The Why Files: Operation Podcast - The Basement: Donald Hoffman | Consciousness, Math, and the Case for Letting Go

Episode Date: September 14, 2026

-One thing to pack, five ways to power! Get 10% Off @Ridge with code BASEMENT at https://www.Ridge.com/BASEMENT #Ridgepod -Discover how to move your IRA or 401k into physical gold and silver — with no taxes or penalties. Get your free portfolio review and free gold & silver guide from GoldenCrest Metals: visit https://GoldenCrestMetals.com/thewhyfiles or call [phone] now. -For a limited time, get 50% off for life, free shipping, and 3 free gifts at https://mengotomars.com. #ad Donald Hoffman has spent forty years asking one question: are we just machines? He walked away from a defense-industry career to answer it, and the math he found says space and time aren't real — and that what you're looking at right now is one of the cheapest headsets available. We get into the beetles, the beer bottles, the nine proofs he's chasing, and the one story he's never told publicly. Buckle up. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Today I'm talking with Donald Hoffman. Don is a cognitive scientist who spent decades at the heart of mainstream science. He wrote fighter jet software for huge aircraft in pure machine code. He trained at MIT. He sat for years in a private consciousness club that Francis Crick co-founded. Francis Crick, the guy who discovered the building blocks of 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 a beer bottle and why that matters for evolution. A beetle dated a beer bottle, huh? Eh, I've had worse. Why Don says space and time our 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 on 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. Professor, thanks for doing this. I appreciate you. Thanks a lot, AJ. First thing that kind of was I found interesting about your background is you grew up in San Antonio,

spent most of your life in Southern California. Where did you start ice skating? How did 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 capades chalet, ice capades show or something like that. And 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. didn't like it at first because you know 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 sort of 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. Really?

And so forth. So I actually did a double jump and one and a half turn jump and so forth. So it was a blast and it's a very, very good exercise. And even now I'll go back and ice skate. Really? I'm not doing double jumps,

but you know, I'm 70s, so it's 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 capades, not hockey. That's fine. Right.

Yeah, 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, you know, 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-physicalist stuff. So he was all on board with that. But when it wasn't just directly into Fundamentalist Christian, 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, was you were getting one story on Sunday and a different one on Monday? Does this kind of reconcile it? That's exactly right. The story I got a pretty severe story from the Christian view. The Earth is only 4,000 years old.

Oh, he was that? Oh, no, he was that. Okay. 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 it 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 it 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 and all the others weren't the truth and so forth so so yeah it was I got one version on Sunday but then I also had you know the Monday version which was there was all the science and I would

like to that says it were billions of years old and we evolved and he didn't believe in evolution at all. That was an affamount 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 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, it's a master's degree in chemistry, and working at various companies in high levels for using chemistry. So I had to, on my own, then decide between the spirit, 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 Catholics don't go to heaven then? Well, a lot of other people, even in other Christian denominations, might not be going to heaven. Right. Okay. So this was, it was pretty austere, right? Yeah. My way or the highway. And it was, and it was, bad thing about it was, but God was not a really, they would talk about God being loved, but, but in fact, you were trained to be afraid. You had to be really, really afraid and cry every Sunday and repent. And, you know, it was quite a scene. So it was real psychological control. And it took, 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 now.

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set. After your purchase, tell me we 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. Are we just machines? And to do that, I would have to understand what machines can do. And is there anything that humans can do that machines can't? That was sort of the idea. So I ended up, trying to answer the question I went to MIT and I was in the artificial intelligence lab so that's going after what machines can do so I started in 1979 and had the good fortune of actually interacting with Marvin Minsky took a class with Marva Minsky the guy that one of the guys that founded the field yeah John McCarthy the two of them founded the field

so I got to argue with him at his home we had his 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 and 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 that was 79 to 83

and I kept working on the mathematical models of vision and it was around in 1986 or 1987 working now at University of California at Irvine with Bruce Bennett and Chaiton Prakash to extremely talented mathematicians. 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. Well, 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. 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 Hugh. And by the way, Hughes is a great place. Did you work out of El Segundo? That's right. Yeah, I worked out of 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 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 wrote... Wow, you didn't even have Fortran yet? Nothing like that?

Well, I had studied Fortran, of course. I mean, I knew Fortran from... Actually, I did that when I was a sophomore, I think. So I knew how to program in Fortran. But when I got to Hughes, they said, you know, we can't do Fortran on these. It's not that. I mean, these are special purpose processors that are interrupt-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 were brand new. It was called the Anuk-30-U-Y-K-30. An-Y-K-30. So you can look that up. That's what I programmed. and so I knew all the ones and zeros. If I wanted to multiply by two,

I didn't multiply by two, I shifted. Things like that. If you wanted to divide by four, you shift to the right. Yeah, and stuff like that. So you found all the tricks. We did an entire complete flight simulator in that ANYOC 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. No. We did an entire flight simulator bit by bit. We knew all the bits. And it was delivered to write Patterson Air Force Base in 1970. To write Pat, wow.

So to write 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 do this kind of stuff. Yeah, that's right. It was cutting edge for these new. electronic displays for Frederick. So I was a cold warrior as 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 79. And Hughes paid the whole way, expecting me to come back and direct 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 director,

there would be directives from above, and I wouldn't be free to really explore what I wanted to do. And so I decided I wanted complete autonomy to explore whatever I wanted to do, not just something that's going to lead to a product. And it's not right or wrong. 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 at Irvine. Of course. That 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 would have made at Hughes. But it was the 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. Well, let me go back to young, young Don for a minute. Yes.

