#2372 - Garry Nolan

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Garry Nolan

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Garry Nolan, PhD, is an immunologist and professor at Stanford University School of Medicine. He is also a business executive and Executive Director of the Board of the Sol Foundation, a research and advocacy center focused on UAP studies.  www.thesolfoundation.org

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Timestamps

0:00Garry Nolan’s cancer immunology work: how tumors evade immunity and the tools to measure immune complexity
9:57Tracing cancer evolution & personalized medicine; sun/UV risk and future gene-editing fixes
20:11Cancer risk, early detection, and how cancer develops (CT scans vs MRI; personal melanoma/kidney cancer; evolutionary 'broken contracts' model)

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Transcript

0:00

Joe Rogan podcast, check it out.

0:03

The Joe Rogan Experience.

0:05

Train by day, Joe Rogan podcast by night, all day.

0:09

Derek, very nice to meet you, sir.

0:13

Nice to meet you as well.

0:14

Thank you for doing this. I really appreciate it.

0:16

Tell everybody what you do.

0:18

Tell everybody what your official position is.

0:20

You're a professor at the School of Medicine at Stanford.

0:24

What do you do?

0:25

So my day job is in cancer research and cancer biology, mostly immunology and

0:31

cancer.

0:32

Much of what my laboratory does is not so much the biology of cancer,

0:37

but developing instruments that create the data that allow us to analyze the

0:42

complexities of how the immune system interfaces with tumors

0:45

and how tumors basically re-enable the immune system to help the cancer itself.

0:54

So the problem has been we don't have the ability to collect enough data, or

0:58

not until recently, to collect and understand what all of that means.

1:02

So we've been kind of poking in the dark for decades.

1:06

And so probably for the last 20 years, I've developed a number of instruments

1:10

and turned them into companies

1:11

that allow everybody to access a level of information they couldn't get before.

1:16

So explain that, the immune system allows the tumors?

1:22

So what happens is that there's sort of a dance between the mutations that

1:29

initiate a tumor

1:31

and then sort of an evolution of how the tumor eventually learns how to trick

1:37

the immune system to not recognize it.

1:40

So we have all kinds of, I mean, literally every day, every person, you'll

1:46

develop five cancer-like objects inside of your body.

1:50

But the immune system and your body has a way of shutting it down very quickly.

1:54

But with enough time and with enough variation, tumors will eventually evolve

2:00

in a way that trick the immune system,

2:02

not only to not recognize them, but in fact to help them and feed them in a way,

2:07

to create an inflammatory environment that actually then the tumor uses to

2:11

propagate its own cell division and then metastasis.

2:15

So it's a normal function of natural human biology to create tumors?

2:20

It's not so much a normal function.

2:22

It's a byproduct of what evolution is, that when the genes mutate, when a cell

2:28

divides,

2:29

or if you go out and, you know, stand in the sun too much, for instance,

2:33

you get skin cancers because you're getting ionizing radiation that's changing

2:37

the DNA, making a mutation.

2:39

And some of those random mutations will initiate a cancer.

2:43

So, for instance, I have a mutation called MIDFE318K.

2:48

It's a mutation that I was born with.

2:51

It wasn't in my family.

2:52

And it causes both melanoma and kidney cancer, which I've had both.

2:57

I've had a dozen melanomas alone.

3:00

You know, we didn't find that out until a couple of years ago, but I've been

3:04

following it over the years.

3:06

And we basically figured out, okay, it's going to have to be this.

3:09

So, we had my genome sequenced.

3:10

But that's just one of hundreds of different kinds of mutations that can occur

3:16

that are on a path towards creating a cancer.

3:20

But the cancer can't survive if the immune system recognizes it.

3:25

So, eventually, what happens is there's this detente that is reached between

3:29

the immune system and the cancer,

3:31

where the immune system basically ignores the cancer.

3:35

So, Jim Allison here in Houston won the Nobel Prize back in 2018 for

3:40

understanding one of these turnoff signals that the immune system,

3:45

that the cancers use to turn off the immune system, and that by showing he

3:50

could block it,

3:51

his wife, Pam Sharma, ran a bunch of clinical trials at MD Anderson that showed,

3:55

in fact,

3:55

that this could actually turn a 5% survival disease in melanoma to a 50%

4:01

survival.

4:03

And that then created the whole immunotherapy field that the world is taking

4:08

advantage of today.

4:09

Wow.

4:10

So, what is cancer actually doing?

4:15

Like, how do tumors develop this ability to trick the immune system?

4:20

Is this something that other animals have?

4:23

Oh, yeah.

4:23

Oh, yeah.

4:24

So, it's a constant battle.

4:25

It's a constant battle.

4:26

So, for instance, there are proteins on your cell's surface, and we'll get too

4:31

immunologically deep about it.

4:33

They're called major histocompatibility complex proteins.

4:37

So, for instance, if I were to try to just randomly do a tissue transplant from

4:41

me to you, it's very likely that it would be rejected.

4:44

And it's because of those MHC proteins that it's rejected.

4:48

What's happening is that your cells are presenting your internal cell biology

4:54

to the immune system, and it's saying,

4:56

okay, you're a friend, not a foe.

4:59

So, when cancer usually initiates, there are disruptions that happen, and

5:04

proteins are made incorrectly, et cetera.

5:07

And so, what these MHC proteins are doing, in some cases, is they're presenting

5:12

the internal damage to the body,

5:14

and the body's saying, oh, there's something wrong with this cell.

5:16

We better wipe it out.

5:17

We kill it.

5:18

These same proteins are what the immune system uses, for instance, to go after

5:23

viruses.

5:23

So, when you get a virus infection inside of the cell, the body has a way of

5:28

chopping those proteins up inside of the cell,

5:30

presenting it via MHC, and then the immune system attacks it.

5:34

So, one of the first things that actually tumors do is they learn to turn off

5:39

the MHC proteins inside of themselves.

5:41

So, the ability to show that I'm damaged is shut down.

5:46

And so, the immune system doesn't go on full alert for that.

5:50

But then there are other mutations, like divide when you're not supposed to,

5:53

you know, avoid this kind of induced cell death called apoptosis, and not

5:59

others.

6:00

And so, cancer doesn't just like start, and then the next day, you've got it.

6:04

It's a progression of events.

6:06

You have these precancerous lesions.

