GARRY NOLAN Something Has Been here a Long time- Jordan Peterson-BONUS Presentation

Episode Transcript
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Speaker 1 (00:00):
Apartment of Pathology at Stanford.

Speaker 2 (00:02):
It's pretty obvious that you have a multitude of abilities
and a stellar track record. You started to become interested
in unidentified aerial phenomena.

Speaker 1 (00:13):
Somebody representing the CIA and an aerospace company showing up
in my office at Stanford, showed me their credentials and
said we need your help looking at patients who had
harm done to them, and then a small subset of
them said that they'd been in proximity to things that
you would call a UFO. I thought it was a
joke at the beginning.

Speaker 2 (00:33):
Let us know, if you would, what the hell you
think is going on?

Speaker 1 (00:37):
That there's something non human here and it's been here
for a long time. Well, I imagine it's put a
bit of a bump into your life. I mean, maybe
one that's mostly interesting, but still to call it strange
is to barely scrape the surface. If something is here,
it's likely been here longer than humans have even been civilized.

Speaker 2 (01:10):
Doctor Gary Nolan is an immunologist, academic, inventor, and biotech entrepreneur.
Serial biotech entrepreneur. He's a professor at Stanford University School
of Medicine and somewhat surprisingly a ufologist. We talked about
his career, his research interests, the rise of AI, and

(01:30):
his interest in unidentified aerial phenomena. So doctor Nolan Gary went,
before we get to the heart of the matter with
regards to your interest in unidentified aerial phenomena more commonly
known as UFOs, let's talk a little bit about you
so that we can situate you in the minds of

(01:53):
our readers. So you have a remarkable research background and
a technology background. Clue us in a bit and tell
us who you are.

Speaker 1 (02:05):
So I'm a professor in the Department of Pathology. I
hold the Ratchford and Carlotta A. Harris In Dowd Professorship,
and the major focus of my labs research, frankly, over
the last thirty years since I've been at Stanford has
been on the immune system and creating technologies that allow

(02:28):
us to collect more and more data about the immune
cells and or cancer cells that we're interested in. And
so that's led me from the development of retroviral techniques
for gene delivery and gene therapy. So all the retroviruses
and lentiviruses that are used in the world today for
gene therapy were developed based on a technique that I

(02:49):
came up with called the two nine three T cell technique,
and that's, frankly, that's old technology to me, but it
still generates a nice royalty. So and then from there
it's about measuring more and more what we call parameters
per sell, which are events that relate we think, to

(03:11):
the biology of the cells. And so we've created and
spun out I don't know, probably at least half a
dozen companies on that side of things alone. Lately, we've
been moving into artificial intelligence. We've started and spun out
two companies there. And now I'm actually moving into atomic
imaging because I sort of feel like that's the next

(03:33):
level down of information that I need to get at
to understand gene function. So we're I've raised the money
to create a whole new kind of instrument that can
measure things at the atomic level.

Speaker 2 (03:45):
Tell me about that a little bit. What I mean
that's electron microscope territory. You have a new technology that
you're I know, that's an old technology.

Speaker 1 (03:54):
Now it's a fusion of two technologies, something called a
atomic probe tomography and field on microscopy, and it's a
way to bring the two together because previously they couldn't
sort of exist in the same machine. So by bringing
them together, we can go another order of magnitude lower.

(04:14):
We can get down to what's called subankstrum, Like the
bond length between two atoms is in the subankstrum realm.
But this technology that we've developed not only can see
down at that level, but can also determine what kind
of bond structure where we have locally, and that has
a range of applications all the way from biology through

(04:35):
to metals, alloys, nanotechnology, et cetera. And actually the instrument
is already half built down at a lab in here
in Koopertino that we've set up. So we're excited about that.

Speaker 2 (04:47):
So how many companies have you started or been involved
in starting rocks?

Speaker 1 (04:53):
About a dozen and we've had about eight successful exits
so far. HM. One, that's pretty good.

Speaker 2 (05:02):
That's pretty good track record, all things considered, All things considered,
one complete failure, but that's okay, one failure out of
that many, isn't so that Yeah, Well, if you don't fail,
maybe you're not trying enough diverse things. I mean, that
seems to be particularly true on the entrepreneurial side. Right,
it's very difficult to invent something and then equally difficult

(05:23):
to make it profitable, or maybe perhaps more right. So
on the medical side, tell me a little bit more
about your research into viruses.

Speaker 1 (05:34):
So our research in the viruses was well, first of all,
the retroviruses. I got involved with HIV research back in
the day, and that was mostly trying to understand what
turned the virus on and off in the immune system.
So I was involved with what was called the cloning
and characterization of the what are called transcription factors that

(05:56):
turned the virus on and off. And I actually cloned
it in David Baltimore's lab at MIT when I was
a postdoc there. David won the Nobel Prize actually for
reverse transcript das very famous man, obviously, so but when
I came to Stanford and using the technologies that we developed,
we did everything from a bola research to Zeka to

(06:18):
whatever the current manifestation of whatever the plague was that
people were worried about. And we even actually saw the
first COVID lungs from unfortunately deceased patients. And that's what
really that actually scared the Jesus out of me when
I realized that we're dealing with something extremely serious with COVID,
at least in some people. But most of my research

(06:42):
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 or to disrupt the function
of the immune system. And so that required the development

(07:04):
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, because 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. So we're a computational lab as well as

(07:26):
a wet lab, as we call it. Do you have
an engineering background, No, But I've always been a tinkerer,
and 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

(07:47):
it is that you want, and being able to explain
it to them in a way that gets them interested.
And that talent frankly translates very well in the entrepreneurial
side of things. When you're talking to a venture capitalist,
you can convince them that the biology is interesting, that
it's doable, that here's the kind of people I need.

(08:09):
And I always use this term inevitable, that it's inevitable.
This is something that's coming. So it really is up
to the early bird that gets the worm. If 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.

(08:29):
Get to it first and own the market.

Speaker 2 (08:32):
And your degrees are what are you in? What areas
were your degrees awarded? All genetics. But one way to
think about genetics is genetics is actually programming. I'm actually
pretty good as a programmer as well, but genetics itself
is software, and so if you think about genetics as software,
it was very easy again for me to be both

(08:53):
a programmer and a geneticist at the same time. So
I've always been good at math, I've been good at
the I'm more, i would say good at the intuition
of how biology works. An intuition plays a larger part,
frankly in science than people would like to admit. Yeah,

(09:14):
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. It's so interesting because I've thought
about this for a long time. It really struck me
when I was first in graduate school, because when you

(09:36):
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.
And that's almost never the case. Usually what happens is
that people have an intuition that's derived from some recognition,

(10:01):
and then they backfill it and make it look like
it's algorithmic. And then the other thing that's so bloody
peculiar about that is that there's almost no discussion in
graduate school training. Maybe this was different where you went
on hypothesis generation itself. It's as if scientists swallow the
idea that you're creating your hypothesis in this algorithmic manner

(10:26):
as a consequence of grinding through the research. And now
I had a student at Harvard, Shelley Carson, who worked
on creativity, and she would make very large leaps in
with regard to her hypothesis, and then it would take
her a few months to backfill so that she could

(10:47):
bring people along to explain the justification. But that certainly
wasn't the method by which it was derived. You 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,

(11:09):
which is the trademarker for creativity, was actually slightly negatively
correlated with scientific productivity, at least at the graduate school
and then early career level. But you you've got a
very wide range of abilities, and then you've got this
both an entrepreneurial and a managerial twist. Is that a

(11:30):
fair characterization, because that's also a rare combination.

