Dr. Gary Nolan is an immunologist, academic inventor, and biotech entrepreneur. He s a professor at Stanford University School of Medicine, and, somewhat surprisingly, a UFO enthusiast. We talk about his career, the rise of AI, and his interest in unidentified aerial phenomena.
00:00:00.000I'm a professor in the Department of Pathology at Stanford.
00:00:03.800It's pretty obvious that you have a multitude of abilities and a stellar track record.
00:00:10.300You started to become interested in unidentified aerial phenomena.
00:00:14.860Somebody representing the CIA and an aerospace company showing up in my office at Stanford
00:00:19.660showed me their credentials and said, we need your help looking at patients who had harm done to them.
00:00:26.680And then a small subset of them said that they'd been in proximity to things that you would call a UFO.
00:00:32.880I thought it was a joke at the beginning.
00:00:35.080Let us know, if you would, what the hell you think is going on.
00:00:39.040That there's something non-human here, and it's been here for a long time.
00:00:42.240Well, I imagine it's put a bit of a bump into your life.
00:00:45.580I mean, maybe one that's mostly interesting, but still, to call it strange is to barely scrape the surface.
00:00:51.360If something is here, it's likely been here longer than humans have even been civilized.
00:00:56.680Dr. Gary Nolan is an immunologist, academic inventor, and biotech entrepreneur, serial biotech entrepreneur.
00:01:19.680He's a professor at Stanford University School of Medicine, and, somewhat surprisingly, a ufologist.
00:01:27.400We talked about his career, his research interests, the rise of AI, and his interest in unidentified aerial phenomena.
00:01:36.540So, Dr. Nolan, Gary, before we get to the heart of the matter with regards to your interest in unidentified aerial phenomena, more commonly known as UFOs,
00:01:50.160let's talk a little bit about you so that we can situate you in the minds of our readers.
00:01:55.780So, you have a remarkable research background and a technology background.
00:02:03.380Clue us in a bit and tell us who you are.
00:02:06.240So, I'm a professor in the Department of Pathology.
00:02:09.820I hold the Ratchford and Carlotta A. Harris Endowed Professorship, and the major focus of my lab's research, frankly, over the last 30 years since I've been at Stanford,
00:02:24.180has been on the immune system and creating technologies that allow us to collect more and more data about the immune cells and or cancer cells that we're interested in.
00:02:35.400And so, that's led me from the development of retroviral techniques for gene delivery and gene therapy.
00:02:42.680So, all the retroviruses and lentiviruses that are used in the world today for gene therapy were developed based on a technique that I came up with called the 293 T-cell technique.
00:02:54.980And, frankly, that's old technology to me, but it still generates a nice royalty stream.
00:03:01.660So, and then from there, it's about measuring more and more what we call parameters per cell, which are events that relate, we think, to the biology of the cells.
00:03:14.360And so, we've created and spun out, I don't know, probably at least half a dozen companies on that side of things alone.
00:03:21.560Lately, we've been moving into artificial intelligence.
00:03:25.760We've started and spun out two companies there.
00:03:28.440And now, I'm actually moving into atomic imaging because I sort of feel like that's the next level down of information that I need to get at to understand gene function.
00:03:40.020So, I've raised the money to create a whole new kind of instrument that can measure things at the atomic level.
00:03:48.520I mean, that's a lecture on microscope territory.
00:03:51.460You have a new technology that you're – I know that's an old technology now.
00:03:56.520It's a fusion of two technologies, something called atomic probe tomography and field ion microscopy.
00:04:03.180And it's a way to bring the two together because previously they couldn't sort of exist in the same machine.
00:04:10.560So, by bringing them together, we can go another order of magnitude lower.
00:04:16.120We can get down to what's called sub-angstrom.
00:04:18.280Like, the bond length between two atoms is in the sub-angstrom realm.
00:04:22.920But this technology that we've developed not only can see down at that level, but can also determine what kind of bond structure we have locally.
00:04:33.180And that has a range of applications all the way from biology through to metals, alloys, nanotechnology, et cetera.
00:04:39.680And actually, the instrument is already half-built down at a lab here in Cupertino that we've set up.
00:05:27.980So, on the medical side, tell me a little bit more about your research into viruses.
00:05:34.940So, our research into viruses was, well, first of all, the retroviruses.
00:05:40.780I got involved with HIV research back in the day.
00:05:43.940And that was mostly trying to understand what turned the virus on and off in the immune system.
00:05:50.080So, I was involved with what was called the cloning and characterization of what are called transcription factors that turned the virus on and off.
00:05:59.420And I actually cloned it in David Baltimore's lab at MIT when I was a postdoc there.
00:06:03.860David won the Nobel Prize, actually, for reverse transcriptase.
00:06:08.880So, but when I came to Stanford and using the technologies that we developed, we did everything from Ebola research to Zika to whatever the current manifestation of whatever the plague was that people were worried about.
00:06:25.820And we even actually saw the first COVID lungs from, unfortunately, deceased patients.
00:06:31.740And that's what really, that actually scared the bejesus out of me when I realized that we're dealing with something extremely serious with COVID, at least in some people.
00:06:41.820But most of my research these days is in cancer research and looking at how the immune system interfaces with the tumor and trying to learn about the signals that the usually tumor manifests to turn off the immune system.
00:07:00.900Or to disrupt the function of the immune system.
00:07:03.940And so, that required the development of new instruments to see things at a level previously people were incapable of, but then also to develop the algorithms to understand the complexity.
00:07:15.800Because you've got thousands of cells in a complex dance with the cancer and trying to figure out what that means took a lot of algorithmic effort.
00:07:26.140So, we're a computational lab as well as a wet lab, as we call it.
00:07:38.020And so, you know, I mean, I think what makes a good scientist is knowing what you don't know and knowing who to bring in to help you create what it is that you want and being able to explain it to them in a way that gets them interested.
00:07:53.980And that talent, frankly, translates very well in the entrepreneurial side of things.
00:08:00.640When you're talking to venture capitalists, you can convince them that the biology is interesting, that it's doable, that here's the kind of people I need.