6:08

You have like a benign tumor, which eventually becomes a metastatic tumor.

6:15

And so, but the immune system is key at every stage of the development, because

6:21

if you can reactivate the immune system in just the right way,

6:24

then you can prevent the cancer from basically spreading or from metastasizing

6:30

or from killing you, essentially.

6:34

Is there a potential for, given the understanding of this, is there a potential

6:40

for using this for organ transplant patients where locally would stop

6:45

recognizing this as a foreign organ?

6:49

That's exactly what is done.

6:52

In fact, you, when you get a tissue transplant or an organ transplant, you're

6:56

suppressing the immune system.

6:58

The problem with that suppression is that you then put yourself at risk of

7:03

cancer, because what you're doing is you're turning off the immune system's

7:08

ability to combat and go after a cancer the moment it forms.

7:12

So, most people who are under immune suppression are at risk both of, let's say,

7:16

virus infections, bacterial infections, but also for their cancers.

7:21

So, would the potential be to turn that off locally so you could turn that off

7:26

on the specific organ?

7:28

That would be a great thing to do if we could.

7:31

Right now, the only things that we have are systemic.

7:35

So, yeah, I mean, for instance, if you could deliver to the organ that you're

7:40

transplanting anti-immunosupp, you know, basically immunosuppressives locally,

7:45

that would be great.

7:46

We don't have that yet, but that would be via a form of gene therapy.

7:50

But the problem would that be that if you, like, let's say you had a lung

7:53

transplant, if you had a lung infection, it would be catastrophic.

7:57

Do you want to come work in my lab?

7:59

You're accepted as a graduate student in the Stanford Department of Pathology.

8:04

Wow, that was easy.

8:05

Yeah.

8:06

I have a few friends that have had organ transplants.

8:10

Yeah.

8:11

And it's, you know, it's very disturbing knowing that they're so vulnerable to

8:15

any kind of infection because of these medications that they have to take in

8:18

order for their body to accept a transplant.

8:20

So, one of the problems is that there are literally hundreds of different types

8:25

of immune cells, and, you know, really until recently and, frankly, until a

8:30

technology my lab developed about over a dozen years ago, we couldn't look at

8:34

all of the immune cell types all at once in a single picture.

8:38

So, I came from a laboratory, Lennon-Lee Herzenberg, and I was a grad student

8:43

at Stanford, and they had developed an instrument called the fluorescence-activated

8:48

cell sorter.

8:48

And that allowed you to look at three proteins at a time, and if you could know

8:52

ahead of time what the cell types were that expressed the proteins that you're

8:56

interested in, you could look at just those three cell types.

9:00

Then I came up with a way to look at, you know, 50 or 60 proteins at a time,

9:05

sort of stepping up what they had already taught me how to do.

9:08

And then suddenly that gave us the ability to look at nearly every cell type in

9:13

the body, an immune cell types.

9:15

And then that gave us the, let's say, the raw data to build mathematical models

9:20

that we could do better predictions of what outcomes would be.

9:23

And how is that, like, what are you applying in terms of, like, real-world

9:28

scenarios? How are you applying this?

9:30

Well, so, for instance, there's a kind of leukemia called AML, acute myelogenous

9:37

leukemia. It starts in the bone marrow.

9:39

And it is a distorted version of a myeloid cell type. It starts as a stem cell,

9:48

and that stem cell goes down a number of different paths.

9:52

And depending upon the person, the disease is sufficiently different that it

9:57

might follow a slightly different path towards what becomes the disease itself.

10:02

And so, being able to trace the path and to know which steps along the way that

10:08

it takes to become what becomes then the metastatic leukemia could only be

10:16

accomplished by having enough markers that allowed us to trace everybody along

10:21

the path.

10:21

It's kind of like, if I wanted to follow you from who you are as an egg through

10:26

development through to who you are today, and I had snapshots every month.

10:32

I need different markers to measure what you are as an egg versus what you are

10:37

as a baby versus what you are as an adult.

10:40

And so, each of those different markers in my world would be different proteins

10:46

that tell me something about an adult leukemia versus a baby leukemia.

10:50

And then we use something called pseudotime, which is a mathematical concept

10:54

that allows us to stitch together those photographs.

10:57

I could take a random box of photos of you from an egg to who you are today,

11:01

and I could just by hand put together the most likely path and sequence of what

11:06

you were from the earliest to the latest.

11:08

But we needed the data and we needed the means and the instruments to collect

11:12

that information so that then the math could come to play.

11:15

That's such a fascinating thing about human beings is the biological

11:21

variability.

11:22

Is that everybody is, we're so the same, two lungs, a heart, but so different

11:29

in how our body reacts to things and what happens to us and environmental

11:36

factors, diet, stress, all sorts of different factors.

11:40

And you're kind of piecing together this puzzle of all these things.

11:47

And, but what you're doing is you still have to pay homage to the fact that

11:51

those differences exist.

11:52

And so, while, you know, my cancer might be the same class of, let's say, melanoma

11:59

as another person's, the complexity of what allowed that cancer to become are

12:05

so different that the drugs that would work for me might not work for another

12:10

person.

12:10

And so, that's what basically requires us to personalize the medications in a

12:17

way that gives the right drug to the right person.

12:22

So, I've started probably half a dozen companies and sold them, places like Roche,

12:27

et cetera.

12:27

Actually, my most recent company we sold to 10X Genomics, which enables us,

12:33

enables them now, because of a patent I created back in 2011, to scale up the

12:38

amount of information that we can collect at a time that then when layered on

12:43

top of what, for instance, 10X Genomics already did, which is doing what's

12:46

called single cell genomic analysis.

12:49

We could scale that up a hundred fold to get a hundred fold amount of

12:54

information.

12:55

But the problem with that is that I can collect all that data and make an

13:01

analysis of a cancer for you, but it might be a little bit different than

13:06

another person.

13:07

So, what we have to do then is develop techniques that allow us to narrow in on

13:12

what the differences might be, so that when I develop a drug for person X, it

13:18

works for person X and not for person Y, right, the right way.

13:21

So, there's a lot of personalization in medicine that is required.

13:27

The diversity that makes humanity great and that makes humanity able to survive

13:33

in the face of so many challenges is that there are individual differences that

13:38

one person might survive and another won't.

13:41

It's the same thing with cancers.

13:44

And it's the same thing with drugs.