Because maybe this is the seed of getting interested in vision, but the story, you're 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. Is the butterflies?

The butterflies. So I was walking to kindergarten. And I 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'm saying I was intellectually saying that way.

It was just my emotional childish reaction was, this is a whole thing to explore. So it's not like I was intellectualizing. It's just obvious that you have to do this. But your decision to leave Hughes is an analog of that. Yeah. It was really, life is about exploring, going where your heart wants you to, and have to, having fun. So it's really a play. It's really, and 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

Lila that it's a game. And I think that that's a really deep insight that the, you know, in some sense, the greatest insights and even technological insights come when you, when you just play. And somehow I think reality rewards that. It's sort of like only when you let go of your uptightness, do you start to relax into new dimensions of reality that you can explore? So for me, it's been a bit of a journey because that five-year-old butterfly chaser

got strangled. Yes. I got in trouble the kindergarten teacher instead of rewarding that let my parents know that I was late and I was

punished did you tell your teacher what happened 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 so you didn't mean any harm I didn't mean any harm but that I was only five

but it was just obvious that this was was a joyful thing that 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 those are the formative years. So unforming the formative takes a little. 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 who's buying. Central banks just bought a record 289 tons of gold last quarter.

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know right now it's trivial everything I've learned is zero percent drop it to the moment you get something deeper and so that's I'm moving back to that, but the interesting thing is that the emotional programming goes very, very deep. So I see, in meditation, I just see myself having to face that old programming, of 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 that 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. That old person is dying. It's really a death of that old.

It is. 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, but 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 in to the unknown. And so that's fun, that's fun for me. I think, 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 been, they've had 10 rebuttals and you've said, maybe they're right. I mean, it's just, 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, you know, 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 as rigorous as you possibly can. Get all the evidence you can. Give as strong a presentation of your idea as 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 ad hominem. It's never ad homineming in my 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 are just theories. It's something I wanted to talk to you about is David Marr. Yes, yes. I guess he basically launched computational neuroscience,

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. Yeah. 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 to 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 a 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 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 and found out he was in what was then called

the psychology department at MIT. Right, they didn't have anything else. I didn't even think of psychology and MIT. I'm thinking engineering and math and so forth. But it's now called the Brain and Cognoscience 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. I brought just a light jacket. A light jacket. I learned one trial learning. But David, so they accepted me.

So David Marr... 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 and these names? Well, it's a who's who. I took a class with Noam Chomsky Jerry Fodor was there Thomas Coon was in the class

I sat in in class given by Thomas Coon but there's this one class where Jerry Fodor and Noam Chomsky were the instructors and Thomas Coon was in it and the graduate students ended up being a who's who in the field it ended up like 50 or 60 graduate students there it was truly a stunning situation

Wally Nata I took a class with Wally Nata I mean it was what an experience i i had no idea how lucky i was you didn't know at the time no i i i all i knew was david mar was there okay and and um whitman richards was also my co-advisor um they 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 um he had leukemia yes and then whitman richard was an absolute gem

He encouraged me to think out of the box. He treated me as an equal, and we bounced 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, Bertolt Horn and Eric Grimson and Ellen Hildreth and many, many more John hollerback. So I got to take a class with Bertolt 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. Oh, that's heartbreaking. He and you know, at one point there was a time when one of the graduate students, I won't mention any name, but he, I knew him not well, but I certainly knew him. He defended his Ph.D. and then committed suicide the very next day. And so that was, it was a real shock to all of us 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 Marcell and he ushered me into his office and waved me in and said he knew about

of course this guy that had just committed suicide the day before and he 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 and he was only

he died when he was 35 it's tragic I mean the guy was a complete complete genius. He was? When I, 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 Ph.D. was a model of the cerebellum. And, but he knew the AI. And he was, he commanded the room. Everybody just looked up to David. So I was very, very, 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. the 30 years of work? Oh, can you imagine? Oh, yeah, no, no, it was, so it really makes me,

I feel very, very lucky to have, 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 would, UCLA is a great school. And nothing wrong with UCLA, but, but that was, MIT at that point was unique in the world. That AI really took off there. So, and so you're learning how to argue, Tell me about the Helmholtz Club. Well, so David died. And I graduated a year or a year and a half later, I guess, maybe two years later. And that's when I 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 DNA. Everybody's heard of him. He was at UC San Diego, well, at the Salk 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 Salk 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 was 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. Had 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. Yeah, 1989 was, is it from Bit Paper? Right.

Right. He may have talked a little bit about observers and the fundamental nature of observers before that paper, but that 89 paper is 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 like USC and UCLA. There are universities south of it, like UC San Diego and the Salk 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.

And so they met actually literally a five-minute walk from my house because I lived on campus at UC Irvine. You could walk to the club? I could walk to the club. So everybody was had to drive. So it was a secret club, not for any nefarious reasons, but simply because for, 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. 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 were maybe 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'd have lunch with us. We'd then grill them all afternoon. It was no holds barred. They would present our stuff, and they couldn't get through their talks. We would just go at it. What was it like when he disagreed? Agreed. Well, Francis was a gentleman all the time. He was absolutely a gentleman. I never saw him

impolite. But what I did see was he would never counten as fools and he would never, he wanted answers. Life is short. He was an older man at the time. Right. I don't have much time. Let's get to it. That's right. And the goal was consciousness. He had demystified life with DNA and he wanted to demystify consciousness. That was a clear goal of the Helmold'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 was on a mission. He was polite. He was the gentleman, but he was not going to have anybody get in 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 the best and brightest and, and really, and really grilled them 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 would be, you know, maybe a dozen of us, 15 of us in the room.