00:08:10.060And I always use this term inevitable, that it's inevitable.
00:08:14.200This is something that's coming, so it really is up to the early bird that gets the worm.
00:08:20.760If you can see that it's something that will happen and has to happen and you have a solution for it, it might not be currently the best solution, but it's a solution.
00:09:01.260I've been good at the, I'm more, I would say, good at the intuition of how biology works.
00:09:08.680And intuition plays a larger part, frankly, in science than people would like to admit.
00:09:15.700Yeah, you know, one of the things that's always struck me as peculiar about scientific research papers is that the introductions are always a lie.
00:09:25.140You know, it's so interesting because I thought about this for a long time.
00:09:31.920It really struck me when I was first in graduate school because when you write a scientific research paper, you present the situation as if all the background reading that you did produced an incremental transformation in your thinking such that you generated a hypothesis.
00:09:55.460Usually what happens is that people have an intuition that's derived from some pattern recognition and then they backfill it and make it look like it's algorithmic.
00:10:06.860And then the other thing that's so bloody peculiar about that is that there's almost no discussion in graduate school training.
00:10:14.460Maybe this was different where you went on hypothesis generation itself.
00:10:19.460It's as if scientists swallow the idea that you're creating your hypotheses in this algorithmic manner as a consequence of grinding through the research.
00:10:29.460I know I had a student at Harvard, Shelley Carson, who worked on creativity, and she would make very large leaps with regard to her hypothesis, and then it would take her, you know, a few months to backfill so that she could bring people along to explain the justification.
00:10:51.220But that certainly wasn't the method by which it was derived.
00:10:54.220You strike me as a peculiarly creative person for a scientist, by the way, I mean, that might seem a perverse characterization, but we also studied predictors of scientific prowess and openness, which is the trait marker for creativity, was actually slightly negatively correlated with scientific productivity, at least at the graduate school and then early career level.
00:11:20.220But you've got a very wide range of abilities, but you've got a very wide range of abilities, and then you've got this both an entrepreneurial and a managerial twist.
00:11:32.900Because that's also a rare combination.
00:11:35.280I think what, I mean, it's hard to talk about yourself as if you don't sound like, not to sound like a narcissist, but I think if you can marry creativity with practicality,
00:11:48.220that's the magic mix, at least for me, is I'm very good at rapidly iterating all the possible reasons why something can be the case, and then rank ordering them very quickly, coming up with at least two cutoffs.
00:12:06.520One is, yeah, this is possible, but it's very unlikely that magic dwarves run the universe, right, everything below that level.
00:12:15.920But then above that level, there's two, there's one more cutoff.
00:12:19.420One is possible, but impractical or perhaps not easy to prove.
00:12:27.340And so if you can rapidly rank order and then come up with where something sits, then you can immediately turn and tell a student, yeah, you should do this.
00:12:37.840Or, yeah, you probably shouldn't do that because here's the reasons why there are so many other things that it could be that you can't prove or disprove.
00:12:46.140So let's not go down that road because it's a rabbit hole.
00:12:49.800So I think marrying creativity with practicality and being able to see, and frankly, what I call reverse engineer the future, you know, it's like you can see what it is, and then you know I need to do this first, and then I need to do that.
00:13:06.340And once I've done each of these steps, those are milestones that give you confidence to take the next step.
00:13:12.520And then because if I think like that, then that actually helps with talking to venture capitalists because they can then follow the path that you've just laid out for them.
00:13:23.760And when did you start your first company?
00:13:27.580Soon after getting to Stanford, actually.
00:13:33.380But I had already learned a lot from my mentors, Len and Lee Herzenberg.
00:13:37.920So I was lucky having come to Stanford to end up in their lab because Len and Lee, who were frankly hippies, you know, they had the two of the three biggest patents at Stanford.
00:13:54.060One was for something called the flow cytometer, which brought in hundreds of millions of dollars.
00:13:59.940And perhaps even more important were the monoclonal antibodies, what are called humanized antibodies.
00:14:06.040So by making monoclonals that could be injected into humans without raising an allergic reaction or a strong immune response, almost all of the injected antibodies today are based on those original technologies.
00:14:21.340And Len was just a natural entrepreneur.
00:14:26.720He never started any companies, but he knew how to license them.
00:14:30.320So he would always bring me into his office when he was negotiating with the pharma companies, and he would give me the contracts to read because I was one of his favorite students.
00:14:42.480So he's like, okay, I'm not going to waste my time by giving this guy something because he'll actually understand it and pick it up.
00:14:49.080And he introduced me to the best patent attorneys of the day.
00:14:52.380And so I learned from them what it was all about.
00:14:54.960So it was, you know, much of what I would love to say is mine is just a rewrite of what I learned from Len and Lee.
00:15:52.720You're, you know, you're going to—you shouldn't dirty your hands with this yet or now, frankly.
00:15:59.820They didn't even want me getting involved at all.
00:16:01.720And it was funny because a lot of them, you know, 10 or so years later, were back in my office asking for my advice on how they could start a company.
00:16:11.940Well, it's a rarer pathway to be scientifically productive and to make your talents manifested in multiple directions and to be an entrepreneur.
00:16:27.040I mean, that's—the research that I referred to looking at predictors of scientific productivity showed that the best predictor, apart from IQ, obviously,
00:16:38.520which is always the best predictor of virtually anything complex by a lot, was conscientiousness, right?
00:16:45.360Just sheer diligence and that there's a certain kind of narrow focus that goes along with conscientiousness, too.
00:16:52.060And so, it is reasonable advice if you're talking to someone whose primary talents are diligence and industriousness for them to focus intently on one area so that they can establish themselves.
00:17:05.340But that obviously wasn't the appropriate pathway for you.
00:17:10.140And so—but that—and it's also complicated and difficult to start a company as well as a research lab and to teach and all of that.
00:17:19.860So, as generic advice, it probably wasn't too bad, but it didn't seem to hold in your case.
00:17:39.200Well, so for everybody watching and listening, I mean, obviously, that's a tremendous number of patents because actually one patent is a lot of patents.