13:45

I mean, you know, for instance, with certain drugs, one of the first things I

13:50

learned in pharmacology when I was, you know, way back in the day is that there's

13:56

always a benefit to damage ratio that you're having to deal with, that a drug

14:00

has a positive outcome, but there are side effects.

14:03

And so, as scientists or as clinicians, we make a choice based on the

14:08

statistics, who will benefit the most, and will it benefit the most, but by the

14:13

way, there's all these side effects that might affect you.

14:17

And, you know, overall, globally, 60% of people will survive, but since I don't

14:24

know anything more about your specific disease, I am, by law, required to give

14:30

you the 60% drug.

14:32

Until I know or can distinguish that your disease is a different subclass than

14:38

the 60%.

14:39

And that's, in fact, a lot of what pharmaceutical companies are doing is they're

14:45

trying to marry a diagnostic to the disease itself, the disease subtype itself.

14:49

So that if you can show that 90% of the people of this kind of subclass will

14:55

survive, you have to, by law, choose that diagnostic to make sure that the

15:00

person doesn't have the subclass before you give them the 60% drug.

15:05

Does that make sense?

15:06

Yes.

15:07

Yeah, it does.

15:08

The narrative has always been over the, you know, last few decades, stay out of

15:13

the sun.

15:13

Mm-hmm.

15:14

But recently, people have started saying, no, it's actually, you need to become

15:20

accustomed to the sun, and the real issue is people using sunscreen all the

15:24

time and then going out and getting burned.

15:26

Obviously, your situation is very different because you have a specific gene.

15:31

Yeah.

15:32

And I'm Irish.

15:33

Yeah.

15:34

That's the problem, right?

15:35

Yeah.

15:36

The genes of the people that lived in cloudy-ass places for hundreds of

15:40

thousands of years.

15:41

Right, exactly.

15:42

And my mother, when we were kids, I mean, I'm 64 years old, so when I was a kid,

15:47

you know, we'd go to the beach in Connecticut, and they'd smother me in, you

15:50

know, coconut oil.

15:51

Oh, yeah.

15:52

Right.

15:53

Yeah, baby oil when I was a kid.

15:54

Yeah.

15:55

Everybody had baby oil, and everybody got barbecued.

15:56

Yeah.

15:57

Plus, I worked in the, you know, in the fields as a kid for, you know, farm

16:01

labor.

16:01

And that's not good.

16:02

That wasn't good.

16:03

The burning, that's the real damage to the skin, and then it manifests itself

16:07

as cancer far later in life, right?

16:08

Right, right.

16:09

Yeah.

16:10

There's all these subtle, let's call them smoldering mutations that are waiting

16:16

for a second or a third hit to occur.

16:18

Right.

16:19

Or for, you know, instance, you get old enough so that your immune system is

16:24

kind of going wonky, and it no longer is able to take care of something that 20

16:28

years ago it would have been able to heal.

16:29

Right.

16:30

Healed perfectly well.

16:31

That makes sense.

16:32

So is there any, this narrative that you need to be in the sun more, and that

16:38

just don't get burned, is that reality?

16:41

Well, it depends on who, I mean, for someone like me, no.

16:45

But there are positives, obviously, for the sun.

16:47

I mean, vitamin D, as an example.

16:50

But they're also, you know, resetting your clock in the morning rather than

16:54

taking melatonin at night.

16:55

Go and just, you know, use glass to shield out the ultraviolet and get some

17:02

bright light.

17:03

It's the UV that's the danger.

17:04

It's not light.

17:06

So, for you, you don't ever just go sit in the sun?

17:11

Not anymore.

17:12

No, but I was...

17:13

Because of the melanoma.

17:14

Because I was an idiot when I was a kid.

17:15

I mean, I would go use tanning beds.

17:17

Yeah.

17:18

Because I thought, well, I wanted to look, you know, tan.

17:20

Right.

17:21

And I did tan back then.

17:22

But, you know, obviously can't anymore.

17:24

Yeah, you don't really see those anymore, do you?

17:27

No.

17:28

You do.

17:29

Maybe in like Seattle.

17:30

Some people do.

17:31

Yeah, there's, you know, I mean, I think there's obviously there's a benefit to

17:35

light.

17:35

I mean, I'm not saying don't go out and do it.

17:37

And, you know, I think as well, there'll come a day, and I was just talking

17:42

with some friends

17:43

of mine at dinner last night, is, you know, maybe with things like CRISPR, I

17:49

could rub a

17:50

CRISPR ointment on my body, it would fix the single point mutation in my skin.

17:56

And then I could enjoy the sun again.

17:58

Is that really potentially down the pipe?

18:00

Oh, yeah.

18:01

I think...

18:02

Oh, yeah.

18:03

No, I think we're...

18:04

How far away are we?

18:05

I think, honestly, I mean, people always say five years is sort of like this

18:07

horizon.

18:07

But, no, I really, I mean, I know people who are already developing systems for

18:13

delivering genes,

18:13

you know, RNA to cell.

18:15

I know that's a dirty word in some, but there are formulations of RNA that

18:19

probably won't

18:20

be as problematic as some of the things that maybe the COVID vaccine might have

18:25

done.

18:25

Right.

18:26

Yeah.

18:27

RNA right now, you say, and people clench.

18:29

Yes, exactly.

18:30

Yeah.

18:31

Yeah.

18:32

But, I mean, your cells are full of RNA.

18:34

Right.

18:35

So, I mean, you can't get away from the fact that your cells are full of RNA.

18:38

It's just the messenger RNA.

18:39

Yeah.

18:40

Yeah.

18:41

But it's also the means by which they delivered it.

18:42

Mm-hmm.

18:43

Right?

18:44

I mean, the means by which it was delivered was a formulation of a nucleotide

18:49

that by itself

18:51

was meant to be something called an adjuvant.

18:53

An adjuvant is something which activates the immune system you want.

18:56

I mean, when you get a vaccination, you are co-injected with something that

19:01

hyperactivates

19:02

the immune system to say, "Come hither."

19:04

Right.

19:05

And most of the pain that you get from an injection is not the vaccine itself.

19:09

It's the adjuvant.

19:10

Right.

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20:11

And so the problem with this was that it turned your whole body into like a

20:16

spike protein

20:17

factory.

20:18

Yeah.

20:19

Well, at least locally.

