just want to have this be a theory of observers and agents without putting the consciousness label on it." And it would work perfectly fine. So consciousness can just be a label? It could. Here's the reason, though, why that might end up being uncomfortable. I do feel like if you hit me on the thumb with a hammer, that I feel there's something I feel that I can't ignore, and it's a real experience, and it's an unpleasant experience. And then it feels, if anything is real, that painful thumb is real. And if that's not real, I don't know what is. And if the taste of chocolate isn't real, I don't know what is. The abstract structure that we call space-time may or may not be real, but my experience right now is to look around, that's real. You know, Einstein gives us some mathematics that we call the space-time mathematics that nicely describes this. But all I know, really, personally, is I'm experiencing colors and distances and smells and so forth, and Einstein's stuff is great, and it works well. But I'm not sure that that's the final reality that that might just be a description of my particular kinds of experiences. What about a, you know, a shark or a bat? You know, this using echolocation. Well, why should its world be anything like my world? So there are all these sensory worlds. Explain that to us using, uh, ants and hands. Yeah, how an ant has a certain world that it perceives. Right. Well, so, I mean, I don't know too much about answer. I think they use. No, I mean, chemical signals. I mean, it was just an example that you thought was very interesting about how, uh, from an ant's perspective, you can just reach down and kill that ant anytime. Oh, right. Yes. So I guess sort of a headset. That's right. So, yeah, in fact, so that's right. So to see that we're in sort of different perceptual worlds from other creatures. Yeah, then it's pretty straightforward. Yeah. So if I see an ant crawling around on my, on my dining table, I can kill it, and it won't even know what's about to happen to it. I can just put my finger on it and, um, you know, my wife probably wouldn't want to do that. She probably put it on a piece of paper and take it outside and try to be kind. But so, but the ant wouldn't know in either case. No, I should say that's from my perspective about the ant. From my perspective, the ant doesn't seem terribly bright. I mean, it does some, it does some chemical tracing and so forth. And it can do some apparently dead reckoning. It can wander around and then dead reckoning. So it does some pretty smart stuff. But from my point of view, it looks pretty simple compared to a human. But if you ask yourself from an ant's point of view, how much would the ant know about aging? Nothing. Almost nothing. And it might not even know that you're there. Right. But if it did, maybe it's representation of AJ would be as simple as my representation of an ant. You know, it's just that simple to it. So by symmetry, I've asked myself, so what I think of as an ant, maybe that's just because of limitations of my own headset. Maybe if my headset is dumbing things down so much that I'm actually interacting with this incredible intelligence far greater than me, far more capable than me. And you just have a trace matrix of that. That's right. I'm just seeing a trace of this thing and I'm getting an ant. And that's because all your headset allowed you. That's all your headset allowed you. And it also means that there could be. This is where a UAP stuff comes in and so forth that there could be other consciousnesses or observers of you don't like conscious other agents or consciousnesses or observers that are in much bigger headsets than ours. And our headset is to them like perhaps the ant headset is to us and we can go down and smash the ant anytime and they could come down and smash us anytime because we're trivial compared to them. So the headsets can go off to infinity. Let's take a quick break and we'll come back and we'll actually talk about those entities with the headsets. Okay. So Andrew Galamore was sitting right in that chair not so long ago. Yes. You guys are working together, which I love. Your first project is literally titled our DMT aliens real. Are they? Well, I think he and I both probably agree that the emphasis on real is probably a little bit misguided sort of what it's it catches attention. Yes, it gets funding. That's right. So the idea would be that there are all these different kinds of headsets that are possible ours is not the final reality space time is not the final reality. There could be all sorts of headsets much bigger than ours that could play with ours. People in the entities and higher headsets could play with us like we play with ants. And so the idea then is does DMT just screw you up right make you hallucinate or does it perhaps somehow allow us to modify our headset in certain ways. Open it up to more dimensions, for example, maybe more dimensions of space, more colors. Maybe even new kinds of conscious experiences altogether. That's and if and if so, could the entities that we're seeing in the DMT space be avatars. Just like when I talk with AJ, you know, I'm not directly in contact with your consciousness. I'm seeing an avatar we call the human body that's allowing me with my headset interact with your consciousness and you see the Hoffman avatar allows you to interact with my consciousness. So these are these are avatars, but even these avatars don't exist when they're not perceived. So I said earlier that you render this on the fly. So the AJ that I'm seeing is in some sense not real because that AJ has gone gone is completely gone. Whereas the consciousness presumably is not gone, but what Hoffman's avatar of AJ is gone, whereas AJ is just