00:17:50.820And on the research side, you can do a rule of thumb calculation, and not everybody agrees with this, but three research papers properly packaged make a pretty nice PhD thesis.
00:18:03.380So, 300 is roughly equivalent to 100 PhDs.
00:18:06.960And that's a lot of PhDs, and I think that's a reasonable way of looking at it, not least because most PhDs end up with either zero or one publications.
00:18:17.700So, the three publication rule of thumb isn't a bad one.
00:18:21.720What do you think of that characterization?
00:18:25.080I think the better way to do it is how often are you cited.
00:18:29.400So, you can publish and never be cited.
00:18:32.980So, at this point, I think I'm at about 89,000-something citations.
00:18:39.040So, that puts you in the top whatever percent.
00:18:42.020And a lot of those, frankly, were the retroviruses because people use the retroviruses.
00:18:49.100And then a lot of it are the technologies that I've developed because for the immune system measuring technologies, whether it's something called Cytoff that I co-developed with this guy at the University of Toronto.
00:19:02.580He invented the machine, but I showed how it could be used for immunology or the Codex or the MIBI or Phosphoflow or now the split pool synthesis technology for single-cell analysis were all things that sort of just, like, came to me.
00:19:20.820It's amazing that some people think that science is this methodical step-by-step, whereas more often than not, it's you pose the question in a way that sort of sets your subconscious to work.
00:19:37.020But then you lay out in front of you all of the necessary raw material and you say, somewhere in this morass is the answer.
00:19:45.760And then at a lecture, out of nowhere, it suddenly just appears, you know, in your head, fully formed.
00:19:55.000It's almost as if your subconscious was busy working and it finally said, oh, I'm done.
00:20:03.040As we celebrate Independence Day this July, we're reminded of the freedoms our founders fought to protect, especially the fundamental right to life, liberty, and the pursuit of happiness.
00:20:12.240But here's something that might surprise you.
00:20:13.680There are still Americans today whose most basic right, the right to life itself, is at risk.
00:23:53.520Now, do you have your own large language model?
00:23:56.300And how do you stop them from lying to you and producing false, like, hallucinations and citing papers that don't exist?
00:24:04.760Yeah, we, you know, we use pretty sophisticated versions.
00:24:08.400We don't have our own LLM, but we have our own chain of thought layer that sits on top of these for the work that we do with the large language models.
00:24:18.900We have, we use OpenAI or Anthropic or Gemini, you name it.
00:24:25.180And then we have a layer sitting on top.
00:24:40.320Yeah, and it's a very weird thing to use.
00:24:42.580I don't know if you have the same experience, but in this system we trained thinks like I think, but it can also think up things that I haven't thought up, which is, I guess what's happening as far as I'm concerned is that in the statistical encoding of my linguistic knowledge,
00:25:04.240is all sorts of latent information, right?
00:25:06.500I mean, I mean, there's relationships in my patterns of thought that I haven't explored, obviously.
00:25:11.500And they're probably near infinite in scope.
00:25:16.500I mean, I would say that's the case for everyone, but because there's just so much information that's encoded.
00:25:22.020And so does your system refer to the material that you've trained it on first and then to the large language model that's general after that?
00:25:32.480It starts with it, but I think the value is because it has lowered barriers, which is really what you're talking about.
00:25:40.860The barriers are lower to finding analogous or metaphors of what it is that you've said in other ways of thinking.
00:25:48.680I mean, much of my work, the inventions that we've made, we're taking the metaphor approach of finding somebody else's technology that works in something else, completely unrelated to biology, and showing how it could be applied to biology, right?
00:26:05.300And so, you know, ideas very often, the best ideas are saying, or the best teachers are people are saying, this is something like this.
00:26:12.860Think of it like this, and then giving a metaphor or an anecdote that explains the idea.
00:26:19.740And so the large language models are just metaphors on steroids.
00:26:23.500Depending on how you set the heat, it can find things for you and solutions for you that you probably could have thought of,
00:26:36.560So for me, for instance, on the atomic imaging idea, you know, I said, okay, well, here's what I'm doing.
00:26:42.940Help me write the patent on it, and it helped me start the patent that I gave to the patent attorneys who wondered what lawyer I'd used to write this because it was already pretty good.
00:26:52.760But I said, find me five other ideas that might also do the same thing.
00:26:59.640And surprisingly, it came up with ideas.
00:27:01.660Now, they were impractical, but it came up with ideas that were, you know, were like, oh, that's pretty cool.
00:27:08.240I wish I knew about this area of physics.
00:27:11.840So, you know, it's actually there was a study just done out of Stanford just last fall that showed that large language models can be as creative as humans,
00:27:22.260if not more creative, as scored by humans, just less practical.
00:27:29.300Yeah, I wonder what the bound is on practice.
00:27:32.720Like, do you suppose, I've talked to some computer engineers, including my brother-in-law, who's quite a genius.
00:27:40.460And one of the things that he is prognosticating, and not only him, is that we have these, obviously, we have large language models that are assessing the statistical relationship between words at multiple levels of resolution
00:27:55.820and can do this remarkable thinking, for lack of a better word, because it sure looks a lot like thinking to me.
00:28:02.720But, you know, human beings, we seem to be able to do that with images as well, right?
00:28:08.860And also with movement, like embodied movement.
00:28:12.320And my guess is the practicality constraint is probably something like the referencing of the semantic system to the domain of image and movement, right?
00:28:24.160Will this, because just because it's coded hypothetically in the linguistic corpus doesn't mean that it's in keeping with the way the world makes itself manifest.
00:28:34.800And humans have three different memory systems, at least, right?
00:28:38.360We've got semantic and episodic and procedural.
00:28:41.040And my suspicions are that when we're looking for practicality, that we assess the joint contributions of all of those different ways of representing information.
00:28:51.720And the large language models can't quite do that yet, but they will soon.
00:28:56.440I mean, it's got to be the case, right?
00:28:58.160Because someone like Elon Musk, for example, he has this immense corpus of real-world data.
00:29:03.480And it's got to just be a matter of time before that's integrated with the large language models.
00:29:09.000Well, actually, you know, there's a part of your brain that does a lot about what you're talking about.