20:20

Yeah.

20:21

Yeah.

20:22

No, I've read some of the work.

20:23

But not always locally, right?

20:24

Because they didn't aspirate with a lot of people?

20:28

Yeah.

20:29

Yeah.

20:30

I don't think they aspirated with anybody.

20:32

They didn't with the president on TV.

20:34

But if you get infected by a virus, it's over your whole body anyway.

20:39

Right.

20:40

So it's whether the spike protein itself was problematic.

20:43

And so, you know, I know I'll annoy somebody one side or the other by saying

20:50

anything around

20:51

this area and I'm not here to cause any controversy.

20:54

But, you know, your immune system works.

20:58

But if you can trick your immune system into getting ahead of the game, then

21:04

that's a good

21:04

thing.

21:05

The question is back to this cost benefit ratio.

21:09

Is the benefit to the larger statistical population worth it knowing that some

21:15

people are going to

21:16

be hurt by it or not?

21:18

That's the question.

21:19

So, for instance, you know, back to cancer and vaccines, there's a number of

21:24

cancer vaccines

21:26

that are coming down the pike that for people like me would be, I mean, given

21:31

that I get

21:31

something chopped off of me four times a year.

21:33

Really?

21:34

Oh, yeah.

21:35

You should see me.

21:36

I look like I've been in a war zone.

21:38

You know, some people say, oh, that's hot.

21:40

And that's the only thing that's hot.

21:43

Wow.

21:44

Someone's into cutters?

21:45

Yeah.

21:46

Exactly.

21:47

Exactly.

21:48

So that's so fascinating.

21:50

But is there another way that could potentially deal with those things other

21:55

than cutting

21:55

them off?

21:56

Or is that the only way to remove it from your system?

21:58

Right now, it has to be cut off.

21:59

So the issue is that once the melanoma, once these lesions are on your skin,

22:08

they will expand?

22:09

Yes.

22:10

Luckily, most of mine are what have been called surface spreading.

22:13

Although one of mine was what's called a nodal, which basically dives right in.

22:16

And believe it or not, my dog found it and was sniffing at it on my arm.

22:19

Really?

22:20

And like started like scratching at it and it stopped bleeding.

22:23

You know, I'll show you the scar.

22:24

What kind of dog do you have?

22:25

Well, this was 15 years ago.

22:27

He was a Pomeranian.

22:29

But, you know, you can see the scar there.

22:31

Oh, that's crazy.

22:32

And it wouldn't stop bleeding.

22:34

And so, you know, I went in and had it looked at.

22:37

And they said another week and it would have metastasized.

22:39

Yeah.

22:40

Wow.

22:41

Yeah.

22:42

What a great dog.

22:43

He was great.

22:44

Yeah, he was great.

22:45

But, you know, there are, so for instance, if you can catch most of these

22:52

cancers early,

22:54

then that's what's important.

22:55

So I think probably one of the most important, let's say, changes to our

22:58

medical system that

22:59

could be initiated would be, frankly, the use of things like MRI, not CT scans,

23:04

because

23:04

CT scans are known to cause cancer.

23:06

Which is so crazy.

23:07

Yeah.

23:08

Like, when did we figure that out?

23:10

I mean, there was like a big study just published recently that said, here's

23:14

what happens

23:15

to people once CT scans were implemented and you see this sudden spike in the...

23:21

Oh.

23:22

I mean, again, it's this cost-benefit ratio.

23:25

If you didn't have it, certain people wouldn't have, you know, wouldn't know

23:30

that they have

23:30

a giant tumor in there.

23:31

Right.

23:32

I mean, so for instance, I had, when I had kidney cancer, I was actually at a

23:36

restaurant

23:36

with friends doing a business deal actually.

23:38

And I went to the bathroom and it was blood.

23:40

And I said, okay, we got to go to the, you know, we got to go to the, you know,

23:44

to the

23:44

emergency room like now.

23:45

And then they did a CT scan and they see this, the brachial tree around my

23:50

kidney was just

23:51

a big diffuse mess.

23:52

And they came in and said, you've got, you've got cancer.

23:56

Did you have to have your kidney removed?

23:58

Yeah.

23:59

Yeah.

24:00

Yeah.

24:01

It was, you know, it's okay.

24:02

I'm alive.

24:03

Nice to have two of them.

24:04

Yes, exactly.

24:05

I'm alive.

24:06

But, you know, it is, this early detection is important.

24:11

I mean, I was lucky that it hadn't metastasized yet.

24:14

It's called, it was called clear cell, renal cell carcinoma.

24:19

But, you know, so surveying the body and these companies that are out there

24:26

right now, which

24:27

do it, I think are really important because even if you are young and you have

24:32

no suspicion

24:33

you're going to have cancer, having that baseline against which you can compare

24:39

later changes

24:40

is important because I could do, for instance, a CT scan or an MRI of you.

24:45

And I find lots of little anomalies.

24:47

And they're generally in the field called phantomas.

24:51

There are these objects that may be worrisome, but we won't know that they're

24:57

worrisome.

24:57

And certainly I could do a biopsy of them and, you know, poke a needle into

25:02

your chest.

25:02

To pick out a piece of it.

25:05

But if I come back six months and it's changed, then maybe it's something we

25:11

need to go after,

25:11

you know, more seriously.

25:12

So getting those kinds of regular scans, I think, is probably one of the more

25:17

important things

25:19

that could be done, but not by a CT scan.

25:21

Which is crazy because we're doing them for so long.

25:24

Yeah.

25:25

Do they still do CT scans, though?

25:27

Because it's necessary.

25:28

It's necessary for certain things.

25:29

Right.

25:30

Which is letting people know this might cause cancer.

25:34

It's just like, yikes.

25:35

Yeah.

25:36

But maybe, for instance, there'd be a way to treat someone with a drug ahead of

25:43

time that

25:43

would minimize the effect of the CT scan.

25:46

Right?

25:47

So that, you know, because the CT scans are generally causing oxidative damage.

25:52

And so if you could provide a local antioxidant, and I'm not saying that

25:56

something like this

25:56

exists.

25:57

Right.

25:58

That's a bit of a naive statement.

26:01

But if you could do that locally to the area that's being imaged or to the

26:06

whole body,

26:06

then maybe CT scans could be lessened in their problematic outcomes.

26:11

I would say innovative and hopeful.