fine. And so the question is, are the DMT entities good avatars? So it's nothing are they real, but we put real in because it's catchy. So it's not that they're real, but are they genuine avatars and one thing about an avatar is that you can sort of share information. So I could tell you something. And then I could ask you to tell someone else and then find out from that someone else whether they said exactly what I told you. So that's the kind of question we can ask about these these DMT entities could could we send two people into DMT space. Is there some avatar there's just like various avatars that seem to come up all the time they do I've been in that space they've been in the space and it feels more real than this. I heard that the resolution seems higher everything seems this seems like the low resolution seems black and white it does. And the funny thing is that's what the recursive trace logic is telling me is just saying this is one of the cheaper headsets. That's right. I didn't even connect that. So what I say this is a cheap headset I really mean it that that we got we got the the cheap version and they're much much and probably even the stuff that you're seeing in DMT is cheap compared to other stuff done. There are certain psychedelics that I do that I don't need reading glasses for like a week. I can just see you just see colors are sharper my I just don't need the glasses anymore. It drives my wife. She's like you can read that I said I it's like superpowers for about a week. It's something about your plasticity that is I want to see that's the kind of thing that we have the. Chance to really understand with the recursive trace logic if we understand how to build this headset we understand what DMT is doing. To change the headset then we're going to be able to understand and reverse engineer this stuff and and actually come up with now NIFA has actually done quite a bit of DMT or some DMT. He's a mathematician and he told me that he went in and saw a tesseract of four dimensional cube rotating in four dimensions rigidly. So that's good evidence from again, it's not proof, but it's good evidence from a reliable mathematician that he was at least in a four dimensional space and was seeing a rigid tesseract for a fraction of a second. He didn't keep it for a whole second, but he saw it. So it suggests to me that it's worthwhile that that's not proof I mean hard no scientist that's not proof, but it's very suggestive that perhaps DMT in our headset is a representation that chemical is a representation in our headset of a tool outside of space and time that allows us to change parameters of our headset. And so as we begin to what we have to do is prove our nine conjectures build the human headset once we built it and there's going to be a lot of neuroscience, so we're going to have a neuroscience team working on this we're going to. There's 86 billion neurons trillions of synapses we have to understand that is just I and this all be very slow here the brain is a headset representation of how the headset is constructed. That's a big. concept. Yes. Rain, the nervous system gives a headset representation of how the headset is constructed. So I'm not getting rid of neuroscience. I'm saying we need more neuroscience and it's going to be much harder than my colleagues and neuroscience think it is. Understanding the 86 billion neurons and trillions of synapses is just the first step. The hard step is reverse engineering it to understand the software from the recursive trace logic that is being used to build the human space time headset. Once we understand that, and it won't be next week, no. We can then ask the technical question, what is DMT doing to the construction of that headset? What exactly is it doing? Is it really just taking us from three to four dimensions or does it take us to more? What else is it really doing? So we'll be able to re, once we do that, we'll understand the software that's building our headset. And if you think about it, once you know the software that's building a VR game, you can do miracles in the game. That's true. So you can change any rule and you're no longer bound by the rules of the game because you're the master of the game. You're writing the rules. So in Grand Theft Auto, the guy who is the wizard is wonderful. You can play all the game by the rules in the game. But the geek who wrote the code can take the gas out of the car of the wizard. No, he's got, he's got, he's got, he can do anything he wants. And so that's what we're, that's when, so I think the recursive trace logic, when we get these nine conjectures proven, and we began to understand how this headset is designed, you cannot think big enough about the technologies that will come out of this. It will make everything that we've got seem like firecrackers. And I'm looking forward to that. I think that it's going to open our eyes. When we see, when people see the technologies that come out of it, then it will be game over for physicalism. Wow, these are these are big goals to replicate the brain as a headset. Do you actually have to create an artificial neural network, or do you just do it with proofs? Well, we will, we're already sort of right now looking at the neural networks and trying to construct them through all the like very clean microscopic sections and so forth. We're piecing together what we can see inside space time of our of the neural structures. We're putting together all the physiology of it, so it's really, really complicated process. So we need to continue to do that. But then we have to ask, now think out of the box, think out of space time completely, right? Because you're only, even if you got the brain perfect, you're not seeing everything. No, you're only