Speaker 1 (11:34):
I think what I mean, it's hard to talk about
yourself as if you'd not to sound like a narcissist.
But I think if you can marry creativity with practicality,
that's the magic mix, at least for me. Is I'm
very good at rapidly iterating all the possible reasons why

(11:58):
something can be the case and then rank ordering them.
Very quickly coming up with at least two cutoffs. One is, yeah,
this is possible, but it's very unlikely that magic dwarves
run the universe right everything below that level. But then
above that level there's two there's one more cutoff one

(12:18):
is possible but impractical or perhaps not easy to prove,
and then above that is the provable. And 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, or yeah, you
probably shouldn't do that, because here's the reasons why. There

(12:40):
are so many other things that it could be that
you can't prove or disprove, so let's not go down
that road. And it's because it's a rabbit hole. So
I think marrying creativity with practicality and being able to
see and frankly what I call reverse engineer of the future.
You know, it's it's like you can see what it

(13:01):
is and then you know, I need to do this first,
and then I need to do that. And once I've
done each of these steps, those are milestones that give
you confidence to take the next step. And 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. And when

(13:23):
did you start your first company? Soon after getting to Stanford?
Actually it was around nineteen ninety four, but I had
already learned a lot from my mentor, as Lenin Lee Herzenberg.
So I was lucky having come to Stanford to end
up in their lab. Because Lenin Lee, who were frankly hippies,

(13:45):
you know, they had the two of the three biggest
patents at Stanford. One was for something called the flow cytometer,
which brought in hundreds of millions of dollars, and perhaps
even more important were the monoclonal antibodies, what are called
humanized antibodies. So by making monoclonals that could be injected

(14:08):
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. And Lenn was just a natural,
a natural entrepreneur. He never started any companies, but he
knew how to license them. So he would always bring

(14:29):
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. So
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. And he introduced me to the
best patent attorneys of the day, and so I learned

(14:51):
from them what it was all about. So it was,
you know, much of what I would love to say
as mine is just a a rewrite of what I
learned from uh from Lenin Lee. Right, So you were
very favored in your mentoring. Yes, I got I got lucky,
but I was also well, that's a good deal. I

(15:12):
rotated in Stan Cohen's lab, and Stan, of course hadn't
had the Cohen Boyer patents, so Boyer her Boyer started Genentech.
Stan Cohen had the other of the three biggest and
they were all in the department of genetics, and those
were the uh those were the patents for genetic engineering.
So it was sort of an environment that led you

(15:36):
to think about practical applications. Now, when I started my
company as an assistant professor, I got a heck a
lot of pushback from senior scientists saying, Gary, you're too early,
You're you know, you're gonna you're you shouldn't dirty your
hands with this yet or now. Frankly, they didn't even

(15:58):
want me getting involved in all. And it was funny
because a lot of them, you know, ten or so
years later, we're back in my office asking for my
advice on how they could start a company. Right right, Well, it.

Speaker 2 (16:14):
It's a rarer pathway to be scientifically productive and to
make your talents manifested in multiple directions and to be
an entrepreneur. I mean, that's the research that I referred to,
looking at predictors of scientific productivity, showed that the best predictor,

(16:35):
apart from IQ obviously, which is always the best predictor
of virtually anything complex by a lot, was conscientiousness, right,
just sheer diligence, and that there's a certain kind of
narrow focus that goes along with conscientiousness too. And so
it is reasonable advice if you're talking to someone whose
primary talents are diligence and industriousness for them to focus

(16:59):
in ten on one area so that they can establish themselves.
But that obviously wasn't the appropriate pathway for you, and
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. So as generic advice,

(17:21):
it probably wasn't too bad, but it didn't seem to
hold in your case. How many patents do you have?
I think somewhere between fifty and sixty at this point,
ah and research articles over three hundred and fifty, right, okay, Well,
so for everybody watching and listening, I mean, obviously that's

(17:41):
a tremendous number of patents, because actually one patent is
a lot of patents, and so sixty is a tremendous number.
And 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.

(18:01):
So three hundred is roughly equivalent to one hundred PhDs,
and 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.
So the three publication rule of thumb isn't a bad one.
What do you think of that characterization? Yeah, I think

(18:22):
it's I think it's good.

Speaker 1 (18:23):
I think the better way to do it is how
often are you cited, so you can publish and never
be cited. So at this point I think I'm at
about eighty nine thousand something citations, so that puts you
in the top whatever percent. And a lot of those,
frankly with the retroviruses, because people use the retroviruss And

(18:48):
then a lot of it are the technologies that I've
developed because for the immune system measuring technologies, whether it's
something called sitof that I co developed with this guy
at the University of Toronto. His name was Scott Tanner.
He invented the machine, but I showed how it could
be used for immunology, or the codex or the maybe
or phospho flow or now the split pool synthesis technology

(19:13):
for single cell analysis. We're all things that sort of
just like came to me. It's amazing that sometimes 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.

(19:35):
But then you lay out in front of you all
of the necessary raw material and you say, somewhere in
this morass is the answer, and then at a lecture
out of nowhere, it suddenly just appears, you know, in
your head, fully formed. It's almost as if your subconscious
was busy working and it finally said, oh, I'm done here.

(19:59):
It is.

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Speaker 2 (21:15):
Yeah, well, your your your thoughts and revelations. Let's say
as well as your perceptions are extremely influenced by your goal.
And so if you set the right question, you establish
the quest, and your thoughts are orienting mechanisms. They're going

(21:35):
to be working on the pathway to that goal and
they do deliver the goods. Just like when you're walking
down the street and you orient towards a goal, you
can see the way to walk. I mean, it's an
analogous to that. And we're not shocked that our perceptions
are delivered to us. No, it's not like we effortfully

(21:59):
construct them. They make themselves manifest in our consciousness, and
if thought is a abstracted equivalent of perception, which is
at least one of the things it is, it's not
that surprising that once you set your mind to the
task that you're what would you say that the spirit

(22:19):
of revelation visits you in the appropriate manner. That's especially
true if it's a genuine question, you know, if you're
really interested in it. So, how could you describe your
typical day? Like how many hours a day do you work?
And how do you set.

Speaker 1 (22:37):
Up your day? I probably work fourteen fifteen hours a day.
I get up, I feed the dogs because they're very demanding.
I sit down, I start on email, and then I
look at my task list. And usually these days it's
a lot of editing. And luckily large language models have

(23:00):
come along and help with that. In fact, it's actually
almost fun to write grants. Now that's a you know, wow,
that's something to say. That's for sure, because I figured
out how to use large language models to write grants
and so now, and what's interesting is that you really
only need to give it like five or six sentences

(23:22):
of the basic idea the way I've constructed this large
language model version, and the rest of it gets automatically produced,
which is actually kind of sad because what it means
is the majority of it is wrote. The majority of
what we write is similar to what you were saying
about papers. The majority of that is wrote, and it's

(23:42):
just there for the convenience of the reviewer. But the
central idea is only a few sentences right right now?