All, I mean, to be a fly on that wall, yeah, sharp. It was unbelievable the conversations that went on there. 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's bringing in people from all over the place trying to go after it. So, and I remember in 1992 he then at one of the meetings he told me about his book. He was writing the astonishing hypothesis, so I got to hear him talk about that and we talked

about that book. So that's when he sort of 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

and 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 wrap your mind around that then what is consciousness creating that that's right and and there's good reason to go this direction because the physicalist approach since Galileo, at least, had done quite well. It was mathematics and a physicalist 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 no beef for a scientist to go after. 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, A, C, G, and T. We got the secret to life, the story. I'm not saying this is right. I'm just saying this was the story. We got the secret of life, A, C, G, 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 got probably some kind of nervous system process, a neural process. At some level, 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. Penn Rosenhammeroff are involved. Penn Rose and Hemaroff. 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 experience, 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 scientists.

Suppose I went to a bunch of physicists and said, I've got a new theory of particle physics. Imagine? They said, oh, really? Really? They'd smile. And a natural question would be, so, Don, 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'll be kicked out of the, they might pat me on the back, say, let's have a beer, and then go your way, man. You know, they might be kind to me, but they're not going to take me seriously. And that's where we are with neuroscience

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After you purchased, they're going to ask you where you heard about them. Please support the show and tell them we sent you. And one person who I is a good friend of mine and who I deeply respect, so I'm not going to put the name, said, well, we basically said we might have one. there is space and integrated information theory might have a theory of space. Now, first, I felt that that made the point. There's trillions of conscious experiences and we might have one. So that still makes the point.

But that one, the theory that he was pointing to is integrated information theory. And, you know, Tannone and Koch. And that theory makes very, very clear that they're saying that it's certain kinds of causal structures that give rise to specific conscious experiences. And the way to write down rigorously what the causal structure is, in any case, is to write down a Markov matrix. That's a matrix. You could say a square matrix.

It has n columns and n rows, and it basically has a probability measure in each row. That's a technical thing. And so that's the way to do the structure. Later we'll do the traffic light if you don't mind. Sure, yeah, we can do that. That's right. A lot of fun. So they say for every experience, 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 Tannone and Co 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 100 rows? Okay. And it's got 100 columns. That means you have 10,000 numbers.

what are those numbers and why? 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 they're 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 getting a lot of good information about neuroscience and the structure of neuroscience and so forth. So it's not like 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 better that all these scientists disagree because truth is not a truth until it's known, right?

That's really true. So this gives us real acid test. 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 just show that that won't. work. But then also they're going to be my harshest critics, which is what we need. I mean, this is not about, you know, patting people on the back and say, oh, they're there, there, there. No, no, this is hard-nosed 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 physicalists are going to come after me, and that's as it should be. of course we'll go out and have a beer afterwards. Sure. It's nothing personal. 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, probably most of the audience knows you from the TED Talk, which was titled something like Don Hoffman proves there's a simulation. That's not exactly right

because simulation is still physicalism through 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 has coded us up. 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 there's two things that I disagree with on Bostrum. First, I like the idea of a simulation in general, right? You do.

The aspect that we're not seeing reality as it is, 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 was 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 either the computational aspect of it or a physical or something about the physical or a computer. But since it's a simulation, it's really only computational. Right, it's not really consciousness, 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. This is one of those theories that, you know, computational theories for building consciousness, have yet to explain a single conscious experience. And I think it's principled.

The failure, again, is principled. So I think that Bostrum is wrong to say that the bottom level is a spacetime 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 Graziano would say, oh, well, there are no conscious experiences.

There's only the illusion of conscious experiences. Okay. That's unfalsifiable. 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 real conscious experiences. I'm happy to go with that game.

Sure. I mean, that's what we always do in science. We make hypothesis. But if you're going to play that game, then to do the scientific thing, you know, oh, 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. It has to be hard to know. As you can see, again, it's not at hominum.

I'm the first to say, Graziano is a brilliant guy. All these people are brilliant. But, you know, this just won't work. But I love the disagreement. That's the only way forward. You and Chetan wrote your road observer mechanics in 89. Yes.

So the two of you made a bet pretty early, and you were 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, those three of us, actually Bruce Bennett, who was a genius mathematician. Is he gone? He died in early 2000s.

And Chaitaun Prakash, who is also a genius mathematician, and is still alive, and we still collaborate. And he's a good friend. We really worked hard in the 80s. It 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 is it from bit paper. So if you look at his paper, one of the citations is to observer mechanics.