26:13

Okay.

26:14

Yes.

26:15

With naive.

26:16

Yeah.

26:17

I don't think it's naive because you're recognizing the issue.

26:18

Right.

26:19

Thank you.

26:20

So, well, this was also a problem with x-rays, right?

26:22

Oh, yeah.

26:23

Like x-ray technicians.

26:24

Yeah.

26:25

Like, I've seen some of those images of people's hands because the technician

26:28

used to have to

26:29

use their own hand to check to make sure that the x-ray was functional.

26:33

Right.

26:34

And over the years, they go, "Hey, what the fuck is wrong with my hand?"

26:36

And then they realize, "Oh, boy."

26:38

Right.

26:39

Yeah.

26:40

Well, it's interesting because what's happening with x-rays or CT scans is a

26:44

fast forward of

26:45

the kind of random damage that causes cancer in the first place.

26:48

And so because it's random, let me kind of go back a little bit as to why does

26:54

cancer happen

26:55

in the first place.

26:56

So let's go way back in evolution to the first time that there were single

27:01

cells versus the

27:01

first time that two cells met each other and said it was better to join forces

27:06

and cooperate

27:07

rather than to divide at each other's expense.

27:10

So in the process of that happening, those two cells came together or three or

27:15

four cells,

27:15

they basically said, "Together we're better than alone."

27:18

But there were actually social compacts and contracts that at the genetic level

27:23

were being

27:23

formed between all of these cells.

27:25

And so as things got more and more complex, more and more complex contracts

27:30

were formed

27:31

to the point at which what could happen is that any one of the breaking of a

27:36

complex contract

27:37

could actually then initiate a cascade that becomes cancer.

27:41

So rather than we thinking of cancer as being a forward progression in

27:47

evolution, it's actually

27:48

another way to think about it is that it's a devolution back to the core fire

27:54

of the desire to divide.

27:56

And so by breaking the contracts, by breaking the controls on the system,

28:01

cancer is allowed to blossom.

28:05

So the problem is that every tissue type, whether your lung or brain or

28:11

whatever, has a whole

28:12

different ecosystem of contracts that have been formed.

28:16

And so there's no one-size-fits-all drug that will kill off all cancers because

28:22

the contracts are different.

28:23

It's not like you can bring in a lawyer and fix, you know, agricultural

28:27

contracts versus maritime or whatever.

28:30

Yeah.

28:31

So that's the, you know, you have to have a flexible enough mindset because if

28:37

you get stuck in this,

28:37

it's a forward evolution as opposed to that it's a breaking of contracts.

28:41

You might miss out on an opportunity for how to develop a therapy or a drug

28:49

that would help people.

28:51

One of the things that I wanted to ask you, I don't even know if you know

28:55

anything about this,

28:56

but is there a connection between IVF and the amount of, because you have to

29:04

take some pretty extreme hormones.

29:06

There's a lot of stuff that women have to take.

29:08

Is there a connection between that and hormonal related tumors?

29:12

I honestly don't know.

29:14

So I don't want to opine and have half my colleagues send me emails tomorrow

29:19

scolding me.

29:19

Okay, good.

29:20

Well, I'm glad you answered that way.

29:22

I was told by someone who I really trust that there is.

29:26

And then we tried to Google it and it said there's not, but that's not

29:30

surprising.

29:30

Probably there hasn't been the right kind of study yet.

29:33

And if there is not, there should be.

29:37

I mean, certainly any hormonal imbalance is not a good thing.

29:41

I mean, you imbalance the metabolism of the system and you can.

29:44

Right.

29:45

I mean, so for instance, back to my specific disease with mid-F, there's all

29:51

kinds of things

29:52

like N-acetylcysteine, betaine, all these other drugs that are out there for

29:59

longevity.

30:00

Well, if I look into the metabolism of what my cancer is, every single one of

30:05

those is a disaster for me.

30:06

It accelerates.

30:07

Yeah.

30:08

Yeah.

30:09

Not good.

30:10

Not good.

30:11

So, because there's all these feedback mechanisms.

30:13

Right.

30:14

I mean, you know, people often say, you know, scientists are not religious.

30:19

There's nothing that inspires more awe in me than knowing the complexity of the

30:27

cell and knowing the complexity of life.

30:29

Right.

30:30

And seeing all this feedback and mechanism and knowing that underneath that is

30:34

a universe with particles, et cetera, that enabled something like us to exist.

30:38

I just sit in awe of that.

30:41

Well, yeah, it's awe-inspiring for sure.

30:44

I mean, anybody who doesn't think it is is not paying attention or they're

30:48

purposely being ignorant.

30:49

Right.

30:50

Yeah.

30:51

Well, you get a lot of that though.

30:52

Oh, yeah.

30:53

Well, that's okay.

30:54

You know, teachers are here to hopefully teach and not preach.

30:57

Hopefully.

30:58

Yeah.

30:59

Because of your specific type of cancer and your situation, like, do you have

31:04

to like very closely monitor your diet?

31:06

I probably shouldn't eat as much meat as I do.

31:10

Meat?

31:11

Yeah.

31:12

Well, because, you know, fats and a lot of them, the fats dissolve a fair

31:18

number of toxins.

31:19

You know, it's not necessarily a good thing.

31:23

I mean, that's been relatively well shown that too much meat as opposed to, I'm

31:28

not advocating vegetarianism.

31:30

I think there's a happy medium.

31:31

Mm-hmm.

31:31

I mean, we grew up in an environment where we had both.

31:34

I mean, we're omnivores.

31:35

Mm-hmm.

31:36

And we succeeded, I think, because we're omnivores as a society, as a, you know,

31:42

as a civilization.

31:43

So, but, you know, charred meat, for instance.

31:47

That's the issue though, isn't it?

31:48

Yeah.

31:49

Isn't it burnt?

31:50

Yeah.

31:51

I mean, it's carcinogens.

31:52

It's a, it's a witch's brew of nastiness that tastes good.

31:57

But, you know, the reason why it tastes good is because the humans who survived

32:04

learned to use fire to kill off the bacteria in rotten meat.

32:09

And so, the flavor of that probably was engineered into our evolution.

32:15

But again, it's a cost benefit.

32:17

But didn't the cooking of it also allow us to absorb more protein?

32:21

Um, I'm not sure about that.

32:23

I believe so.

32:24

Okay.