seeing of compression, so there's something really complicated software out here, so to speak, some software that gets compressed in this headset into what we call the brain. It's really complicated inside this, the 86 billion neurons of synapses looks really complicated, but it's trivial compared to what's outside, completely trivial compared to what's outside. This is all restricting. Our headset is really restricting, funneling down, losing information, so really more money for neuroscience, not less. Right. A lot more. Yeah, we're living the compressed data stream. We're not getting a lossless data stream. That's right. Once yourself and your own experience in DMT is that this is already feels like the lost, the lossy interface. It does. So you brought up UAPs earlier, so is that what they are? Are they objects in the higher, using a better headset? I don't know, but I can say that the recursive trace logic leaves that possibility open and it gives us a rigorous way to begin to think about it. One thing about the recursive trace logic is, as we talked about earlier, it's about attention. If I have the 10 by 10 of colors and you've only seen the three with you, you're only paying attention to three of the colors. There's all sorts of magic that can happen outside in the other seven colors. And when you look at the trace construction, you have your visible states and that matrix then there are transitions from the visible into the invisible. So in the markup matrix, the big matrix, you have transitions from the visible to the invisible. Then you have transitions among the fully invisible part, the seven by seven. And then you have transitions back in. So you have the exit, the external world, and the re-entrance. Wow. So that, that could explain everything from UAP teleportation to particles appearing out of the vacuum. That's right. So it shows you how to exit from our space time headset, how you could have an entire world that's far more complicated than our headset, infinitely more complicated, and then re-entrances. That's one aspect of it. Another aspect is just the magician's trick. Lot of magic that happens in magic shows is by manipulating your attention. Right. I do this and you automatically have to go over there and now I'm doing something over here. Right. So the recursive trace logic is the logic of attention. And all you, so one way that you can have these things happen is just distract and change. So again, the recursive trace logic is all about it. So there are all sorts of tools that, once you're higher up on the recursive trace logic, that you could use to hoodwink people, you know, consciousnesses that are stuck with smaller headsets, all sorts of tools. So I'm really excited to look, but right now, then we have the tools that we wouldn't have in space time. If you're stuck in space time, we have Einstein's theory of gravity. We're trying to get quantum gravity. But with gravity, you cannot do what these UIPs seem to be doing, hover with no apparent propulsion, move at Mach 40 instantly, at 466 G's, go into the water with no displacement, go into, that's right. That's just not possible with our physics. But it's certainly possible if you know the software of our headset and you play with the software. Right. So we're the ant, then. We're the ant, that's right. And they, if they understand the software of our headset, it's just like the grand theft auto. The geek that wrote the software, the wizard will be stunned by what you're doing to him. Hey, I have no way. It doesn't obey his rules, it doesn't obey his laws. He'll say, this is impossible and it's not impossible because the geek is not stuck in the headset. Right. The geek is making the headset. So when we may be dealing with UIPs, we're dealing with perhaps higher levels that understand how our headset is built and can play with the software rules. It feels like they're doing that. So the UIP doing Mach 40 is just hitting that quicker faster than we can perceive it. That's right. Or it could be distracting us. So it's going to be a trickster element to it for sure. There could be a trickster. And that's again what I was talking about earlier about the Lila kind of thing. It's, it's, they could be playing with this. It's very, very clear from the technologies. If they wanted to destroy us, we would be helpless. Oh, yeah. Of course, Lila helpless. So it's, it's not like there are cases where it seems like there's some kind of hostility and so forth. However, really hostile, we wouldn't last five seconds. So I get the feeling that there is, again, a, a, a, a, a, a, a, a, playing aspect of this. Let's explore more, let's play with these. And, and if it really is the one consciousness looking at itself through various headsets, it could be the one consciousness saying, I put myself on these really stupid human avatar headsets. Really, really, I want to give them a little prod from a little higher headset to sort of wake up. So it's the, the one source consciousness playing with itself at, at various levels. But with recursive trace logic, we could begin to scientifically see how that is, is being done. But I would put a humble note on the whole thing. I think the recursive trace logic is just a scientific theory. It makes its own assumptions and I look forward to replacing it at some point. So that will need to go beyond recursive trace logic. For right now, I think it's a good next step forward. But whatever conscious the fundamental reality is, what we might call the source, it, it transcends any scientific description, including mine. So, so the, but I would say the recursive trace logic is really the logic of infinite number of perspectives. It's the logic of an infinite number of perspectives that