So he'd read our book when he published his paper on It From Bit. That's a fun phone call to get. Yeah, it really is. So he was aware that we had, you know, 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 it. When I came from MIT to UCI, I was on the

fast track. I mean, I was getting grants left and right. Sure you are. I was 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 at one point where the mathematics all of a sudden just slapped me in the face. And I realized that we're creating all this stuff, like it's a V-E-W-E-W-E-E. our headset. Well, before we do that, let's take a break and we'll come back and we'll get into the

math. Okay. Okay. Okay. Okay. Fair fact. Let's assume everyone's seen your 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. 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, and so 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 Then 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, our beetles, so there are these beetles in the outback of Western Australia,

the jewel beetle is called, and they're dimpled, glossy and brown. The males fly, and the females are flightless. And the males will go flying around, look, looking for a female, and if he finds one that looks right, he'll alight and mate. 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 of brown, they tossed them out into the outback, and the jewel beetle males would fly down onto these stubbies and fly, and fly out.

all over them, trying to mate. Now, it's remarkable. It's not like 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 persist in trying to mate. Until they die. Yeah, that's right. So they do not give up. And this could make the species go extinct. 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 that's as much insight as they have into females. And some females might tend to agree. Males don't have much insight into it. And so 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 man behind the curtain, right? 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 at, look online, you know, do an AI on supernormal stimuli.

Okay. Supernormal stimuli, and you will find all sorts of things that are fun about how organisms can be tricked by bias. And we use that all the time in designing, for example, makeup. is supernormal stimuli. When you put on lipstick, the red of your lips is super normal in nature, no woman would ever, 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, that algorithm and make you more, of course, at some point, then you go into, clown material, right?

Right. So you can go to, so you can push supernormal to a point, and then you go clown, and then 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 involved to show the truth, their 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.

Mar and Pogio looked at the fly visual system and so Mar and Pogio 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 about that?

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's 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 it mathematical, with evolutionary game theory. So we can now actually take Darwin's ideas and state them with mathematical precision and start to prove theorems and look at the details of his theory.

That was in the 70s that evolutionary game theory came out. And in game theory, there are things called payoffs, right? If you're playing a game, 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 knee 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 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 have. So topologies, metrics, partial orders, all sorts of technical things that you could 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. 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 to the probability is zero. Zero percent of the payoff functions hold information about the structure of the world. Fit wins.

So fitness loses. Fitness loses. Well, 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 1. What did they get wrong 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? Okay. So, 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, oh, 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, 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 it is, whatever structure you might.

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 a homomorphism is. That's right. Projection, okay.

Yeah, the map is a faithful representation of the structure of the subway system. Exactly. That's a great. That's a great way of talking about homomorphism. I'll use that in the future. I've got to catch them up. Perfect. Because 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. Payoff, there's 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 shaped to see the truth? Zero percent. It's that simple. It's just like give the whole argument in one 30 second clip.

The set of payoff functions are big. The ones that are homomorphisms, 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 people will say, look, Don, this is all high flute and math. It sounds really great. But here's the fact.

You 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. So you've used your theory to refute the foundations of your theory. So you should just go learn some logic, Don. This is stupid. I've seen this. Oh, yeah. 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. I also get that all the time in comments on YouTube videos and so forth. Oh, don't read that. Stick with the journals. Absolutely, absolutely. So the reply is very, very straightforward.

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Learn more at Bloomberg.com. Every scientific theory starts with assumptions. No scientific theory is proving its assumptions. It's assuming its assumptions. Those are the miracles of the theory. The theory is saying if you grant me those assumptions, please, then I can explain all this other wonderful stuff. And if it's a good theory, it will.

If it's a really good theory, it will give you the mathematical tools to really explore the scope of that theory. But it's going to be a finite scope because it's not a theory of everything because it doesn't explain its own assumptions. So no scientific theory is a theory of everything because no scientific theory explains its own assumptions. There can never be a theory of everything. Just that simple. The argument is drop-dead simple. Every theory has assumptions and they don't explain. So a good theory, though, will give you the mathematical tools to explore its limited scope. It's not arbitrary scope.

It's a limited scope. But a great theory will give you the tools to actually understand the limitations of the assumption themselves. So a great theory will actually tell you that the assumptions themselves are not the final word, which we knew altogether. I mean, we knew that before, that the assumptions cannot be the assumptions. 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 plank 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 plank 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 they should go and learn some like. No one says this is actually viewed as a breakthrough. This science

is so rigorous and 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 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, there's infinite job security in 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 is 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 knows. And yet, that's 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 opportunities in 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. 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 bring to this thing? 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 realize they have no idea. But, I mean, 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 stuff, 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 a 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. 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 is fundamental has been around for thousands of years.

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 in retrospect, the model is simple.

But of course, even in my case, I just discovered a big step in it just five months ago. So I've been at this for 40 years. 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. It made a lot of sense. Oh, great, great, great.

And the way the universe ticks a different rate, ticks at a certain rate, all that stuff. It's very interesting. Yes. Well, so, yeah, so I'll just say that what I had to do and what my team had to do, so Chaitan 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 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 a conscious observer, what's the minimal, minimal thing that you would want? Well, observers have certain experiences that they can have. Maybe I can see red, green, or blue, or something like that.

So I'm going to list the experiences that this observer can have. And the other thing that seems necessary is 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. There are experiences and they change. And what's the most general mathematical object that you can use to do that? well you list your experiences like a column

and then for each a row next to each experience to say what's the probability if I'm having this experience I'll go to that experience you just list all the transition probabilities that's it

that's called a Markov matrix that little thing I just talked about so simple is 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, probability that you're going to see red next is zero, but you're, the next, and probably you can see green next is one. Right. Probably you're going to see yellow next to zero. Right. So this is while we're building the matrix. So that's right. So the first row is 010. 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, the probability 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 a cyclic matrix. But most marker matrices aren't cyclical.