Speaker 2 (23:51):
Do you have your own large language model and how
do you stop them from lying to you and producing
false like hallucinationations and citing papers that don't exist.

Speaker 1 (24:03):
And yeah, we you know, we use pretty sophisticated versions.
We don't have our own LLLM, 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 we have, we use open AI or anthropic
or Gemini, you name it. And then we have a

(24:24):
layer sitting on top.

Speaker 2 (24:26):
And oh yeah, and it is that layer trained on
your work, yes, or on relevant work. I see, I
have one of those as well that I trained on
my books and some other material that. Yeah, and it's
it's a very weird thing to use. I don't know
if you have the same experience, but in this system
we trained things like I think, but it can also

(24:49):
think up things that I haven't thought up, which is
not I guess what's happening as far as I'm concerned,
is that in the statistical encoding of my linguistic knowledge
is all sorts of latent information, right. I mean, there's
relationships in my patterns of thought that I haven't explored obviously,

(25:10):
and they're probably near infinite in scope. I mean, I
would say that's the case for everyone. But because there's
just so much information that's encoded, and 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, or it's I mean, it's in the context
window it starts with it. But I think the value

(25:34):
is because it has lowered barriers, which is really what
you're talking about. The barriers are lower to finding analogous
or metaphors of what it is that you've said in
other ways of thinking. I mean, much of my work,
the inventions that we've made, we're taking the metaphor approach

(25:54):
of finding somebody else's technology that works in something else
completely unrelated to biology, showing how it could be applied
to biology, Right, And so you know, ideas. Very often
the best ideas are saying, or the best teachers that
people are saying, this is something like this, think of
it like this, and then giving a metaphor or an

(26:15):
anecdote that explains the idea. And so the large language
models are just metaphors on steroids. Depending on how you
set the heat, it can find things for you and
solutions for you that you probably could have thought of it,
but it did the leg work.

Speaker 1 (26:35):
So for me, for instance, on the atomic imaging idea,
you know, I said, okay, well here's what I'm doing.
Help 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. But I said, I said,
find me five other ideas that might also do the

(26:57):
same thing. And surprisingly, it came up with ideas. They
were impractical, but it came up with ideas that were
that you know, we're like, oh, that's pretty cool. I
wish I knew about this area of physics, so you know,
it's actually there was a study just done out of
Stanford just last fall that showed that large language models

(27:18):
can be as creative as humans, if not more creative
as scored by humans, just less practical.

Speaker 2 (27:28):
I wonder what the bound is on practical, Like, do
you suppose I've talked to some computer engineers, including my
brother in law who's quite a genius, and 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

(27:52):
multiple levels of resolution, and can do this remarkable thinking
for lack of a better word, because it sure looks
a lot like thinking to me. But you know, human beings,
we seem to be able to do that with images
as well, right, and also with movement, like embodied movement.
And my guess is is the practicality constraint is probably

(28:15):
something like the referencing of the semantic system to the
domain of image and movement.

Speaker 1 (28:22):
Right, will this.

Speaker 2 (28:23):
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 And humans have three different memory
systems at least, right, we've got semantic and episodic and procedural,
and my suspicions are that when we're looking for practicality

(28:44):
that we assess the joint contributions of all of those
different ways of representing information. And the large language models
can't quite do that yet, but they will soon. I mean,
it's got to be the case, right because someone like
Elon Musk, for example, he has this immense purpose of
real world data, and it's got to just be a
matter of time before that's integrated with the large language models.

Speaker 1 (29:07):
Right. Well, actually, you know, there's a part of your
brain that does a lot about what you're talking about.
It's called the basil ganglia and the caud eight pertainment,
which is actually where intuition happens. So there's a game,
a Japanese game of chess, which is sort of a
limited form of what we think of as chess, and

(29:27):
so they were doing basically reads of people's brains while
they made these moves, and especially when they made like
what would be considered a genius move, and the area
of the brain that lights up is the head of
the caud eight and the patainment, which is so the
basil ganglia is actually what part of the brain tells

(29:49):
you where your body is in three D space, what
your memories are, et cetera. It's all subconscious, subservient to
your executive function. So when you make a decision to
do something, that gets sent to the basil ganglia, which
determines whether or not you can actually do it and
whether you want to do it, Like if you're walking
across a room, how do I walk? All those subconscious

(30:12):
decisions are all done in the basil ganglia. But as
it turns out, as humans have evolved, that has then
been sort of taken over to be used as our
decision making system. Our intuition system works through the basil ganglia.
So all those ideas that you just talked about, where
it actually finally comes to is this practical or not?

(30:36):
The basil ganglia is part of that process of central
place for that process. So is that an embodiment constraint? Essentially? Sorry,
what do you mean by that? Well, some things you
can act, Oh, oh yes, can't. Yeah, but it also yeah,
it also appears to be used in the abstract sense now,

(31:00):
like is this the right move to make in a
chess game? Which is which is kind of abstract reasoning,
And we actually did right, right, We did a study
on it. I mean, I believe it or not. We
came to this area of the brain because of some
of my UAP stuff, and we did a study with

(31:21):
a group at Harvard and found in fact that the
size of this area of the brain correlated directly with intelligence.
And so oh really, yeah, which which part exactly was that?
The that was the caught eight? Yeah, but we were
how high was the correlation? Do you remember? You know

(31:42):
the magnitude? I can't. I can't remember. But we have
three papers, three papers on it we published. So it's
interesting stuff. When were they published in the last three
or four years? Oh?

Speaker 2 (31:54):
Yeah, okay, so I've come across those are very interested
in the neurological determinants of intelligence.

Speaker 1 (32:00):
But there was a there was a guy in literally
I think the year two thousand, 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. He's now at UCLA. He's a professor
of neurology. There had proposed that the caut eight and

(32:26):
the basil ganglia were going to be involved in intuition.
I didn't read his whole paper on it, but he
was already a postulate when he was like a post doc.

Speaker 2 (32:34):
I wonder what the what do you think the connection is?
I mean, when you think of intuition, you tend to think,
at least I tend to think of of pattern recognition.
Let's say, what what do you suppose the connection is
between pattern recognition and and and the caud eight and
and it's and it's and it's relationship to to motoric movement.

Speaker 1 (32:56):
It's a it's making a decision with sparse data. 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, and it's the movement.

Speaker 2 (33:14):
But you know in the military, right, So that's that's
that's having to well, I'm imagining someone on a playing field,
you know, in a hockey game or a soccer field.
Obviously they're tracking many moving objects simultaneously and abstracting out
something like a meaningful pattern, right, which direction is this going?
And then they're modulating their reactions in consequence of reading

(33:38):
the field. And the great athletes, the great team athletes
are particularly good at that. Wayne Gretzky was particularly good
at that, and hockey and so and so. Okay, so
the pattern recognition would be something like you can imagine
that being also crucial in a hunt, right, because you're
going to want to know where the animal is gonna go,
and and with your pack you have to orchestrate your

(34:01):
movements and you have to do that together. There's something
almost musical about that, like lions can do that and
pack animals and so oh yeah, I see that. And
that would be focused on a goal, the hunting arrangement,
and that would require extremely fast reflexes. So it's the
intuition in that regard is a very complex form of
reflex in the sense, yes exactly.