00:29:13.020And it's called the basal ganglia and the caudate potamen, which is actually where intuition happens.
00:29:20.180So there's a game, a Japanese game of chess, which is sort of a limited form of what we think of as chess.
00:29:28.620And so they were doing basically reads of people's brains while they made these moves.
00:29:37.160And especially when they made like what would be considered a genius move.
00:29:41.040And the area of the brain that lights up is the head of the caudate and the potamen, which is – so the basal ganglia is actually what part of the brain tells you where your body is in 3D space, what your memories are, et cetera.
00:29:56.080It's all subconscious, subservient to your executive function.
00:29:59.380So when you make a decision to do something, that gets sent to the basal ganglia, which determines whether or not you can actually do it and whether you want to do it.
00:30:09.260Like if you're walking across a room, how do I walk?
00:30:12.000All those subconscious decisions are all done in the basal ganglia.
00:30:16.740But as it turns out, as humans have evolved, that has then been sort of taken over to be used as our decision-making system.
00:30:27.040Our intuition system works through the basal ganglia.
00:30:30.680So all those ideas that you just talked about, where it actually finally comes to, is this practical or not, the basal ganglia is part of that process, a central place for that process.
00:30:44.820So is that an embodiment constraint essentially?
00:31:14.600I mean, believe it or not, we came to this area of the brain because of some of my UAP stuff.
00:31:20.160Um, and we did a study with a group at Harvard and found, in fact, that, uh, the size of this area of the brain, uh, correlated directly with intelligence.
00:31:58.460I'm very interested in the neurological determinants of intelligence.
00:32:02.500But there was a, there was a guy in literally, I think, the year 2000 from Harvard, who, through his own sort of best guesses or whatever, who had proposed before anybody actually found it, that, I think his name was Hoffman.
00:32:32.400But he was already a postulate when he was like a postdoc.
00:32:36.100I wonder what the, what do you think the connection is?
00:32:38.940I mean, when you think of intuition, you tend to think, at least I tend to think of pattern recognition, let's say.
00:32:46.540What, what do you suppose the connection is between pattern recognition and, and, and the caudate and, and it's, and it's, and its relationship to, to motoric movement?
00:32:58.220It's a, it's making a decision with sparse data.
00:33:01.020It's, it's, it's the, it's the instantaneous decision to leap when there's, when there's movement, like the leopard's about to jump out of the tree at you.
00:33:13.380And it's the movement, but, you know, in, in the military.
00:33:18.560Right. So that's, that's, that's having to, well, I would imagine someone on a playing field, you know, in a hockey game or a soccer field.
00:33:25.300Obviously, they're tracking many moving objects simultaneously and abstracting out something like a meaningful pattern.
00:34:25.080So it's, humans seem to have evolved a way to use a pre-existing system in the basal ganglia that was really just there for motor movement and making subconscious decisions.
00:34:35.680And they've, they've, they've layered over it and they've put an abstraction layer on top of that so that we can now use it in for mathematical principles and, and other ideas.
00:34:50.520And, and I've learned actually to, to see when the aha moment comes, it's almost like a form of color.
00:35:00.380It's like when the next time you get an aha moment, you, if you can try to capture that it, when it happens and realize that it was a different kind of input than what a methodological moment is, where you basically, you've added it up and you've gotten the number by just simple addition, as opposed to that aha moment.
00:35:24.920And I've learned to recognize and pay attention to the aha moment, not that it's always true, but that it came from an intuition because, you know, it's, it, it very often you can get it and then just dismiss it because it was just an intuition as opposed to something that you figured out.
00:35:45.940So, listening to those aha moments, and I, I, I, I'm telling you, I see it as a color.
00:35:52.320When it happens, I, I, I recognize it as a different kind of thought.
00:35:56.860It's not like it's being given to me magically or anything like that.
00:35:59.280I know a lot of people would like to think that that's what it is, but.
00:36:02.800There's something kind of magical about it.
00:36:04.780It, it, like, thought has this revelatory quality, as you pointed out.
00:36:09.280You can set your sights on something and then the pathway there, the, the mechanism that delivers you there is delivered to you, you know, so there is a magic about it.
00:36:20.580You know, I'm going to, people are going to laugh at me for this because I always do it, but I'm going to do it anyways.
00:36:26.180That, I've been studying Old Testament literature a lot for a long time.
00:36:34.960And I'm interested, I'm bringing this up because of something you said about the basal ganglia, too, developing an abstraction layer.
00:36:43.440You know, part of that abstraction layer is no doubt our ability to tell stories because stories are verbal representations of action patterns.
00:36:52.920And so, so the, the burning bush episode in, in Exodus, that's an intuition episode.
00:36:59.960You know, and Moses takes his intuition seriously enough to deviate from the, from the, from his normative path.
00:37:09.460And then he delves deeply into the source of the intuition.
00:37:13.740And that's what transforms him into a leader, right?
00:37:16.940He gets to the bottom of something, down a rabbit hole to the bottom of something.
00:37:20.760And so it is a, it is a, it is a, it is a narrative representation of not only of intuition, but of the willingness to attend to it and to, and to delve into it deeply, right?
00:37:35.480So, okay, so we should switch topics here.
00:37:40.220I wanted to go over your background with you to establish for everybody listening who you are.
00:37:46.800And it's pretty obvious that you have a multitude of abilities and a stellar track record that's continuing.
00:37:56.660And so that sets the foundation for our next discussion.
00:38:01.860You started to become interested, and I would like to know the story, in unidentified aerial phenomena.
00:38:10.060And that's definitely a lateral move from your other interests.
00:38:13.900And so I'm very curious about all of that.
00:38:17.920I guess what I'd like to start with is why the interest and, and why take the risk to pursue it as well?
00:38:26.140Because you have a lot to lose, let's say, on the reputational front.
00:38:29.300And it's clear you're a very creative person.
00:38:31.200So I'm sure your interests go everywhere.
00:38:33.760But tell us how it is that you became interested in this and why you decided to pursue it with some degree of seriousness.
00:38:42.440So, I mean, there's a couple of origin stories to it.