They're more complicated than that, but that gives the idea. But now just imagine we're just going to make this following statement. All possible observers are represented by all possible markup matrices. So these markup 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 that's an infinite space. So that's what we do. And but so each matrix now think of it as is an observer window.

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. If you're just sitting there, you're looking through 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, 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 just talk about how I could move around on those observations. 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 at the world, at the world through this window. Now I want to look at the window, through this window and so forth. That's what I call that a policy. And what is that?

That's another mark of matrix. Because it says, here's the probability. 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 collection of Markov matrices. But 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 I want to change to this policy. 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 surgotic, 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 the 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. And so we can,

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 basically saying something like this.

I don't want to put words in his mouth, but I suspect that he might like this approach. 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 pre-established harmony. And he was thinking about God, having set up this pre-established harmony, so that they are coordinated somehow, that they're not just random observers,

you know, just 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. Yep. Did more alchemy than he did physics? More alchemy, that's right.

And so I think that he would have liked to have a situation where he could put, you know, consciousness and observers fundamental, but the math just wasn't there. Right. 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, you know, F equals G, M1, M2 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 Leibniz 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 pre-established harmony that Leibniz 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 seven of the colors. So I can't see those seven colors. So I'm still trying to look through that window,

but I can only see three of the colors. Well, now I'm going to get effectively a 3x3 matrix on those colors. Right. that's induced by the big 10 by 10. So there's all sorts of hidden stuff going on in those other seven colors that I can't see. But they're there. But they're there. They're hidden.

I can't see them. Right. But they do influence what I'm seeing in the three by three. So that's a good way of explaining this. Yeah. Yeah. And so that thing is called the trace matrix. And for those who are more mathematically sophisticated, I do 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, 2, 3, 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 it's called the sure complement, S-C-H-U-R complement. So you take a big matrix and you induce a matrix on a subset that you can see. Right, like a trace element, a small part of it. That's right. So this small part is in effect reflecting the hole, but just through this smaller window.

It's almost like the smaller one is observing the hole 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, 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 years ago was that that gives us

the trace relationship is a partial order on all markup chains. It gives you a logic. For those who know, a little bit of mathematics is not Boolean. So Boolean logics are the ones that we are most comfortable with. You can take and ores

and compliments and so forth. So this... But 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. That makes sense.

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 sublogics. It's really, really pretty. It's elegant. It's unbelievable. So the local Boolean is the base of all of it. That's right. You have an infinite number of these local bullions, 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 Chaiton Precah, and I said to him, Cheaton, 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, Don, 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 uh transit so the trace a implies b that's right so the trace of a trace is a trace so i have a big so i have a 10 by 10 and i trace it under five and then i trace the five down to three i get the same answer as like if like went from 10 right straight to three what did he say when he called you from heathrown after he proved it um well i think it was fairly a matter of fact yeah it's it's true and i was i was i i believed it was true i i i i believed it was true i I believe it's true. But when Chaiton says it's true, then I know it's true because Chaiton 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. Because that's a whole set of Markov colonels. So there's a trace logic on them. And then there's a trace logic on the meta-polices. and the meta-metapoluses and so.

So you get a recursion of these trace logics all the way out to infinity. And I want to propose that this is the pre-established harmony that Labnis was looking for. Wow. So there's all these observers and they're tied together by this beautiful recursive mathematical logic. So we're still trying to understand this logic.

This is, there's a lot of mathematics to be done on this. How is the establishment responding to this? Well, it's, the theorem is true. So, yeah. So, so there's no problem with, with, with the theorem. But if Cheaton proved this, that means others can. That's right. But in fact, for mathematician, this is falling off a log.

Right. To prove that theorem is, I mean, Chaiton was, fluted. Heathrow while he was waiting in the in you know he had Heathrow for something he proved it so it's the kind of thing where a brilliant mathematician like Chaiton 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 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, and here's the kind of thing that gets publicly stated about this. So there will be, there is, I don't know if I'll mention the person's name, but very, very prominent person with YouTube said about this, that this is complete nonsense. Of course, Markov trains are fine, but to use them for consciousness, this person said, you see, Markov chains are used for standard stuff like

predicting the weather, predicting stock markets and so forth. Nuclear fission. Nuclear fission. Google page rank. That's right. 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, who 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.

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 now. 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 could 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. It's silly. It's just plain silly because you could apply it to any other application. The math does not tell you any applications.

It said, this is a structure. When you use it in science, what you do is say, I think that this. 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. Now, I think what's really going on is the argument that they're 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 a 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, 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 things, 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 mean, I use red, green, and blue because it's very, very simple, but it could be, you know, a particular three-dimensional shape, a 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 mark-off change in what I call the recursive trace logic, the recursion of Markov chains, policies,

and meta policies 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, and the best way to do that is model it with Markov's change. 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 of 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?

it can change, but the policies and meta policies 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, you're not, these are just mark-up chains, you're not showing any deliberation, you're not showing any irrational reasoning or reasoning here, or, you know,

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, you're going to have, when you write it down, you'll get a markup change. It says, what's the probability, given that I'm in this world, that I'll go and do this thing

or go to that world. So there are just different ways of describing the same thing. So I like the mark of Shane 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. you about the physicalists, right? I've said, look, they start off with space and time and physical objects is 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've got this nice mathematics and you're claiming it's consciousness. Great. Where then does 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 of 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.