Speaker 1 (34:23):
So it's humans seem to have evolved a way to
use a pre existing system in the basil ganglia that
was really just there for motor movement and making subconscious decisions,
and they've layered over it and put an abstraction layer
on top of that so that we can now use
it for mathematical principles and other ideas. It is what

(34:46):
provides that aha moment. And I've learned actually to see
when the aha moment comes, it's almost like a form
of color. It's like, and the next time you get
an AHA moment, you see if you can try to
capture that it happened when it happens, and realize that

(35:10):
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. And 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

(35:34):
you know 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. So listening
to those Aha moments, and I'm telling you, I see
it as a color when it happens, I recognize it
as a different kind of thought. It's not thing it's

(35:55):
being given to me magically or anything like that. I
know a lot of people would like to think that
that's what it.

Speaker 2 (35:59):
Is, but I don't know. There's something kind of magical
about it. It like thought has this revelatory quality. As
you pointed out, you can set your sights on something
and then the pathway there. The mechanism that delivers you
there is delivered to you, you know.

Speaker 1 (36:17):
So there is a magic about it. You know.

Speaker 2 (36:19):
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. That I've been studying Old Testament
literature a lot for a long time, and I'm interested.
I'm bringing this up because of something you said about
the Basil Ganglia too developing an abstraction layer.

Speaker 3 (36:41):
You know.

Speaker 2 (36:41):
Part of that abstraction layer is no doubt our ability
to tell stories, because stories are verbal representations of action patterns,
and so so the burning Bush episode in Exodus, that's
an intuition episode.

Speaker 3 (36:59):
You know.

Speaker 2 (36:59):
And Moses takes his intuition seriously enough to deviate from
the from the from his normative path, and then he
delves deeply into the source of the intuition. And that's
what transforms him into a leader.

Speaker 1 (37:15):
Right.

Speaker 2 (37:15):
He gets to the bottom of something, down a rabbit hole,
to the bottom of something.

Speaker 1 (37:19):
And so it is a It is a It is.

Speaker 2 (37:21):
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, So okay, so we should
switch topics here. I wanted to go over your background
with you to establish for everybody listening who you are.

(37:45):
And it's pretty obvious that you have a multitude of
abilities and a stellar track record that's continuing, and so
that sets the foundation for our next discussion. You started
to become interested, and I would like to know the
story in unidentified aerial phenomena, and that's definitely a lateral

(38:10):
move from your other interests, and so I'm very curious
about all of that. I guess what I'd like to
start with is why the interest and why take the
risk to pursue it as well, because you have a
lot to lose, let's say, on the reputational front, and
it's clear you're a very creative person, so I'm sure
your interests go everywhere.

Speaker 1 (38:32):
But i'd tell us how.

Speaker 2 (38:35):
It is that you became interested in this and why
you decided to pursue it with some degree of seriousness. So,
I mean, there's a couple of origin stories to it,
but I think the most the easiest to start with
is with the Atacama mummy, right, the small mummy that
people had been promoting as being an alien, right the

(38:58):
mummy that was found in out of Comma, Chile, And.

Speaker 1 (39:02):
Right, that was a couple of years ago, way not
too long ago. Oh, actually was no, it was twelve beer,
it was twelve yeah, yeah, actually already. Yeah, it was
a long long time ago. I mean that was. And
so I had seen it on YouTube. I reached out
to the people who were, let's say, marketing it, and
I said, hey, I can figure this out for you.

(39:22):
I can tell you what it is. And so we
arranged to get a small piece of the of the body,
a rib. I wanted the rib because I wanted the
bone marrow from within the rib, because I felt that
would be the place best protected from a bacterial contamination.
And long and the short of it was that we

(39:43):
showed that it was a human baby, probably well it
was probably pre term birth, but that we found a
number of mutations in it, the in the genome that
could explain what it looked like and why it looked
up the way it did. And so, you know, when
a movie came out regarding that circa twenty twelve or so,

(40:06):
it was like sending up a you know, a flair
to two sides of the world. One the people who
didn't like that I was debunking the alien so I was.
I became an instant a symbol of dislike for the
UFO community, which is interesting, you know, paradoxically these days.

(40:31):
But 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 called
them as they as he sees it. And so that led,
as it turned out, to somebody representing the CIA and
an aerospace company showing up at my office at Stanford

(40:53):
literally unannounced, showed me their credentials and said we need
your help looking at patients who had harm done to them.
And I was like, well, what kind of harm? And
then they laid out the data literally like MRIs and
X rays of internal scarring.

Speaker 2 (41:13):
Of what were these these people who reported abductions?

Speaker 1 (41:17):
No, no, no, oh no, oh sorry, okay, these were
more for the wrong tangent. These are intelligence agents, diplomatic,
core military personnel, et cetera, all who who had said
that they were hearing buzzing in their ears or you know.
And and then a small subset of them said that
they'd been in proximity to things that you would call

(41:40):
a UFO. So 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 after the Autacama
mummy escapade, and and so they had come to me,

(42:01):
I mean, why come to me? Well, one, I was
willing to talk to people about this stuff, but two,
they wanted to do blood analysis of the individuals who'd
been harmed as part of a complete medical workup. And
so they'd asked around and they said, well, who does
the best blood analysis or you need to go talk
to this guy nol And at Stanford. He has this

(42:22):
thing called sitop that can do the deepest analysis of
blood that you know currently today and still so 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.
I'm sure you've heard of Havanas syndrome. So the review

(42:45):
that for everyone, So Havana syndrome was something that basically
came out around twenty fifteen twenty sixteen, and it was
a it was called Havana because it was the diplomatic
core individuals in our government who were getting headaches or
having to be sent home. And it turned out that

(43:07):
it is probably a kind of microwave technology being used
by some of our adversaries. It's one hundred percent reeal.
You know, some people in the CIA tried to debunk it.
But now there's whole there's a whole like set of
paperwork out put out by the Department of Health and
Human Services on anomalists what's now called anomalist health incidents

(43:29):
where Havana syndrome and all of the sets of associated
symptoms are all listed and 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. But you know, in the three years.

Speaker 2 (43:48):
Heay, so let me get this straight. So you had
someone from the CIA show up to your office and
he had a list of people who were who had
medical problems, and some of those medical problems were a
consequence of people coming into contact with contact with what
technology that that is mysterious?

Speaker 1 (44:11):
Is that the right thing? Yeah? Yeah, well, I mean
they didn't know what the what the source of it is,
but now we know that there was. Basically, I mean
it's it's an energy weapon, just a microwave weapon. Just
imagine you could focus the beam of your microwave in
a very narrow path towards a person's head. You'll bake
the brain cells in their head. So, I mean, there's

(44:32):
nothing magical about it. We have them. Everybody knows that
they that these things exist. At the time when we
were working on it, we were calling it into interference syndrome.
You call something a syndrome when you don't know the
exact cause, but it can have a variety of manifestations.
And so what we had done was we had matched
the symptoms to what are called the international diagnostic codes,

(44:56):
so that we had the ability to say, it's this,
and it's this, and it's this, and if you have
ten of fifteen of these, you have interference syndrome. So
at the same time, somebody was figuring out what Havana
syndrome was, and it turned out that our set of
symptomologies matched perfectly with the Havana syndrome ones for most

(45:16):
of our patients. We were able to hand all of
that over to the US government and I've worked with
Senate staff and others you know, on that, and that's
something I can't talk much about. But what remained, and
this is what's good about how science has done. Once
you've characterized something and you find it uninteresting, not that

(45:37):
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. What
was left on the table were the oddities, and those
were the Now the people who had gotten close to UAP,
they claimed at least some of them, and they had,

(45:57):
as it turned out, slightly different demologies. Some of those
were more likely to have arhythmas or uh you know,
scarring on the skin as opposed to internally or manifestations
on there on the back of their neck of some
kind of irradiative damage of some kind. Now there, then

(46:19):
there was a pattern to this, Yes there was, yes, well,
And the pattern was always anecdotal, unfortunately in that they
had a story that you at face face, but.