the one source can take on itself. So they're all consistent perspectives, but they're all mutually, can be mutually inconsistent. But each one by itself is consistent, each, each boolean logic is a consistent view, but different boolean logics can contradict each other. But they're all useful perspectives on the source, which transcends all of them. It's beautiful. If we, if we have evolved to not able to perceive that, is that an impediment to the research? Is there, maybe, does the source just say, well, I'm not going to let him figure this out? Yes. So you and I are just the source looking through a particular headset. And there are certain things, we, we know that the game is such that there are very few of us who, I mean, there are, the Einstein's are very few, right? Right. Right. The Schrodinger's, Einstein's and so forth are very, very few and we were grateful for all of them. We are. But they're trivial, the Einstein's and Schrodinger's are trivial compared to what's out there to be discovered. Yes. And yet you and I are fully that source and we, you know, we're going to, we're going to, In silence, go into the space of infinite intelligence that it is. So all of us, in some sense, are that infinite intelligence. And we've chosen to play in this avatar, and we've chosen to allow ourselves to have limitations, to actually just take this perspective very, very seriously to look at reality, to look at source through this particular lens and to play. So really it's, it's, we take ourselves very seriously, it's all very, very serious and so forth. But really it's about playing with this perspective, really enjoy this perspective. And then let go of it and realize this was just a perspective. And you infinitely transcend it. I think I have learned your philosophy and it comes out of your, your heart scare after COVID. Yeah. COVID, you're, you're running, hearts gone in 190 minute for 30 hours. You're in the hospital, two surgeries, you text your wife goodbye. Yes. What was in that text? It was very, very short, because I was, you know, I just was in a horrible place. I was exhausted. I couldn't hardly think. I, I, I, I, I sectored my wife and then I, I think a text of my daughter separately. I, I just said, I don't think I want to make it. I love you. Goodbye. Something was that was just that simple, same thing to my daughter was something like that. I don't, my heart's been beating 190 beats a minute for 30 hours. I don't think I'm going to make it. I love you. Goodbye. Um, I, I, as soon as I did that, I laid back in the bed, today, just to wait for it to happen. You were at peace in that moment or were you scared? I was scared. Sure. It was exhausted, my heart was racing. So even just though racing a hard night to beat some minute, it feels like you're, you're, you're scared to death because you're, your heart is racing. Yeah. So even though it's just, it's your fibrillation, it feels to you like you're, you're scared to death. Now, I've only been recently starting to talk about this at that very moment when I leaned back. It was about three in the morning in the hospital. I saw these two male figures standing next to my bed. I hadn't seen them before. And one of them male figures looked to the other, smiled briefly and nodded his head. Then all of a sudden, I felt an incredible warmth in my heart. And my heart started beating normally. What? I, I, so I looked down and I looked up and I didn't see them anymore. And neither of them was wearing hospital garb. I haven't heard you talk about this part of this story. Now, I haven't done it publicly before. What do you, what do you think they were? I have, I didn't talk about it for several years because I, I mean, this is so strange that, but I realized in the last couple of years, it's like, okay, if they were hospital people, it would be malpractice to a weight of 30 hours to give a patient the drug that they knew would take care of me, because that didn't make sense. Second, when I felt it, I didn't feel the warmth in the IV. I felt it directly in my heart. I didn't feel anything in my arm. And third, I'd never sell those guys before or since. So, so, I don't know what to make, so I'm just stating what, what I saw and I'm here because my heart flipped from 190 beats a minute for 30 hours to instantly, like instantly a feeling of warmth and it was done. What did you say to the doctor when he came in and said, what happened? I was so exhausted that I, I, I, I couldn't even grok what, what was going on. All I knew was I was so glad I wasn't dead and so glad that I, my heart wasn't beating like that and I just needed some rest so, and then I, I could not wrap my head around it. I tried to think out of the box but that was so far out of the box that I just let it go for three or four years. I didn't even think about it. I didn't. I believe you. Yeah. Um, here's where I think your philosophy comes in and it's, it's from this story to just for laughs gags. Oh, yes. That's your, that's your show that you love, right? I, yes. How do you know that? I love just for laughs gags. One of my favorites, yeah. Why? What happens on that show? Well, people are surprised, so the, you know, they, they're set up to expect one thing and they might get all upset. And then in many cases, they end up laughing. So they, they get into the situation, they're upset, they're all tense. And then they realized, oh, wait, wait, wait, wait, ah, I didn't need to be upset. That was just a gag, the whole, the whole time. And it really does, just for laughs gags, sort of as a, for me, a, a good example of what I think the whole thing is. Again, this is the whole point is to relax and enjoy the game. And, and in fact, the more that you can do that, I, I