Nipha and Chaton, tentative proofs of getting special relativity and general relativity. It looks very, very plausible to me. And I'm working on the Bourne rule. This family is on the brink of civil war on September 18. Mobland. The hit original series is back on Paramount Plus. We are the Hurricanes. Don't know the ant?

And Google us. From the underworld of Guy Ritchie. Do you want to step up the ladder? I won't calm up dead. Starring Tom Hardy, Pierce Brosnan, and Helen Mirren. Do I have to do everything myself? You want to want! I'll give you a...

Mobland. New season hits September 18th on Paramount Plus. 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, 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. Does Minkowski space time factor into this? That is where Minkowski space time comes from. This is where when you don't have gravity involved. When you don't have gravity. Yeah, when you don't have gravity. So this is just Minkowski space. So Einstein did this in 1905.

It wasn't until 1915 that he came up with curved space time. It took him 10 years to really master the mathematics for that. Oh, is that all? Well, yeah. Irremarkable. 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 of 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. It'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's going.

But only a state change. Only for each state change, right? Every time a color changes from red to green, or red to red, right? So you could have red change to red. Sure. So now, suppose we go back to the three-by-three subwindow. Yes. Notice that, say, it only has red, green, and blue, not the other seven colors.

So it is only going to up its counter when red, green, or blue, happen. but it won't catch yellow, purple, pink, or the others. So notice, its 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 3 by 3 is only counting 3 of those, so it's only getting 30% roughly of the counts. Well, let's help people understand. Let's have the colors changing. Give me colored glasses.

And let's click our counters together. Right. So suppose I have, let's keep. but 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 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, 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 your counter, you're seeing less. My counter is slower. That's right. So the reason I think you're, so the reason I think A.J.'s counter is going slow.

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. And so your counter is going faster than from your point of view. But the same way is, that's why it's, it's symmetric. From AJ's point of view, my counter is going too 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? time? Now that would be... What's that universe frame rate? Well, 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. So 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 alien to the recursive trace logic. It only has counters.

It doesn't have the notion of time. What I have to do is show that I can use the recursive trace logic. In fact, I can use 0% of 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 like a fundamental clicker in the recursive trace logic, but it won't have the notion of seconds tied to it at all. I guess it doesn't need it then, as long as it's there.

Well, and as long as it's there, 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. 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? And also space time falls apart at 10 to the minus 33. We might think, that's pretty small. No, what about 10 to the minus 33 trillion?

Why should space time fall apart at 10 to the minus 33? That's a fairly shallow data structure. So 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 mark-of 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 this.

A VR headset. Because you could still make this work. 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 out of it.

So that's what I'm building a headset, I'm saying, I'm starting with this universal consciousness, the recursive trace logic, mathematically described with the pre-established harmony that Leibniz wanted. So that's what Leibniz 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 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 one of the most trivial

and simple spacetime headsets that's available. We have the training wheels version, really dumbed down. So our view that we're like at the top of the food chain and we're at the top of intelligence, my view is, No, 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, right? So I've got a proof that I like.

Chaiton likes it? Chaiton's looking at it, and NIFA are looking. 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 very basic, that implies that there's something more advanced. The mathematics makes it very, very clear that there's an infinite number of far more interesting headsets.

Infinite. Infinite number. Infinite number. There's unbounded. So ours is one of the most trivial. Ours, you could 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 headset is 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 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 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 two, four. In terms of the number of dimensions, you can three, two, one. So 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 an infinite number of different kinds of headsets that you can... 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. You mean our species? Well, our species is a headset representation of a consciousness that is actually able to do all of this stuff. And so part of our joy here is to enjoy this headset to wake up and realize it's just a headset and to realize the Lila thing. This is a game.

We let ourselves get long. 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 as as 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 right there's infinite yeah yeah that's the idea that's the lea 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 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... Well, there's one way of thinking about it. Just one simple way is 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, that's one direction. And then you can go of the notion of dimension altogether and just try different topologies and so forth. So there's as 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 infinities. So I study mathematics because it really helps push me out of my life. little boxes out of my little, you know, dead ends, thought dead ends. I've heard you say you

know enough math to get into trouble, not enough to get out. Who gets you out? Well, so my, my good friend, Chayton, 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 very good. He's, he's brilliant. I've been very, very lucky to work with him. And Bruce Bennett worked with me until the early 2000s. And Bruce was brilliant. I'm now working with Niffa, Hermanson, who's, he's an expert in Markov Chains in fact. So this is his area. And at the Trace Institute, we're looking to get some more mathematicians now to work with us on this. So more mathematicians the better. You're building up a nice roster over there. What's a Tuesday like at the Trace Institute?

Well, right now it's distributed, so we meet by Zoom and so forth because NIFA is in New Zealand and Chaitan is in, you know, he's about an hour and a half away from me. So it's just the normal thing. So our meetings are, you know, on a Tuesday would be, so Robert Prentner is in Shanghai. He was a former postdoc of mine. He's now professor at Shanghai. He's working with us. He's going to be the leader of the Trace Institute.

He's a younger guy. I'm 70. He's in his 40, so 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, I've forgotten the exact mission statement. I just mean generally what you guys try to accomplish. Yeah, 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 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 Bourne rule. One of them is we can get the Big Bang. Another one is that we can get quantum non-locality. You can get non-locality out of this? Absolutely. We can get non-locality out of this thing.