Speaker 2 (46:29):
I mean a symptom. The symptom pattern was stable. And
how many people, how many individuals approximately? Like what kind
of sample pool were you were you assessing?

Speaker 1 (46:38):
Now you're down to about five or six people because
of of the original small number of people. Of the
original hundred that we started with, ninety or so it
turned out were what we could think of as Havana syndrome.
The remaining were what we're interesting and you know, but
sort of back to let's say, my career. My career
has always been I've always been good at seeing the

(47:04):
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, and not just you know, going with
what's sitting on the line, but understanding why the data
point off the curve is important, and then being able

(47:26):
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.
And so that was where I was already starting to
get introduced because of this UAP stuff. Because of that,

(47:50):
we had these groups of individuals who said that they'd
gotten harmed by UAP, and we diligenced them to make
sure that they didn't have some sort of psychological problem.
They had full psychological workups, and we knew that these
were people that we're you know, we're trusting the nation's
security with. You know, it's kind of like, okay, well

(48:13):
it's an anecdote, it's a story. And now I've heard
fifty stories like this by that point, right, And it's like, well.

Speaker 2 (48:22):
No, they say, the plural of anecdote isn't data, but
the plural of anecdote is definitely hypothesis, yes, right.

Speaker 1 (48:28):
And so once you start to get that, I was like, okay,
well there seems to be something here. And you raised
a point. You ruined your career. I literally was told
by a senior official at the National Cancer Institute by
around circa twenty fourteen, twenty fifteen, because I was just
talking about this, just saying, isn't this an interesting idea?

(48:49):
You're going to ruin your career? Gary? And I was
just like, but it's but the data is on the table.
It isn't ridiculous to ask the question. But the fact
that they were trying to push it off the table
incensed me. It was just like, that's not how a
scientist thinks. That is just your And I said to him,

(49:13):
I said, you sound more like a priest than a scientist.
Maybe you should give your PhD back.

Speaker 2 (49:19):
Oh and well, there aren't that many scientists, you know,
there are a lot of people who act out the
role of scientists.

Speaker 1 (49:25):
But that's not the same thing.

Speaker 2 (49:27):
Yeah, right, Scientists are very peculiar people when they're real,
so so.

Speaker 1 (49:32):
And that, you know, And that's been sort of my
approach to it, is like, how dare you tell me?
I can't ask the question because there's more than enough
evidence that there's something worth studying. And people mix up
evidence with proof. You know, data sits in isolation and

(49:52):
has no meaning whatsoever. It only has meaning in the
context of a hypothesis. And you know, so does the
does the hypothesis and the data match to mean that
it is perhaps evidence? Evidence, just as in court, is
not proof of anything that requires a jury to decide
whether or not the evidence is sufficient to you know,

(50:14):
manifest guilt or not. The same thing in a paper.
There's very few papers that you will ever read that
ever say there is in at least in biology, this
is a conclusion. There's all kinds of weasel words that
we as biologists use to give ourselves diplomatic egress just
in case. So, but you know when people like Nilda

(50:36):
grass Tyson say there's no evidence, Well, that's just a
lack of understanding of what the difference between data and
evidence is. There's reams of evidence, there's libraries full of evidence,
there's books I could throw, I could drown people in
that with evidence. But that's not a conclusion. That's not

(50:59):
what we think of as scientists as proof. Now I have,
I'm of personally two minds as far as I'm concerned.
There's definitely something going on that appears to be not human.
That's just my own So okay, but that's different than science, right,
I'm true, right, right, right, go for it.

Speaker 2 (51:21):
Okay, 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 anomalists,
Like what were they reporting? And then you took it
seriously because there had been psychological workups done on them,

(51:42):
and there were a number of people reporting the same thing,
So you know that something's up. So tell me, tell
me a story and then tell me what you started
thinking about with regards to a potential cause.

Speaker 1 (51:55):
Well, one was a guy by the name of John
Burrow and the Randall Schrum forest case where he literally
got close to one that came down near our nuclear
storage facilities there. It's a very famous case. And he
came to me as part of this group of ten

(52:20):
remainders and I was introduced to him to do the
blood analysis and do the collection of the blood. And
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

(52:41):
he could get he could prove or that it might
have actually been originally caused at Randalstrum in England because
his medical file was deemed top secret. So we literally
had to go to and this is on the record.
We literally had to go to Senator McCain in whose
state this guy lived in Arizona and get him to

(53:05):
write a letter to the Veterans Administration forcing them to
open his file so that he could get insurance payment
for his heart condition. It's all on the record. So
why there's 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

(53:26):
top secret? What's in it? There was nothing in it. Frankly,
it was just somebody had decided it needed to be
top secret because things, things related to UFOs just need
to be you know, nobody talks about them, rush them
under the table, but we you know, we literally and
it's again it's public record. And so what did he experience?

(53:47):
He saw something, He came close to something, something that
was about five feet across on the ground, and I
don't know, I mean, I wasn't there. I'm just relaying
the story.

Speaker 2 (53:58):
Right, right, right, And so is that what's the typical
pattern of encounter?

Speaker 1 (54:03):
You know, I mean, is there a pattern of now phenomena? No, No,
there's not enough of a This is the problem is
that you can't repeat harm. You know, when when harm happens,
it's it's sort of incidental, and so you just have
to deal with And I think it's less about the harm.
So I mean, I think we should move away from
a discussion of the harm and just talk more about

(54:28):
what it is that people are seeing. And I'm talking
about credible people, right, what's the credible data that we
can collect? What's okay?

Speaker 2 (54:38):
So it's a broader conversation on unidentified aerial phenomena. That's
so so sure, Leat, and I want to talk about
your soul foundation as well, and also the fact that
you've analyzed materials with unusual properties, so right, if we
can tangle all that together, that will be good.