00:38:48.580But I think the most, the easiest to start with is with the Atacama mummy, right?
00:38:54.660The small mummy that people had been promoting as being an alien, right?
00:39:00.480The mummy that was found in Atacama, Chile.
00:39:25.820And so we arranged to get a small piece of the body, a rib.
00:39:33.700I wanted the rib because I wanted the bone marrow from within the rib because I felt that that would be the place best protected from bacterial contamination.
00:39:41.760And the long and the short of it was that we showed that it was a human baby, probably, well, it was probably preterm birth, but that we found a number of mutations in the genome that could explain what it looked like and why it looked the way it did.
00:40:00.420And so, you know, when a movie came out regarding that circa 2012 or so, it was like sending up, you know, a flare to two sides of the world.
00:40:16.440One, the people who didn't like that I was debunking the alien.
00:40:21.180So I became an instant symbol of dislike for the UFO community, which is interesting, you know, paradoxically these days.
00:40:32.880But then it also was a flare to scientists, as it turned out, as well, the intelligence community, that here's a guy willing to look at things and just call them as he sees it.
00:40:44.820And so that led, as it turned out, to somebody representing the CIA and an aerospace company showing up at my office at Stanford, literally unannounced, showed me their credentials and said, we need your help looking at patients who've had harm done to them.
00:41:05.580And I was like, well, what kind of harm?
00:41:07.540And then they laid out the data, literally like MRIs and x-rays of internal scarring of—
00:41:16.300Are these people who reported abductions?
00:41:24.140These are intelligence agents, diplomatic corps, military personnel, et cetera, all who said that they were hearing buzzing in their ears or, you know, and then a small subset of them said that they'd been in proximity to things that you would call a UFO.
00:41:42.360So, I thought it was a joke at the beginning, especially when they mentioned the UFO stuff, because I had no intention at the time of going back and doing more alien research after the Atacama mummy escapade.
00:42:04.480Well, one, I was willing to talk to people about this stuff.
00:42:08.660But two, they wanted to do blood analysis of the individuals who'd been harmed as part of a complete medical workup.
00:42:16.860And so, they'd asked around, and they said, well, who does the best blood analysis?
00:42:20.220Oh, you need to go talk to this guy, Nolan, at Stanford.
00:42:23.080He has this thing called Cytoff that can do the deepest analysis of blood that, you know, currently today and still.
00:42:29.060So, basically, over the course of two or three years on working with this group and on these patients, it turned out that these were actually the first of the Havana syndrome patients.
00:42:43.660I'm sure you've heard of Havana syndrome.
00:42:47.980So, Havana syndrome was something that basically came out around 2015, 2016.
00:42:55.200And it was called Havana because it was the diplomatic core individuals in our government who were getting headaches or having to be sent home.
00:43:07.520And it turned out that it's probably a kind of microwave technology being used by some of our adversaries.
00:43:15.240You know, some people in the CIA tried to debunk it, but now there's a whole, like, set of paperwork put out by the Department of Health and Human Services on anomalous, what's now called anomalous health incidents, where Havana syndrome and all of the sets of associated symptoms are all listed.
00:43:37.240And there's a path now for people who think that they have it to go follow it up, you know, appropriately with the Veterans Administration or what have you.
00:43:52.560So, you had someone from the CIA show up to your office, and he had a list of people who had medical problems.
00:44:00.600And some of those medical problems were a consequence of people coming into contact with—contact with, what, technology that is mysterious?
00:44:13.700Is that the right way of thinking about it?
00:44:16.100Well, I mean, they didn't know what the source of it is, but now we know that it was basically—I mean, it's an energy weapon, just a microwave weapon.
00:44:23.940And just imagine you could focus the beam of your microwave in a very narrow path towards a person's head.
00:44:30.740You'll bake the brain cells in their head.
00:44:33.720So, I mean, there's nothing magical about it.
00:44:36.720Everybody knows that these things exist.
00:44:39.480At the time, when we were working on it, we were calling it interference syndrome.
00:44:44.140You call something a syndrome when you don't know the exact cause, but it can have a variety of manifestations.
00:44:49.760And so, what we had done was we had matched the symptoms to what are called the international diagnostic codes so that we had the ability to say, oh, it's this, and it's this, and it's this.
00:45:01.620And if you have 10 of 15 of these, you have interference syndrome.
00:45:07.360So, at the same time, somebody was figuring out what Havana syndrome was.
00:45:11.020And it turned out that our set of symptomologies matched perfectly with the Havana syndrome ones for most of our patients.
00:45:19.300We were able to hand all of that over to the U.S. government, and I've worked with Senate staff and others on that, and that's something I can't talk much about.
00:45:30.420But what remained, and this is what's good about how science is done, once you've characterized something and you find it uninteresting, not that it's uninteresting that these patients are being harmed, but I could hand it off to somebody else who would then take care of it as a national security concern.
00:45:46.220What was left on the table were the oddities, and those were now the people who had gotten close to UAP, they claimed, at least some of them.
00:45:57.400And they had, as it turned out, slightly different symptomologies.
00:46:02.720Some of those were more likely to have erythemas or scarring on the skin as opposed to internally or manifestations on the back of their neck of some kind of irradiative damage of some kind.
00:46:23.320And the pattern was always anecdotal, unfortunately, in that they had a story that you at face—
00:46:30.640Right, but I mean the symptom pattern was stable.
00:46:33.820And how many people, how many individuals approximately, like what kind of sample pool were you assessing?
00:46:40.140Now you're down to about five or six people because of the original—
00:46:44.320Okay, so it's a small number of people.
00:46:45.460Of the original hundred that we started with, 90 or so, it turned out, were what we could think of as Havana syndrome.
00:46:51.980The remaining were what were interesting.
00:46:54.840And, you know, but sort of back to, let's say, my career.
00:46:58.620My career has always been—I've always been good at seeing the data point off the curve and realizing that it's not noise, or at least asking the question, how did that data point get there?
00:47:15.040And not just, you know, going with what's sitting on the line, but understanding why the data point off the curve is important.