So we can get everything of quantum mechanics, if we can't then we're wrong, by the way. So I'm saying these conjectures are the things that anybody would require me to do. Didn't Pristin give you a challenge? Didn't you ask you to derive the Schrodinger equation using this? Well, yeah, so we have... That would be cool to solve that.

Exactly. And that's one of the conjectors that we can get all of quantum field theory. So not just shortening our equation, but get quantum field theory completely out of this. Nobel is probably listening. if you can get that working? I mean, is this something that practically you can release?

Like, hey, gang, we solve this. Conjecture four is done. Moving on. That's right. That's our goal in the next two or three years is to get these nine conjectures proven. That's the first... Quantum field theory within three years? Yeah, that's our goal. We're trying to show. So we don't have to show that 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 other kinds of structures that are probably much more interesting than that. So that's what we're up to right now is, but we have to get this headset. The idea is that for our scientists, what's going to impress them is the mathematics and the spacetime physics that we know. So Einstein's general and special relativity, quantum field theory, the Bourne rule, Big Bang, and so forth.

If we can nail that down, and here's one just real brief reason why I'm sure we can do it. The set of the space of all Markov chains is computationally universal. Anything that can be computed by any touring 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. Aha. In what sense? I don't know.

why consciousness is fundamental is even required for this to work? I feel like this could work 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 not, 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, what we call space time, may or may not be real. But my experience right now is to look around, that's real. Einstein gives us a mathematics that we call the Spacetime Mathematics that nicely describes this. But all I know really person is I'm experiencing colors and distances and smells and so forth. And Einstein stuff is great and it works well. But I'm not sure that that's the final reality.

That might just be a description of my particular kinds of experiences. a shark or a bat that's using echolocation why should its world be anything like my world? So there are all these sensory worlds. Explain that to us using ants and hands. Ants and hands? Yeah, how

an ant has a certain world that it perceives. Right. Well, so I don't know too much about ants and I think they use chemical signals and so forth. I mean,

it was just an example that used I thought was very interesting about how from an ant's perspective you can just reach down and kill that ant anytime. Oh, right, right.

That announced. Oh, right, yes. I guess it's 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, you know, my wife probably wouldn't want to do that. She'd probably put it on a piece of paper and take it outside and try to be kind. But the ant wouldn't know in either case. Now, 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 chemical tracing and so forth. And it can do some apparently dead reckon It can wander around and then dead wreck and 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 aunt's point of view, how much would the aunt know about AJ?

Nothing. Almost nothing. And it might not even know that you're there. Right. But if it dead, maybe its representation of AJ would be as simple as my representation of an aunt. You know, it's just that simple to it. So by symmetry, I have to ask myself, so what I think of as an aunt, maybe that's just because of the 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 to see.

That's all your headset allowed you. And it also means that there could be, this is where UAP stuff comes in and so forth, that there could be other consciousnesses or observers, if 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 any time, 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, we'll actually talk about those entities with the headsets. Okay. So Andrew Gallimore was sitting right in that chair not too long ago.

Yes. You guys are working together, which I love. Your first project is literally titled, Are DMT aliens Real? Mm-hmm. Are they? Well, I think he and I both probably agree that the emphasis on Real is probably a little bit misguided.

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. The entities in higher headsets could play with us like we play with ants. And so the idea then is, does DMT just screw you up? 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 all together that's and if so could the entities that we're seeing in the DMT space be avatars. Just like when I talk with AJ, 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 to interact with your consciousness. And you see the Hoffman avatar allows you to interact with my consciousness. So 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 is gone. Gone. It's completely gone. Whereas the consciousness presumably is not gone, but Hoffman's avatar of AJ is gone, whereas

AJ is just fine. And so the question is, are the DMT entities good avatar? So it's not saying are they real, but we put real in because it's catchy. Yeah. 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 DMT entities. Could we send two people into DMT space? Is there some avatar, there's 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. I have. And it feels more real than this?

I've heard that the resolution seems higher. Everything seems, this seems like the low resolution. This seems black and white. It does. And the funny thing is that's what the recursive trace logic is telling me. It's just saying this is one of the cheaper headsets. That's right. I didn't even connect that. This is, we really, so when I say this is a cheap headset, I really mean it.

That we got, we got 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. Don, 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. I just don't need the glasses anymore. It drives my wife nuts. She's like, you can read that?

I said it's like superpowers for about a week. It's something about neuroplasticity. 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 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, a 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's not proof. I mean, a hard-nosed 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 that's going to be a lot of neuroscience, so we're going to have a neuroscience team working on this. There's 86 billion neurons, trillions of synapses. We have to understand that is just a, and this I'll be very slow here. The brain is a headset representation of how the headset is constructed. That's a big concept.

The brain, the nervous system, is 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 in 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 spacetime 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? Absolutely. You can change any rule in... 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. He 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 can do anything he wants.

And so I think the recursive trace logic, when we get these nine conjectures, and we begin 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 people see the technologies that come out of it, then it'll be game over for physicalism.

Game over for physicalism. Wow. These are big goals. Yeah. 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're already sort of right now,

looking at the neural networks and trying to construct them through all the 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 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 a compression of, 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. And it looks really complicated inside this, 86 billion neurons, trillions 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 we need 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. And that's what you experience yourself

and your own experience in DMT is that this already feels like 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 can only see the three but three, 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 7 by 7, and then you have transitions back in. So you have the exit, the external world, and the re-entrance. Wow. So that could explain everything from UIP teleportation to particles appearing out of the vacuum. That's right. This gives you... So it shows you how to exit from our spacetime headset, how you could have an entire world that's far more complicated than our headset, infinitely more complicated, and then reentrances. That's one aspect of it.