Speaker 1 (54:59):
Yeah. So the reason why we started the Sole Foundation,
and it was me, Peter Scayfish, and David Grosh. David
Grosh was the gentleman who testified in front of Congress
about what he claims were the reverse engineering programs, and
the principal reason for starting the Sole Foundation was to enable, say,

(55:19):
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,
to be able to say, here's a hypothesis and here's
the data I have. Do you think my hypothesis matches
or do you have another idea? But the spectrum of

(55:43):
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, so we have Peter Scayfish,
who's an anthropologist, and are the one well he's an
let's call him an anthropologist and so he's interested in

(56:05):
people's stories, Right, what are so called experiencers, what's the
pattern of the of the experiencers, and what kind of
let's say, trauma might they undergo, not 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 because of

(56:27):
the stigmas associated with talking about this and not wanting
to be, you know, considered crazy. Uh. And then so
he's collecting and writing papers on that. We have focused
on religion. We had somebody from the Catholic hierarchy write
a paper on that for us. Two on the on

(56:49):
the more you know, extreme science side, the hard science side,
the materials analysis that that I do. Uh. And part
of it again was to say, okay, let's have this conversation.
Let's We had our first Foundation meeting, I mean big
convention at Stanford where we had about two hundred or

(57:13):
three hundred people there who'd come from all over the
world to have a What year was that? That was
three years ago? Now who we've had one each year.
And 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,

(57:36):
and I was like, oh God, you can't do this
to me. Everybody's invited, the plane tickets are paid for,
you know, etc. What's going on? And I managed to
trace down who it was at Stanford that was sort
of causing the trouble. It turns out it was the
branding office at Stanford and that they had a problem
with that Stanford's name wasn't first. That we had put

(58:00):
Soul Foundation first and not Stanford, and they wanted it Stanford,
you know, and the Nolan Laboratory, not the Soul Foundation.
So Stanford was more than willing to you know, to
be upfront about it. They were, you know, open about it.
In fact, the alumni association had me give at the

(58:20):
last homecoming a big talk to probably about two hundred
people about it because of the interest level. So there
was there's been no problem on that front. But then
I then got interested in the materials because again through
the connections that I had made, I came to know

(58:42):
a gentleman by the name of Jacques Valet. Jacques Valat
is probably one of the most famous let's call them ufologists. Ever,
in terms of like his scientific prowess, he was involved
in the early days of the internet. He was an astronomer.
He's a venture capitalist in the Bay Area, and he's
heretical in the sense that he didn't believe that whatever

(59:06):
this was was necessarily extraterrestrial, but it was. It was
some other kind of manifestation of either the human psyche
or something more beyond, something almost you know, paranormal in
its in its capabilities. So it was interesting to listen

(59:30):
to this, but I was more interested in, you know, okay, well,
what can I teach another scientist? How can I convince
another scientist. So it turns out Jacques had a number
of materials, metals and or objects that had been associated
with landings of alleged uap or UFOs, and so I said, okay,

(59:54):
well give me some of them. I need only tiny
amounts and we can do traditional analysis on it. And
so one of the things that I got ahold of
we showed recently to be that was from a beach
in Ubatuba, Brazil, that a fisherman had seen this object

(01:00:17):
dropped from some other from this ufo and 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, and we measured
it and it was ninety nine point nine nine nine
percent silicon. Okay, that's not hard to make today, but

(01:00:41):
it's not something in the late nineteen fifties or early
nineteen sixties you drop giant pieces of all over a
beach in Ubatuba, Mexico. So it's whatever that was, it
was clearly an object of industrial purpose. Right, There's no

(01:01:04):
ninety nine point nine nine nine percent silicon anywhere on
planet Earth. It's all contaminated. And I actually have atomic
I have an atomic map of one of these pieces
that we developed that we did with atomic probe tomography.
What was fascinating was that one of the two chains
of custody that I obtained also had magnesium ratios that

(01:01:29):
were not what you would expect from Earth. They were
different than the standard magnesium ratio. So magnesium has three
isotopes twenty four, twenty five and twenty six twenty four
is like, let's just say rounded up to eighty percent,
and the other two are nine and eleven percent. Whereas

(01:01:54):
the one of the two chains of custody. The magnesium
ratios were or just higglely piggledy all over the map.
They had nothing. They didn't look anything like what you
expect to find from a piece of silicon on Earth.
Anywhere you look on Earth, you're going to find silicon. Sorry,
the magnesium at the eighty eleven and nine ratio. Whereas

(01:02:20):
this one of these pieces was wrong. That doesn't prove
that it's a UFO. It just proves that it's of
some kind of manufacturing purpose. So that's one we're actually
writing the paper up on that one. I published a
peer reviewed paper on another thing, another object from what's

(01:02:46):
called Council Bluffs, Iowa, where again there were multiple witnesses.
In this case, even the police had seen an object
and it seemed to drop something, and when the people
arrived they thought, actually it was a plane crash. When
they arrived, they found about thirty pounds of malten metal
in the middle of a frozen field. And I have

(01:03:09):
the original polaroids, and so I just did an analysis
of it. And 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. It was not fully mixed. It was
only partially mixed. So it's kind of like if you
were to take chocolate, vanilla and strawberry ice cream and

(01:03:32):
partially melt them and just kind of turn it your
spoon a couple of times around. Depending on where you looked,
you'd find different ratios of chocolate, vanilla and strawberry, as
opposed if you were to put it in a blender,
everywhere you look it would look the same. So what
I found in the metals was that it was incompletely mixed. Okay,
So who would drop thirty pounds of incompletely mixed iron,

(01:03:57):
titanium and aluminum in the middle of a field for
no good reason from something that looks like a UFO.
So all the conventional explanations that it was thermite, it's
not thermite because there's no aluminium hydroxide and I checked,
you know, to carry that much malten metal requires at

(01:04:18):
that temperature a cauldron that it would be like half
a ton to the middle of a field. You're not
going to put it in a plane. So what is it? Unexplained?
But the reason for doing it, and actually i've there's
somebody who's uh, it looks like is going to give
me sort of free money to analyze more of these things.

(01:04:40):
Is not to prove that they're from UAP, but it's
to do the right kind of analysis on the materials
so that I can get it out there and publish
it with no conclusions. Just here's the data, and here's
the story, and here's the analysis as complete as we
can do at this time, because maybe somebody else will

(01:05:00):
look at it three years from now, or some other
enterprising student will go, ah, that's how you would if
if you released this, this would be the engine control
for I don't know, anti gravity or something. So it's
it's you know, you you it. It's part of that

(01:05:21):
thing of like you come up with an intuitive idea
because you've spread all of the data in front of you. Well,
if you don't have the data, you can't come up
with the with the solution. But if I can get
the data out to as many people, maybe somebody else
will come up with the hypothesis that unifies the story.
So it's part of like the I mean, I think

(01:05:41):
of it as the open source data approach or the
open science where you get the data out for everybody
because somebody paid for it, So maybe you shouldn't keep
it in your you know, in your desktop drawer or
these days and a folder on your computer. Get the
data out there so that other people can use it.

(01:06:01):
Does that make sense?

Speaker 2 (01:06:02):
Okay, so so far it makes sense. I've got more questions.
So you started by assessing the medical problems of a
small subset of people whose symptoms didn't fit the pattern,
but whose self reported stories had it their own characteristic
and that their symptoms had their own identifiable characteristics. Now

(01:06:27):
I'm not sure how you got from that to the
Soul Foundation. Now, my understanding is that because you had
worked on that that hypothetical alien corpse and debunked that,
and then you got involved with this CIE project, that
more of these stories were coming your way.

Speaker 1 (01:06:49):
Yes, is that? And yes? Okay?