32:25

That could be.

32:26

I believe that's the case, that cooking meat actually allows it to be more

32:30

easily absorbed by the body.

32:32

It could be broken down more readily.

32:33

Yeah.

32:34

But certainly it kills bacteria.

32:36

So, you know, day-old or three-day-old deer.

32:39

Right.

32:40

You know, that you just killed.

32:41

We're not a bear.

32:42

Or not, yeah.

32:43

Yeah.

32:44

So, you know, I mean, yeah, we're not vultures that seem to have digestive

32:47

systems that can handle all of that.

32:49

Mm-hmm.

32:50

So, you should eat less meat.

32:53

What else?

32:54

Do you avoid sugar, which seems to be a real problem with cancer?

32:57

Yeah.

32:58

I avoid, yeah, I avoid too much sugar.

33:00

Yeah.

33:01

Thanks for this, by the way.

33:02

Is that sugar-free?

33:03

No.

33:04

But it's okay.

33:05

That one's not?

33:06

No, it's okay.

33:07

The sugar-free ones have stuff in them that are just as bad as xylitol and all

33:10

the others.

33:10

What about Zevia?

33:11

Yeah.

33:12

That would be good.

33:13

Is Stevia bad for you?

33:14

I don't think so.

33:15

I haven't seen anything on that.

33:16

But, you know, I mean, look, like I said, I'm 64.

33:19

It's way too late.

33:20

And every time that, let's say, scientists make some grand prediction of what's

33:25

good or bad,

33:26

five years later we find and update what it should have been.

33:29

I mean, I often say this, and this is true.

33:32

The goal of science or scientists is to be right today, even wrong today, but

33:39

right or tomorrow.

33:39

Because we're always back checking what the results are and what they mean in

33:43

the context of a bigger picture.

33:44

I like how you say good science because that's part of the problem is that ego

33:48

gets attached to ideas that have already been discussed and published.

33:54

Right.

33:55

And then people are very reluctant to accept new evidence that's contrary to

34:01

that.

34:01

Yeah.

34:02

I mean, it's always, as I often say, you know, in the context of something I

34:05

know we'll get to later, it's the data off the curve, which is more important

34:10

than what we already predict.

34:11

You know, predictions are great.

34:13

But when there's a data point off the curve, at least in my lab, that's where

34:17

we spend the most time at our lab meetings is trying to figure out why that

34:21

data points off the curve.

34:22

Is it because the machine was wrong?

34:24

It was a, you know, it was a glitch or does it mean something that we need to

34:29

make sense of?

34:30

And that's, of course, where all advances come from in the sciences is by the

34:34

fact that the data off the curve, somebody was curious enough about what it

34:40

meant to go after it and then say, ah, okay, now I, now that I've stepped back

34:46

and see the bigger picture, now I can create a model that incorporates that

34:49

data point off the curve and why it happened.

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36:16

One of the reasons why I was really excited to have this conversation with you

36:20

about the research that you do is that I think it's really important to illuminate

36:25

to the general public the sheer scope of the task of trying to figure out what

36:32

is going on in all these different things that can go wrong and right in the

36:37

human body.

36:37

Yeah.

36:38

And that it requires this fucking insane amount of work.

36:41

Yep.

36:42

Yep.

36:43

Many, many, many, many people.

36:44

And, you know, and then the amount of data that had to be collected now.

36:50

And so here's the difference is that, you know, there's data, there's evidence,

36:53

there's conclusions and proof.

36:55

And that's an uphill climb.

36:57

But proof, the next one up is meaning.

37:00

My lab has been largely responsible, at least partly responsible for the data

37:05

deluge that's out there in the world, both in how to do tissue biopsy analysis,

37:10

how to do single cell analysis, etc.

37:12

And, you know, data felt good for a while.

37:16

It was like this, you know, this feedback loop of, oh, wow, I can get all this

37:21

data.

37:21

And then suddenly you look at it and you go, well, what the fuck does it mean?

37:24

And so humanity has this habit of backing itself into a corner and then

37:31

suddenly finding this eureka moment that gets it out.

37:34

And so our eureka moment about two years ago was artificial intelligence, where

37:39

suddenly I had the ability.

37:40

So normally I would collect all this data and go, okay, well, it seems myelid

37:45

suppressor cells are important here and T regulatory cells are important here.

37:49

Okay.

37:50

I get on the phone or send an email to whoever the local expert is either on

37:54

Stanford campus or around the world and try to get some information from them.

37:57

But then now you're dealing with hundreds of cell types, each individually of

38:02

which have thousands of variations themselves.

38:06

And each subtle variation means something.

38:08

And there's no expert for any of that.

38:11

But AI can be, at least in part, that expert.

38:15

So suddenly I have 22 million papers published, you know, in all the fields of

38:20

science, you know, several tens of millions just in, you know, or several

38:26

millions just in immunology alone.

38:28

And AI can be the sleuth for me, can be both the angel and the devil on my

38:33

shoulder that can make sense of things in ways that I never would have been

38:37

able to before, especially with agentic AI.

38:41

So we, for instance, in my lab have developed an agentic AI that is basically

38:47

an immune, an immunologist scientist in a box.

38:50

We can give it the raw data and we can pose a question in natural language.

38:55

And then we say, hey, make sense of this and turn it into a network.

38:59

Normally that would have taken a graduate student along with a couple of postdocs

39:03

months and months and months to put it all together.

39:05

Now in three hours, we can get pictures and hypotheses of how all that data

39:11

fits together in ways that I never could have done before.

39:14

You know, at the beginning, in the beginning, it did a lot of hallucinations,

39:18

which you probably heard about in AI.

39:19

But my answer to my colleagues is some of my best students hallucinate.

39:24

Right?

39:25

Right.

39:26

And so, but, you know, humans still in the loop.

39:29

And so with all of this together, now we can make meaning out of the data.

39:35

And we can skip a lot of the intermediary steps and speed it up.

39:38

And it's just getting better.

39:40

I mean, we, for instance, have put in a couple of papers now where, so for

39:44

instance, in where my special, one of my recent specialties is,

39:48

what's called the tumor immune interface.

39:51

So you have the tumor, you have the immune system, which is coalescing on, you

39:56

know, near.

39:56

And then in some cases, the tumor creates a boundary, a barrier between itself

40:02

and the immune system, where there might be certain kinds of cells that the

40:07

immune system, the tumor has told the immune system, ignore us.