00:47:25.780And then being able to quickly, again, back to that, iterate the possibilities, say, ah, well, it's—if we know that it's not a problem with the instrumentation, then it's an indication that we don't understand something.
00:47:44.900And so that was where I was already starting to get introduced because of this UAP stuff, because of that we had these groups of individuals who said that they'd gotten harmed by UAP.
00:47:56.700And we diligenced them to make sure that they didn't have some sort of psychological problem.
00:48:30.540And so once you start to get that, I was like, okay, well, there seems to be something here.
00:48:35.120And you raised a point, you know, ruin your career.
00:48:40.100I literally was told by a senior official at the National Cancer Institute by around circa 2014, 2015, because I was just talking about this, just saying, isn't this an interesting idea?
00:48:51.640You're going to ruin your career, Gary.
00:48:53.960And I was just like, but it's—but the data's on the table.
00:48:59.180It isn't ridiculous to ask the question.
00:49:03.380But the fact that they were trying to push it off the table incensed me.
00:49:09.340It was just like, that's not how a scientist thinks.
00:49:12.420That is just your—and I said to him, I said, you sound more like a priest than a scientist.
00:50:19.980There's very few papers that you will ever read that ever say there is, at least in biology, this is a conclusion.
00:50:26.800There's all kinds of weasel words that we as biologists use to give ourselves diplomatic egress just in case.
00:50:34.420So, but, you know, when people like Neil deGrasse Tyson say there's no evidence, well, that's just a lack of understanding of what the difference between data and evidence is.
00:51:22.480Okay, so tell me, well, tell me a typical story, like the typical story pattern that characterized the testimony of these leftover individuals whose symptoms were troublesome but somewhat anomalous.
00:51:39.240And then you took it seriously because there had been psychological workups done on them, and there were a number of people reporting the same thing.
00:52:13.760And he came to me as part of this group of 10 remainders, and I was introduced to him to do the blood analysis and do the collection of the blood.
00:52:27.760And then later, as it turned out, and here's an interesting thing, later, he developed a heart problem, and he couldn't get the Veterans Administration to open up his file so that he could get – he could prove that – or that it might have actually been originally caused at Randall Shum in England because his medical file was deemed top secret.
00:52:52.720So, we literally had to go to Senator McCain in whose state this guy lived in Arizona and get him to write a letter to the Veterans Administration forcing them to open his file so that he could get insurance payment for his heart condition.
00:53:16.860So, why does an individual who had a problem that he claims had been, you know, caused through some interaction way back when, why do you have to make his file top secret?
00:53:32.540It was just somebody had decided it needed to be top secret because things related to UFOs just need to be, you know, nobody talks about them, brush them under the table.
00:53:41.900But we literally – and it's, again, it's public record.
00:55:00.960So, the reason why we started the Sol Foundation – and it was me, Peter Scafish, and David Grush.
00:55:07.740David Grush was the gentleman who testified in front of Congress about what he claims were the reverse engineering programs.
00:55:14.480And the principal reason for starting the Sol Foundation was to enable, let's say, a picket fence within which people of reasonable intelligence or academics, who don't always have reasonable intelligence, but could have a conversation and not be laughed out of the room.
00:55:34.160So, to be able to say, here's a hypothesis, and here's the data I have.
00:55:39.020Do you think my hypothesis matches, or do you have another idea?
00:55:42.620But the spectrum of things about which we wanted to be able to talk about were everything from religion all the way through to material science on my side.
00:55:53.060So, we have Peter Scafish, who's an anthropologist, and a – what is the other one?
00:56:02.320Well, he's an – let's call him an anthropologist.
00:56:04.160And so, he's interested in people's stories, right?
00:56:10.560What's the pattern of the experiencers?
00:56:13.980And what kind of, let's say, trauma might they undergo?
00:56:18.020Not only because of the experience itself, but the trauma of not being able to talk to your friends and or family about what it is that you think that you saw.
00:56:28.220Because of the stigmas associated with talking about this and not wanting to be, you know, considered crazy.
00:56:34.440And then – so, he's collecting and writing papers on that.
00:56:41.720We had somebody from the Catholic hierarchy write a paper on that for us.
00:56:48.240Two, on the more, you know, extreme science side, the hard science side, the materials analysis that I do.
00:56:58.940And part of it, again, was to say, okay, let's have this conversation.
00:57:05.600Let's – we had our first foundation meeting, I mean, big convention at Stanford where we had about 200 or 300 people there who'd come from all over the world.
00:57:25.420And the funny story there was about two weeks before we were to have the meeting, I started getting these pings from administrators around Stanford that there might be a problem.
00:57:37.760And I was like, oh, God, you can't do this to me.
00:58:15.980In fact, the Alumni Association had me give, at the last homecoming, a big talk to probably about 200 people about it because of the interest level.
00:58:31.220So there's been no problem on that front.
00:58:59.200He's a venture capitalist in the Bay Area.
00:59:01.580And he's heretical in the sense that he didn't believe that whatever this was was necessarily extraterrestrial.
00:59:11.140But it was some other kind of manifestation of either the human psyche or something more beyond, something almost, you know, paranormal in its capabilities.
00:59:28.880So it was interesting to listen to this, but I was more interested in, you know, okay, well, what can I teach another scientist?
00:59:40.260So it turns out Jacques had a number of materials, metals and or objects that had been associated with landings of alleged UAP or UFOs.
00:59:53.220And so I said, okay, well, give me some of them.
00:59:58.360I need only tiny amounts and we can do pretty traditional analysis on it.
01:00:04.260And so one of the things that I got a hold of, we showed recently to be, that was from a beach in Ubatuba, Brazil, that a fisherman had seen this object drop from some other, from this UFO.
01:00:23.160And it was, it shattered and he picked up some pieces of it and it made its way through what I would consider to be a reasonable chain of custody.
01:00:32.520And we measured it and we measured it and it was 99.999% silicon.
01:00:39.980Okay, that's not hard to make today, but it's not something in the late 1950s or early 1960s, you drop giant pieces of all over a beach in Ubatuba, Mexico.
01:00:54.960So it's, whatever that was, it was clearly an object of industrial purpose, right?