Speaker 2 (01:06:51):
And so what other kinds of stories? And tell us
about the foundation itself and who's involved? And then I'm
also extremely curious about your conclusions. I mean, I'm sitting
here thinking you're obviously studying anomalous phenomena. Why would you
make the why or have you even derived the inference

(01:07:15):
that apart from the the isotopes, why would you derive
the conclusion that extraterrestrial origin is the most likely.

Speaker 1 (01:07:25):
No, I never said that, culprit or.

Speaker 2 (01:07:27):
No, okay, fine, fine, fair enough, fair enough, you didn't,
and so that well, that's exactly why I'm posing the question.

Speaker 1 (01:07:32):
I'm not trying to corner you yet.

Speaker 2 (01:07:34):
I want to know, like, you're studying anomalous phenomena, you
know of Charles forty? Yeah, yeah, yes, okay, okay, okay.

Speaker 1 (01:07:44):
Did you ever watch Magnolia? No, the movie?

Speaker 2 (01:07:48):
No, Oh, Magnolia is a great movie, by the way,
and it's about Charles It has a sub theme of
Charles Fort. So if you're interested in Charles Fort, Magnolia
is very much much worth watching. It's a great movie,
also beautifully put together musically. And of course Charles Fort
studied anomalist phenomena his whole life, and Magnolia happens to.

Speaker 1 (01:08:09):
Be about that.

Speaker 2 (01:08:10):
But okay, so you're studying anomalies, lay out the realm
of hypotheses because there's military experimentation, I mean, there's all
sorts of obvious competing hypotheses. So tell me what you did,
you know, what you've gone through, more about your foundation
and what you've concluded. So the principal reason for starting

(01:08:31):
the Soul Foundation was that I was because of let's say,
my public persona about this, more and more scientists were
coming to me and saying, hey, I want to help, how.

Speaker 1 (01:08:46):
Can I do it? And then it a common friend
of Peter and Peter Skayfish and I along with David Grush,
who I had met through all of these events. And
David again was the guy who sat in front of
Congress and testified about the alleged reverse engineering programs of
which he was aware. And I met with Dave and

(01:09:07):
spoken with him, you know, very deeply and watched every
element of his body language as I possibly could to see,
you know, look for evidence of being of misconstruing him
in some way, and as far as I can tell,
he's telling at least as far as he's concerned, the
truth about what he knows. And I said, okay, well,

(01:09:29):
we need a more formalized way to approach this. And
so what do you do as a scientist in a
new area. You start a society more or less, or
you start a foundation that becomes the lead foundation for
other groups to come together. And the Soul Foundation pretty
much has established itself as a non partisan umbrella group

(01:09:54):
through which the many individuals who are interested in UAP
and talking about you know, in a professional manner, can
come together in our next actually event, it's going to
be historic. It's going to be in Italy, and we've
got people from the European Parliament. We've got a number
of former, let's say, US officials who will be there

(01:10:19):
to talk about these matters. And again it's I don't
expect a revelation. I expect just from this people to
come and know that there's a place where they won't
be laughed at, but they can share, maybe give ideas.
And one of the sets of ideas of what's going

(01:10:41):
on right now is there's a big movement for what's
called the UAP Disclosure Act that for your listeners, for
the last two years, Senator Rounds and Senator Schumer, supported
by multiple representatives on both sides of the aisle, have
put forward a part of the bill that goes into

(01:11:04):
the Defense Department bill, sixty pages of which talks about
the reverse engineering programs and extraterrestrial or not necessary not
even extra trust grow non human intelligence, and that for
the next five to ten years there will be an
oversight group which will collect and gather all of this

(01:11:25):
information for potential benefit of humanity. Now you just asked
me about ruining my career. Would Senator Schumer, the head
of the Democratic Party, and Senator Rounds, an important figure
on the Republican side, come out and make any of

(01:11:46):
these kinds of statements or allow for their offices to
be the vehicles through which such a bill would manifest
itself if they felt that they were going to be
derided on the floor of the Center. Probably not. And
so there's Marco Rubio has come out openly and talked

(01:12:08):
about this. He's now our Secretary of State. There's twenty
minutes of part of a film that he's in where
he's openly talking about the fact that there are these
objects moving in ways that we don't know. I was
speaking with your producer prior to your getting to the set.

(01:12:28):
The Soul Foundation. One of our purposes we put together
press kits of like fifteen different snippets from former heads
of the CIA, THEDIA, NSA, President Obama, etc. All saying
there's something that we don't understand, and it's moving in
ways in our atmosphere that we can't explain, and it

(01:12:50):
appears to be technology. Now they'd like you to think
that it's some thing out of Lockheed perhaps, but you
know it was. These things were being seen before Lockheed existed, right,
They were seen in World War Two. They were seen
subsequent to World War Two, long before we had any capabilities.
So what is it. I don't care. I don't care

(01:13:14):
if it's human or not. I just want to have
reproducible findings. And yet somehow, for some reason, the government
won't release the information that it has. I mean, just
recently there's a there was a Freedom of Information Act
release of the so called mosil orb ou m O

(01:13:34):
s u L Mossel Iraq and a solid silver ball.
That ARROW, the which is the Anomaly Resolution Office of
the Department of Defense, came up and said, yeah, we've
see lots of these things. The former assistant director of ARROW,

(01:13:55):
which is the office programmed and set up up by
the DUD to collect the kind of information around these anomalies,
openly stated just three weeks ago on a podcast that yeah,
we see, we've seen multi We have videos of these
black triangles that move in ways that we don't understand. Okay,

(01:14:19):
if it's our technology and we can move in ways
like that. Why are planes still crashing at Reagan Airport right? What?
Why are we letting you know airplanes use fuel when
we have some other kind of technology that can move
the way that these things can and as being kept

(01:14:41):
a secret?

Speaker 2 (01:14:41):
Is that just forget you talked about black black triangles
and silver orbs. Can you go into a little bit
more like what I'd like to know that the central phenomena,
What where do you think most of the signal resides
with regard to these anomalous sightings? What's the pattern?

Speaker 1 (01:14:59):
The pattern, the the best pattern are what it is
that the military sees. And those are the ones that
where I have a focus and where actually I'm involved
with another group that's funded privately called Skywatcher, And what
we're doing is we've been setting up sensor systems in

(01:15:21):
what we call cleared areas where we know that there's
no overflight and we do sometimes work in concert with
the FAA and others to make sure where we're setting
up for repeatable measurements and sensor systems to see things,
and we're seeing stuff that doesn't make sense, and so
we're not coming to conclusions, but we're collecting the data

(01:15:44):
and because I'm a scientist, I'm like their principal advisor
to this group, and we're setting up and doing the
kinds of measurements that I think are necessary because I'm
not going to wait for the government, you know, I'm
not going to wait for daddy government to tell me
what's right. I'm going to I'm a scientist, going to
go out and do it myself. And so that's what

(01:16:05):
we've done, and we've raised significant funds. I mean, and
you can go look up Skywatcher on the Internet and
what it is that we're doing. And part of what
we're doing is it's it's it's two purposes. One, it's
it's basically aerial surveillance, partially just for drones because we've
seen what drones can do in wars. So and we

(01:16:25):
knew and you know about the drone incidents in New Jersey,
right and all of the hubbub that that caused. Well,
we were actually there, we were actually measuring things. What
was that? What was that Some of them were simply drones.
Some of them, though, were moving in ways that would
be hard to explain by drones. But all the stuff

(01:16:46):
that we observed close to shore was clearly human activity.
But so we're setting up we're setting up Skywatcher as
sort of a dual purpose. One is to work with
the government to hopefully or defense contractors or anybody who
wants to pay for our services to collect aerial data

(01:17:10):
basically as rapidly as possible, because often you can't deploy
the necessary equipment on site quickly enough to collect the
data when there's an anomaly that shows up. I mean,
our principal goal is protection of the United States, but
if in so doing we happen to collect other information

(01:17:31):
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, and 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 fifty one they

(01:17:55):
have something that does that, it's good for, i think,
arry 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. You want to know this
because if you ignore it, you could be ignoring the

(01:18:18):
data point off the line that is important to know
about always back to that. Don't ignore the anomalies because
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.