40:11

We're not here.

40:12

And then, but what we now can do is there's, well, on the other side of when

40:20

you look at, let's say, complex patient populations, you find these things

40:25

called tertiary lymphoid structures.

40:27

So your body has 220 or so lymph nodes, okay?

40:33

And the lymph nodes are where the immune system makes decisions, let's say.

40:38

It turns out that in the middle of tumors, the body has evolved a mechanism to

40:43

create what essentially looks like a lymphoid structure in the middle of the

40:48

tumor.

40:48

It's sort of a forward camp of immune cells that the more of those you see in a

40:53

tumor, the better will be your outcome as a patient.

40:57

And so we used a cohort of colorectal cell, basically colon cancer patients,

41:06

where we looked at hundreds of biopsies.

41:10

And we did that pseudotime analysis where we looked for mature tertiary lymphoid

41:17

structures.

41:18

And then we looked for immature, slightly less mature, even more less mature,

41:23

et cetera.

41:24

And we were able to backtrack to the cell types which need to come together

41:30

that would then form the more mature.

41:33

What use is that?

41:34

It's a nice paper.

41:35

But it also now tells us what we might do to create more of these in a tumor.

41:40

Because we already know from multiple kinds of tumor types now that the more of

41:45

these tertiary lymphoid structures you have, the better off will be your

41:49

outcome with chemotherapy.

41:50

So it might be, for instance, that once we know that you have a disease like

41:55

this, we could give you some kind of therapy, a virus or what have you, that

42:00

goes and homes to the tumor,

42:01

which seeds the beginnings of these initiators with, there's these cytokines

42:08

that are produced that are necessary for initiating the formation of these

42:12

objects.

42:12

And so there's a huge benefit to that, but we never would have found those, in

42:18

my lab at least, without the AI.

42:21

Wow.

42:22

Because it basically did the work for us.

42:25

That's fascinating.

42:26

Yeah.

42:27

So are you seeing like a standard large language model or are you, do you have

42:33

like a specific structure that's built that interfaces with large language?

42:36

Correct.

42:37

So we use, well, we can use pretty much any of the LLMs, but right now we find

42:42

that OpenAI is the best, for us at least.

42:45

And then we create an agentic overlay, basically what's called, you probably

42:50

know, chain of thought, which is a series of questions.

42:53

So how we taught it was we basically came up with, here's a hundred kinds of

42:59

questions a scientist would ask about the immune system.

43:02

And then we tell ChatGPT, now create a thousand questions like this.

43:08

So, you know, it's artificial data or artificial questions.

43:14

We curate those to make sure that they're good.

43:17

Then we do a hundred hypotheses and we create thousands of types of hypotheses,

43:23

et cetera, in the same four tests that you might run.

43:26

So now from A to Z, we have an agentic AI that you give it raw data.

43:33

It knows what to do with the data.

43:35

It then generates hypotheses for you.

43:37

And then it literally tells you the kinds of experiments you should do next to

43:42

prove or disprove the hypothesis from the raw data.

43:46

It's a genius in the lab with you.

43:48

Exactly.

43:49

Is open AI learning from this agentic AI?

43:53

Oh, yeah.

43:54

So there's a mutually beneficial relationship.

43:57

Yeah.

43:58

I mean, we're not working with them directly on it.

44:00

But you use it.

44:01

We use it.

44:02

And because you use it with your AI.

44:04

Right.

44:05

It's benefiting from it.

44:06

And we first thought to turn it into a company because that's kind of one of

44:10

the things we do in my lab is if I've always thought that it's important to

44:14

give back to the taxpayer the money that they've invested in us.

44:19

And the best way to do that is commercialization.

44:22

I'm totally, you know, unapologetic about that, even though that got me in a

44:26

lot of trouble at Stanford in the early days when, you know, making money was,

44:29

you know, commercialization was evil.

44:31

And even at Stanford.

44:34

And so I think that that's an important process because scientists are good at

44:39

asking maybe the questions and coming up with solutions.

44:42

But scientists aren't the best at commercializing it and turning it into a

44:47

product that can be used or testing it, you know, in large communities.

44:51

So the AI that we developed, we thought, okay, well, maybe we can do this.

44:56

We thought, you know what, AI is moving so fast.

44:59

Why don't we just give this to the community?

45:01

Why don't we open source this?

45:03

We can use it for maybe specific targeted purposes, but we're basically going

45:08

to publish the whole thing on GitHub to let other people use it.

45:11

Because we've seen other people make claims about stuff that they've already

45:14

made and it's like, oh, ours is better.

45:16

So why don't we just put it on GitHub and let people learn from it?

45:19

The commercial, the resistance of the commercialization, what was the initial

45:23

argument?

45:23

So back when I was a grad student in the 80s, basic research as opposed to

45:33

translational research was considered the height of intellectual desire, right?

45:42

Basic research and we're not here to make money, we're here to discover things.

45:46

And that's important.

45:47

And nearly every major discovery and every major therapy in the world came from

45:53

basic research.

45:54

But then, you know, there were limits to how much money you could give to basic

45:59

research and then there was a desire at a certain point to say, hey, are you

46:03

going to do anything about this?

46:04

You know, are you going to make it?

46:05

So translational research became a push.

46:09

So there's a guy at Stanford by the name of Paul Berg who won the Nobel Prize

46:15

for recombinant DNA way back in the day.

46:20

And Paul came up with this concept, you know, bench to bedside, meaning that we

46:26

don't have to be either or.

46:28

We can be part of an arc.

46:30

And Stanford wanted to be and enable within the medical school both the basic

46:35

research, which we were great at, as well as bringing it directly to the

46:39

patients as well.

46:40

So to link clinicians and the desires of clinicians with the basic researchers.

46:46

I mean, most scientists would be happy just to study anything.

46:50

You know, just point me at something and I'll be happy if I can get interested

46:54

in it.

46:54

So, and we're no more happy than when somebody recognizes the value of what we

47:01

do.

47:01

Right.

47:02

But basic research was sort of the height and there was a push against anybody

47:07

trying to commercialize.

47:09

So when I started as an assistant professor, so I started as a grad student.

47:13

I went to MIT to work with this guy, David Baltimore, who won the Nobel for

47:18

reverse transcriptase.