01:01:05.260There's no 99.999% silicon anywhere on planet Earth.
01:01:11.820And I actually have atomic, I have an atomic map of one of these pieces that we developed, that we did with atomic probe tomography.
01:01:20.200What was fascinating was that one of the two chains of custody that I obtained also had magnesium ratios that were not what you would expect from Earth.
01:01:36.000They were different than the standard magnesium ratio.
01:01:39.060So magnesium has three isotopes, 24, 25, and 26.
01:01:44.66024 is like, let's just say, rounded up to 80%, and the other two are 9 and 11%.
01:01:53.580Whereas the, one of the two chains of custody, the magnesium ratios were just higgledy-piggledy all over the map.
01:02:04.180They had nothing, they didn't look anything like what you expect to find from a piece of silicon on Earth.
01:02:12.060Anywhere you look on Earth, you're going to find silicon, sorry, the magnesium at the 80, 11, and 9 ratio.
01:02:21.540Whereas this, one of these pieces was wrong.
01:02:38.100We're actually writing the paper up on that one.
01:02:40.680I published a peer-reviewed paper on another thing, another object from what's called Council Bluffs, Iowa, where, again, there were multiple witnesses.
01:02:51.520In this case, even the police, had seen an object, and it seemed to drop something.
01:02:58.180And when the people arrived, they thought actually it was a plane crash.
01:03:01.200When they arrived, they found about 30 pounds of molten metal in the middle of a frozen field.
01:03:14.580And the long and the short of the analysis was there was nothing wrong with the isotope ratios, but it was a mixture of metals that nobody would normally put together.
01:03:28.660So it's kind of like if you were to take chocolate, vanilla, and strawberry ice cream and partially melt them and just kind of turn your spoon a couple of times around.
01:03:37.120Depending on where you looked, you'd find different ratios of chocolate, vanilla, and strawberry, as opposed to if you were to put it in a blender, everywhere you looked, it would look the same.
01:03:47.900So what I found in the metals was that it was incompletely mixed.
01:03:52.820Okay, so who would drop 30 pounds of incompletely mixed iron, titanium, and aluminum in the middle of a field for no good reason from something that looks like a UFO?
01:04:07.120So all the conventional explanations that it was thermite, it's not thermite because there's no aluminum hydroxide, I checked.
01:04:16.820You know, to carry that much molten metal requires, at that temperature, a cauldron that would be like half a ton to the middle of a field.
01:04:26.540You're not going to put it in a plane.
01:04:31.020But the reason for doing it, and actually there's somebody who it looks like is going to give me sort of free money to analyze more of these things,
01:04:42.020is not to prove that they're from UAP, but it's to do the right kind of analysis on the materials
01:04:50.600so that I can get it out there and publish it with no conclusions, just here's the data and here's the story,
01:04:57.800and here's the analysis as complete as we can do at this time.
01:05:00.980Because maybe somebody else will look at it three years from now or some other enterprising student and go,
01:05:05.640ah, that's how you would, if you released this, this would be the engine control for, I don't know, anti-gravity or something.
01:05:18.180So it's, you know, it's part of that thing of like you come up with an intuitive idea because you've spread all of the data in front of you.
01:05:28.440Well, if you don't have the data, you can't come up with the solution.
01:05:32.800But if I can get the data out to as many people, maybe somebody else will come up with the hypothesis that unifies the story.
01:05:41.140So it's part of like the, I mean, I think of it as the open source data approach or the open science where you get the data out for everybody
01:05:50.480because somebody paid for it, so maybe you shouldn't keep it in your, you know, in your desktop drawer or these days in a folder on your computer.
01:05:59.840Get the data out there so that other people can use it.
01:16:41.540Some of them though, were moving in ways that would be hard to explain by drones, but all
01:16:47.380the stuff that we observed close to shore was clearly human activity.
01:16:53.360But so we're setting up, we're setting up Skywatcher as sort of a dual purpose.
01:16:58.760One is to work with the government to hopefully, or defense contractors, or anybody who wants
01:17:06.240to pay for our services to collect aerial data basically as rapidly as possible.
01:17:14.880Because often you can't collect the data when there's an anomaly that shows up, I mean, our principal goal is protection of the United States.
01:17:29.460But if in so doing, we happen to collect other information about some, let's say, anomalous objects, we will have the tracking data necessary to say, hey, well, this is, we don't understand this.
01:17:42.200And it's important to know because if it isn't a human adversary who have capabilities that we don't appreciate, even if somewhere in Area 51, they have something that does that.
01:17:58.460It's good for, I think, our military, the more public aspect of our military to know that these objects do exist and report them when you see it, because it might be the Chinese, or the Russians, or the Iranians, right?
01:18:13.880You want to know this because if you ignore it, you could be ignoring the data point off the line that is important to know about.
01:18:25.280So, always back to that, don't ignore the anomalies.
01:18:30.260Because anomalies, just about every single Nobel Prize that was ever awarded in physics and chemistry or biology is because somebody paid attention to the anomaly.
01:19:06.440So, there are, let's say, five characteristics of something that you would think of as an anomaly.
01:19:15.960One is instantaneous acceleration and deceleration, right?
01:19:20.440There's very few things that we know of that can go from zero to 5,000 miles an hour and then stop on a dime without squishing everybody on the inside, you know, sending them through the windshield.
01:19:30.320So, when you see these things go from, in the case of the, I think it was the Nimitz or the Eisenhower, it goes from sea level to space in less than a second.
01:19:43.740And they have the radar trackings of those things.
01:19:45.680And now imagine the size of the object, let's say it weighs a ton, to instantaneously accelerate and decelerate at that level, it takes more than the, would take the energy of more than the nuclear output of the United States for a year.
01:20:02.740Okay, so, where did you get that energy, first of all?
01:20:07.180So, instantaneous acceleration and deceleration.
01:20:11.540So, seeing things that do zigzags across the sky means that somebody or something has control, if it's going fast enough, and it's not doing an arc.
01:20:23.380It means something has control of momentum and inertia.
01:20:27.580You can, they can negate momentum and inertia.