Speaker 2 (01:18:38):
Right right, right, Yes, So so tell me, tell me
about the patterns of anomalists activity that characterize that defines
something as an unidentified aerial phenomena, and then tell me
what you've concluded as a consequence of your of your

(01:19:01):
investigations and where you Yeah, let's do that.

Speaker 1 (01:19:05):
So there are let's say five characteristics of something that
you would think of as an anomaly. One is instantaneous
acceleration and deceleration. Right, There's very few things that we
know of that can go from zero to five thousand
miles an hour and then stop on a dime without
squishing everybody on the inside, you know, sending them through

(01:19:28):
the windshield. So when you see these things go from
in the case of the I think it was the
Nimitz or the Eisenhower, goes from sea level to space
in less than a second. And they have the radar
trackings of those things. And now imagine the size of
the object. Let's say it's it weighs a ton. To

(01:19:50):
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. Okay,
so where did you get that energy? First of all,
so instantaneous acceleration and deceleration. So seeing things that do

(01:20:12):
zigzags across the sky, it means that somebody or something
has control. If it's going fast enough and it's not
doing an arc, it means something has control of momentum
and inertia. They can negate momentum and inertia. So that's
an observation seen hundreds, if not thousands of times by

(01:20:35):
pilots all over the world. So what does that mean
about our understanding of physics? First of all, so that's
one thing. The other is no apparent flight services and
no apparent exhaust so no energy output. So you're you're
moving and doing these things, and yet if you look
at them on with flur, which is a kind of infrared,

(01:20:57):
you don't see any hotspots. If you were to look
at a jet, all you would see is the plume
from the jet. So no flight surface is meaning you know,
basically Bernoulli's principle is not at play here, right, which
is basically how the wings work and lift. So Bernoulli's

(01:21:19):
principle is not at play. So you're moving without a
flight surface and without an apparent mode of inertia. You're
not putting something out so that you can move forward.
And then the other one is what you would think
of is what's called trans medium travel, meaning something that

(01:21:42):
can go from the water to the air and then
back again, or to the air and to space. We
have nothing that can do something like that. Recently, there
have now been drones made and talked about openly, and
actually these are US drones just shown on a I

(01:22:02):
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. But that's only
been developed in the last few years, not something from
fifty sixty years ago. So those are the kinds of
things that people see. And again it's you know, you
ask me what I think of as real that those

(01:22:27):
anecdotes are to me stories and why I get interested
in the medical or the material side, is it's something
I can repeat. I can't repeat these pilot observations, but
I can repeat experiments on materials or experiments on experiments

(01:22:47):
on human but reading the humans who have been harmed. Now,
the thing about Skywatcher is is that we at least
in a limited sense, have a signal that can be
released that sometimes it seems to attract these objects. And

(01:23:08):
so that's where the repeatability attempt is coming in. Explain
that a bit more so. There's 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 Skywasher

(01:23:29):
had determined when he was working with the military, not
as it wasn't his purpose to develop it, so we
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

(01:23:52):
that he can release that somehow seems to have these
things objects show up, and I was there when it happened.
We go out on these these week long events in
like the middle of nowhere, and stuff shows up and

(01:24:13):
you know, some of it's been on, some of it's
you know, you can go find it on Twitter, but
the stuff that's on Twitter isn't good enough in my opinion,
I'm more interested in the data that we're more recently
collecting with better cameras and better sensor systems, because the
idea is just to do the science.

Speaker 2 (01:24:32):
So 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 hypotheses
you're nursing. And then on the daily wire side for

(01:24:54):
everybody watching and listening, I'd like to ask you more
about stories about what you've said, for example, when you've
been on these SkyWatch expeditions and what the SkyWatch program
is reporting. And then also to delve a bit more
into the political you talked about the Shumer and I

(01:25:17):
don't remember the other senator rounds this bipartisan proposal to
declassify and make public some of the information narratives of
sightings from pilots in particular. Okay, 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

(01:25:38):
additional half an hour to 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.

Speaker 1 (01:25:49):
On and what this has done, what this has done
to you too.

Speaker 2 (01:25:54):
I mean, this has got to kind of come out
of left field, so to speak, in a severe way.
So I imagine it's put a bit of a bump
into your life. I mean, maybe one that's mostly interesting,
but still, you know, it's to call it strange is
to barely scrape the surface. So what are what are you?
What do you make of this?

Speaker 1 (01:26:14):
That there's something non human here and it's been here
for a long time is my provisional conclusion. And you know,
the question is not that people should ask, is not
is there something here? You have to ask the question first,
can there something be here? And the short answer is,

(01:26:36):
of course there can, because the universe is fourteen billion
years old. You 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 ten thousand miles
an hour, right, But what got on in the first
place doesn't mean the same thing as what gets off

(01:26:56):
on the other side. So yes, the short answer is
something can be here. What it is, I'm not one
hundred percent sure, And I feel very uncomfortable with the
sightings of biological beings, if only because they they just

(01:27:16):
look a little too much like us. And 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. So I think there's something here. I think
the data, the evidence of the hypothesis, there's more than

(01:27:41):
enough evidence to say that it's worth investigating. So I
would ask my colleagues to just hold their you know,
hold their sarcasm for a while, because how do you
deny thousands of reports like this? And you know, I
don't want to sound conspiratorial, but I mean I did

(01:28:03):
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. They said, you need
to just shut up, Gary. I mean, I'm just telling you.
I mean, I've I've I've briefed Canadian Parliament. I went

(01:28:24):
to your parliament in Toronto and I briefed all three
parties on it. I don't even the only ones who
didn't want to hear anything were the separatists, so interestingly,
but no, I spent two days there on that, and
we've briefed the European Parliament as well on it, and

(01:28:46):
they're aware of what their own some of their own
military are talking about. So that I conclude that there's
definitely something here. But 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. So

(01:29:08):
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.

Speaker 2 (01:29:21):
Well, that's a hell of a place to end. So
I think we will end there for everybody watching and listening.
We're going to continue our investigation on the narrative side
and the political side behind the paywall at Daily Wired.
So if you want to join us there for an
additional half an hour, that would be good. Thank you
very much, doctor Nolan.

Speaker 1 (01:29:40):
That was.

Speaker 2 (01:29:44):
Interesting, to say the least. It's very difficult to know
what to make of it. Obviously, you have an incredibly
credible background and a very wide ranging mind, and it's
very fascinating to see your reaction to this set of

(01:30:04):
circumstances that have come your way, and thank you for
sharing it.

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