Another aspect is just the magician's trick. A 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 there. here. 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 in 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. No. Hover with no apparent propulsion, move at Mach 40 instantly, at 466, G's. Go into the water with no displacement. 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. If you're the geek that wrote the software, the wizard will be stunned by what you're doing to him. He has 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 a UIP doing Mach 40 is just hitting that clicker faster than we can perceive it. That's right. Or it could be distracting us. There's 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, 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, completely helpless.

So it's not like, there are cases where it seems like there's some kind of hostility and so forth. But if they were really hostile, we wouldn't last five seconds. So I get the feeling that there is, again, a playing aspect of this, let's explore more, let's play with these.

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 one source consciousness

playing with itself at various, level, but with recursive trace logic, we could begin to scientifically see how that 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 to some point. So that we'll need to go beyond the 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 transcends any scientific description, including mine. So what 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 bullion logic is a consistent view, but different bullion logics can contradict each other, But they're all useful perspectives on the source, which transcends all of them. It's beautiful.

If we have evolved to not be able to perceive that, is that an impediment to the research? Is there, maybe does the source just say, I'm not going to let them figure this out? Yes. So you and I are just the source looking through a particular headset. And there are certain things. We know that the game is such that there are very few of us who, I mean, the Einstein's are very few, right? Right, right. The Schrodinger's, Einstein's, and so forth are very, very few, and we're grateful for all of them.

We are. But they're trivial. The Einstein's and Schrodingers are trivial compared to what's out there to be discovered. Yes. And yet you and I are fully that source, and we, 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, 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've

learned your philosophy and it comes out of your your heart scare after COVID you know COVID you're you're running hearts gone 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 sacked my wife, and then I think I texted my daughter separately.

I just said, I don't think I'm going to make it. I love you. Goodbye. That was just that simple. Same thing to my daughter. Something like that. My heart's been beating 190 beats a minute for 30 hours. I don't think I want to make it.

I love you. Goodbye. As soon as I did that, I laid back in the bed to die. Just to wait for it to happen. You were at peace in that moment, or were you scared? I was scared. Sure. I was exhausted.

My heart was racing. So even just the racing, a hard night to beats a minute, it feels like you're scared to death because your heart is racing. So even though it's just atrial fibrobor. relation it fills to you like you're scared to death. I've only been recently starting to talk about this. At that very moment when I leaned back, it was at 3 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 the male figures looked to the other, smiled briefly lightly, and nodded his head.

And then all of a sudden, I felt an incredible warmth in my heart. And my heart started beating normally. What? 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. I haven't done it publicly before. Who do you think they were?

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 years it's like, okay, if they were hospital people, it would be malpractice to have waited 30 hours to give a patient the drug that they knew would take care of me. So that didn't make sense. Second, when I felt it, I didn't fill 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 I don't know what to make so I'm just stating 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 couldn't even grok what was going on all I knew was I was so glad I wasn't dead and so glad that my heart wasn't beating like that and I just needed some rest. And then 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. Here's where I think your philosophy comes in. And it's from this story to Just for Laughs, Gags. Oh, yes. That's your, show that you love, right? Yes, how do you know that? I love Just for Laf's Gags. It's one of my favorites. Why? What happens on that show?

Well, people are surprised. So 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 get into the situation. They're upset. They're all tense. And then they realize, oh, wait, wait, wait, wait. Ah, I didn't need to be upset.

That was just a gag the whole time. And it really does, just for laughs gags, sort of as for me, 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 in fact, the more that you can do that, 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 discovery. So let go of the ego, let go of attachment, let go of all that stuff, and be opened like a little child. And then Jesus said, unless you become like a little child, you cannot enter the kingdom of heaven. And I really think that that's right. You have to just be open to say, I don't know anything. As much as I've learned, I know zero percent. Let me know more and play the game.

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 can go back and laugh at 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 mean, there's no, 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, as rich as it was, I infinitely transcend it. And that's the best story I can tell right now

about how the one is how it knows itself and why 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 butterfly, is it 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. It's a boy looking at a butterfly. It's there for you. It's there for me reminding me, I'm relaxed on.

don't get up tight it's just a game that's the message Don Hoffman and the Trace Institute everything will be a link below he's got to catch a flight but I hope you'll come back your treasure I'd love to thank you and thank you so much this has been a great pleasure AJ thanks Don't bye everybody

that was Donald Hoffman he ended on a butterfly so let me start with the other boat the beer bottle beetle is real and demologist Darrell Gwyn 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 true. That's Don's whole argument in 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.

I can wait. And the hospital. Don's heart raced out of control for, 30 hours. He texted his wife goodbye and lay back to die. Two strangers stood by the bed at three 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 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 watch to mean it. Don's book is The Case Against

reality. The new work is at trace institute.org, and everything I mentioned is linked below. Until next time, be safe. Be kind and know that you are appreciated. It's an area 51, a secret code inside the Bible said I was. I love my UFOs and paranormal fun as well as music. So I'm singing the like I should. The conspiracy theory becomes the truth. friends and it never ends no it never ends I got stuck inside males hole with mk out of being only two of

were the shadow people the name was cold the under number stations planets are both to project stargate and with the dark watcher