01:20:30.560So, that's an observation seen hundreds, if not thousands of times by pilots all over the world.
01:20:38.780So, what does that mean about our understanding of physics, first of all?
01:20:51.800So, you're moving and doing these things, and yet if you look at them with FLIR, which is a kind of infrared, you don't see any hotspots.
01:21:01.120If you were to look at a jet, all you would see is the plume from the jet.
01:21:09.040So, no flight surfaces, meaning, you know, basically, Bernoulli's principle is not at play here, right?
01:21:17.420Which is basically how the wings work and lift.
01:21:19.900So, Bernoulli's principle is not at play.
01:21:23.800So, you're moving without a flight surface and without an apparent mode of inertia.
01:21:33.100You're not putting something out so that you can move forward.
01:21:35.760And then, the other one is what you would think of as what's called transmedium travel, meaning something that can go from the water to the air and then back again or to the air and to space.
01:21:51.240We have nothing that can do something like that.
01:21:54.360But recently, there have now been drones made and talked about openly, and actually, these are U.S. drones just shown on a – I saw on a military video recently where they can go – drones can be underwater, travel, and then come out of the water and go do the attack.
01:22:12.420But that's only been developed in the last few years, not something from 50, 60 years ago.
01:22:18.600So, those are the kinds of things that people see.
01:22:21.260And again, it's – you know, you ask me what I think of as real.
01:22:27.680Those anecdotes are, to me, stories, and why I get interested in the medical or the material side is it's something I can repeat.
01:22:39.240I can't repeat these pilot observations, but I can repeat experiments on materials or experiments on – not experiments on human, but reading the humans who have been harmed.
01:22:51.600Now, the thing about Skywatcher is that we, at least in a limited sense, have a signal that can be released that sometimes it seems to attract these objects.
01:23:10.520And so, that's where the repeatability attempt is coming in.
01:23:15.320So, there's a – because it's a company and I'm not the official spokesperson for it, and this is public information that's out there, is that there's a signal that an individual as part of Skywatcher had determined when he was working with the military not as – it wasn't his purpose to develop it.
01:23:38.820So, he didn't take anything out, it was sort of a – he noticed something, and then he refined the technique, and now he knows that he has, let's say, an electromagnetic sequence that he can release that somehow seems to have these things, objects, show up.
01:24:00.020We go out on these week-long events in, like, the middle of nowhere, and stuff shows up.
01:24:13.620And, you know, some of it's been on – some of it's, you know, you can go find it on Twitter.
01:24:20.600But the stuff that's on Twitter isn't good enough, in my opinion.
01:24:24.180I'm more interested in the data that we're more recently collecting with better cameras and better sensor systems.
01:24:31.240Because the idea is just to do the science.
01:24:32.960So, I think what we'll do on the Daily Wire side, because we have to wrap this up in relatively short order, I want to close here by asking you what you've concluded provisionally as an explanation for this, like what hypothesis you're nursing.
01:24:54.020And then, on the Daily Wire side, for everybody watching and listening, I'd like to ask you more about stories, about what you've seen, for example, when you've been on these Skywatch expeditions, and what the Skywatch program is reporting.
01:25:10.040And then also to delve a bit more into the political, you talked about the – Schumer and – I don't remember the other senators.
01:25:29.980Narratives of sightings from pilots in particular.
01:25:33.580Okay, so we'll delve into that more on the Daily Wire side for everybody watching and listening, so you can join us there for an additional half an hour.
01:25:40.820To close up here, I think it would be useful for you to let us know, if you would, what the hell you think is going on.
01:25:51.700And what this has done to you, too, this – I mean, this has got to kind of come out of the left field, so to speak, in a severe way.
01:26:01.580And so, I imagine it's put a bit of a bump into your life.
01:26:05.300I mean, maybe one that's mostly interesting, but still, you know, it's – to call it strange is to barely scrape the surface.
01:26:11.980So, what are – what are you – what do you make of this?
01:26:16.240That there's something non-human here, and it's been here for a long time, is my provisional conclusion.
01:26:22.480And, you know, the question is not – that people should ask is not, is there something here?
01:26:31.600You have to ask the question first, can there something be here?
01:26:36.560And the short answer is, of course there can, because the universe is 14 billion years old.
01:26:41.700You could have gotten from one side of the galaxy to the other in our galaxy in Elon Musk's Tesla if it were traveling at 10,000 miles an hour.
01:26:53.680But what got on in the first place doesn't mean the same thing as what gets off on the other side.
01:26:59.700So, yes, the short answer is something can be here.
01:27:04.920What it is, I'm not 100 percent sure, and I feel very uncomfortable with the sightings of biological beings.
01:27:12.760If only because they just look a little too much like us.
01:27:19.820And I just can't see from a genetics point of view how – why the human form is so – or even, you know, two legs and two arms is necessarily biologically the most, you know, successful shape.
01:27:37.120I think the data, the evidence of the hypothesis, there's more than enough evidence to say that it's worth investigating.
01:27:45.720So, I would ask my colleagues to just hold their, you know, hold their sarcasm for a while.
01:27:54.080Because how do you deny thousands of reports like this?
01:27:59.780And, you know, I don't want to sound conspiratorial, but, I mean, I did get a phone call from somebody representing the White House because I was talking about something that they felt was a little too on the edge.
01:28:14.760They said, you need to just shut up, Gary.
01:28:39.660But, no, I spent two days there on that.
01:28:43.020And we've briefed the European Parliament as well on it.
01:28:47.660And they're aware of what their own – some of their own military are talking about.
01:28:53.240So, that – I conclude that there's definitely something here.
01:28:57.820But I think the more interesting conclusion is if they are – if something is here, it's likely been here longer than humans have even been civilized.
01:29:09.100So, it really opens the question – and actually, it's something that I think Charles Fort actually said – is, you know, Earth is probably somebody else's property.
01:29:21.120Well, that's a hell of a place to end.
01:29:26.800For everybody watching and listening, we're going to continue our investigation on the narrative side and the political side behind the paywall at Daily Wire.
01:29:36.120And so, if you want to join us there for an additional half an hour, that would be good.