actually think about this in terms of my research progress, the more that I can relax and enjoy and be open. Let go of everything I think I know. Don't be any like egoic attachment to what I think I know. You've got to, the ego is the biggest, biggest impediment to growth and, and discovery. So let go of the ego, let go of attachment, let go of all that stuff and be opened like a little child. Like Jesus said, unless you become like a little child, you cannot enter the kingdom of heaven. And I really think that that's, that's right. You have to just be open to say, I don't know anything as much as I've learned, I know 0% let me know more and, and play the game. I think that's what it's about. I think so too. And don't take it too seriously. And when it's over, you might be scared, but then when it's finally over, you can just have a big laugh. That's right. And even being scared was part of the whole deal. Yes. Then you go, you can go back and laugh at that even being scared. But you go through, for some reason, we set it up so we want to go through that scared part too. We did. That's right. It's interesting. I was scared. I'm no hero. I was scared to death, and I was really sad to say goodbye. Yeah. So I think for the one to really know itself, it has to, the source, it has to take an infinite number of perspectives. And to take a perspective doesn't mean just sort of casually. It jumps in with both feet all in on that perspective to really believe it's that. And it really then lives that out and then slowly realizes that was just a perspective and it wakes up from it. But that's how it really learns that that perspective is rich as it was. I infinitely transcend it. And that's how, that's the best story I can tell right now about how the one is, how it knows itself. I think it does this. I think it's perfect. So now, given everything that you've done, everything that you know, when you see a monarch butterflies, it's more beautiful or less? It's very beautiful. There's a preschool just down the street for me that has a big picture of a child on a poster looking at a monarch butterfly. And every time I go by, I go, that was me at five years old. Don't lose the love of surprise and the joy of discovery of all the beautiful stuff that's around you right now that you're just not seeing. So I'd love to see that picture of that. It's a boy looking at a butterfly and for you, it's there for, it's there for me, reminding me, relaxed on, don't get uptight. It's just a game. That's the message Don Hoffman and Trace Institute. Everything will be linked below. He's got to catch a flight. I hope you'll come back. You're a treasure. I'd love to. Thank you. And thank you so much. This has been a great pleasure, AJ. Thanks, Don. Bye, everybody. That was Donald Hoffman. He ended on a butterfly. And let me start with the other book, The Beer Bottle Beetle is Real. And D'Amologist Darrell Gwynne and David Rents watched males in the outback, mating with stubbies until they died. And their 1983 paper won a Nobel Prize. Australia changed the bottle for the beetle. Evolution built them to like dimples, not truth. That's Don's whole argument and one insect, and I love it. Now the new math. Don says proofs of special and general relativity built from consciousness alone are sitting on his desk. Nothing is published, so there's nothing to check. He said it himself. It's not real until it's published. Like a way. And the hospital. Don's heart raised out of control for 30 hours. He texted his wife goodbye and laid back to die. Two strangers stood by the bed at 3 in the morning. Neither wore hospital scrubs. One smiled and nodded and his heart flipped back to normal. He never told that story publicly before I had never heard it. 40 years of math to prove reality is a headset. And the takeaway he cares about most is a preschool poster of a kid staring at a butterfly. That part I can verify. I watched a minute. Don's book is the case against reality. The new work is at traceinstitute.org and everything I mentioned is linked below. Until next time, be safe, be kind, and note that you are appreciated. Oh, oh, oh, oh, yeah, I believe that it will be a scenario that we want. A secret code inside the Bible said. I love my UFOs and piranhas, my boss, as well as mirrors it. So I'm saying it like I should. But then another conspiracy theory becomes the truth with my friends. And it never ends. I know it never ends. I fear the crap got out and got stuck inside my home. With MK Ultra, I'll be in only two hours. Do you stand, look you've red-faced the moon landing alone? On a film set, I wore the shadow people there. The raspberry leaves just fought the smiling man. And I'm told, and his name was cold. I can't believe I can't swim with the fidget. Had no fish on Thursday night, we'd stay J-2. And when I have my feet off to the night, all I ever wanted was to just hear the truth. So the waffles on your feet all through the night. The mouth man's sight and van, the solar storm still come to a God, the secret city underground. Mysterious numbers, dations, planets are phoned to project stockade, and what the dark world's just found. In a simulation, don't you worry, though, the black nights at a light in tow to me so I can't believe. I'm dancing with the fidget. And when I have my feet off to the night, all I ever wanted was to just hear the truth, so the waffles on your feet all through the night. All I ever wanted was to just hear the truth, so the waffles on your feet all through the night. No tightness, no stickiness, no residue, just plump, dewy, hydrated skin that still feels like your skin. Try new, grippy setting mist from Mavily New York. Baby, it's me, Blaine! It's a shannon-maldonado. It's a shannon-maldonado.