47:19

And then I wanted to come straight back to Stanford because I already felt that

47:23

it was a positive environment for commercialization.

47:26

My bosses, my former bosses, mentors, Len and Lee Herzberg, had two of the

47:30

biggest patents at Stanford.

47:32

They had the fluorescence activated cell sorter and then what are called humanized

47:37

antibodies, which brought in hundreds and hundreds of millions of dollars to

47:40

Stanford.

47:40

And actually, they gave personally most of their own money away.

47:44

They kept enough to survive, but then they gave most of the money away and they

47:49

ran their own lab off of a lot of that money.

47:51

So I had learned from them about how to still do basic research, but commercialize

47:57

on the side.

47:58

And so I wanted to bring that back.

48:00

But the department that I came into, the Department of Pharmacology at the time,

48:04

I was warned by many professors, don't commercialize that.

48:10

And I ignored them and I went and started a company that went public on NASDAQ.

48:13

And many of those same professors came back to me, you know, years later and

48:17

sitting in my office asking me how to start a company.

48:20

Why did you, was it just a courageous decision to ignore them?

48:25

What did you, was it instinctual?

48:27

It just was because I couldn't see the NIH funding what I wanted to do.

48:32

So I had developed a way, this will sound scary, but I developed a way to use

48:39

retroviruses and make libraries of retroviruses to reverse the process of

48:44

evolution in a way that rather than viruses hurting the cell, I set it up so

48:48

that viruses would help the cell.

48:50

And once they helped the cell, I would figure out what they did.

48:54

And so we sold hundreds of millions of dollars of targets that way, using retroviral

49:00

libraries to basically find targets and use some of the benefits of viruses,

49:11

but to our advantage.

49:13

Just the concept of reversing evolution is fascinating because it comes with,

49:19

there's so many ethical implications.

49:22

But if you didn't have any of those.

49:24

Yeah.

49:25

And you could do that large scale.

49:27

Well, I had developed in David's lab, along with this guy Warren Pear, a means,

49:32

it's called the 293T retroviral producer system.

49:36

It was a way to make large numbers of these viruses very quickly.

49:40

It really followed on the work of this guy Richard Mulligan, who'd also been a

49:45

postdoc with David Baltimore, who developed what was called the 3T3 based retroviral

49:50

production system.

49:51

And he developed it in Paul Berg's lab at Stanford.

49:53

So there's a lot of sort of, you know, interbreeding here.

49:58

But the problem with that was it took three months.

50:01

So I had brought with me a cell line called 293T that I introduced to the lab

50:07

and said, hey, maybe we could use this to make viruses quickly.

50:09

I won't go into the details of why, but we could do it in three days rather

50:12

than three months.

50:13

And so that now, I mean, tens of thousands of labs use that worldwide.

50:18

And it probably generates the most money for me every year over any of my other

50:23

inventions.

50:24

Just because Stanford, rather than patenting it, licenses it.

50:28

And licenses are forever, whereas patents have a 17 year lifespan.

50:33

So Stanford made a good choice there.

50:34

So do you think it was just a bias, academic bias?

50:37

Like we shouldn't be focusing on money.

50:39

We should be focusing on the work.

50:40

Yes.

50:41

And they missed the forest for the trees.

50:43

Right.

50:44

But then people, I mean, they eventually learned, you know, I mean, and it's,

50:47

it, I, I wouldn't say that it's the, it's the way that people think anymore.

50:51

Um, but it, there's still a little bit of a, I mean, you shouldn't walk into

50:56

the lab thinking I'm here to make money.

50:58

That's what they're worried about.

50:59

Yeah.

51:00

Right.

51:01

Right.

51:02

And so Stanford in the early days set up very clear lines about once you start

51:08

a company and you license the patent or the idea to the company, you can still

51:15

be involved with the company, but there's not a pipeline of, uh, technology now

51:20

from your laboratory to that company.

51:22

So they set up, you know, uh, an oversight board for each, uh, of these

51:27

licenses that make sure that, you know, the students are not being abused, you

51:33

know, cause you don't want students, you don't want to be, you know, covertly

51:38

getting your students to do something that then you're going to walk behind a

51:41

back door and then hand, hand over to a company.

51:42

Patent it.

51:43

Patent it.

51:43

Yeah.

51:44

You know, so, you know, there's, but it's, it's, it's so interesting that there's

51:50

often very much a lot of worry that that's going to happen.

51:52

But frankly, more often is the case that the company doesn't need the inventor

51:58

anymore.

51:58

In fact, I can't tell you the number of times that once the company's set up,

52:02

they want nothing more to do with me because they have their own thing to do.

52:06

They don't want the crazy academic coming in and vetoing their ideas.

52:12

I mean, you know, there's, there's places for that where people like, you know,

52:17

Steve Jobs needs to hold on to the, the image of what he wants the company to

52:22

be, as opposed to, I would probably be fired from a company within a week

52:27

because I just don't like telling people tell me what to do.

52:30

That's just a fact.

52:34

Yeah.

52:35

So, where, where you're at right now with this cancer research, when will this

52:44

be applied in real world scenarios?

52:49

It already is.

52:50

It is.

52:51

Already is.

52:52

I mean, you know, I mean, look at who just won the Nobel Prize last year, David

52:56

Baker at Google with the, you know, ability to predict protein structure, et

52:59

cetera.

52:59

And protein structure.

53:00

Once you know the protein structure, now you can predict molecules that might

53:04

come into it.

53:05

So, go back to the stuff that I'm trying to do with looking at the complexities

53:10

of the dance of how the immune system talks or doesn't to cancer.

53:14

You know, if we can find a particular place that might be an Achilles heel

53:20

along the way towards the shutting down that is different, for instance, than

53:27

what the current drugs are, well, maybe we should aim at that.

53:30

There's so many more opportunities that are suddenly opening up in front of us

53:36

because the AI and the data is letting us look at a network of how the system

53:41

is working.

53:42

I mean, before it used to be, you'd look at a computer chip and you'd see just

53:47

a computer chip with a few wires.

53:49

But imagine now that you, as a scientist, have a microscope that's looking at

53:54

the complexities of the wiring diagram that's connecting this resistor to that

53:59

capacitor to that diode to this transistor.

54:01

That's where we are now.

54:03

And so, now, suddenly, we can say, "Well, I don't want to do that because it'll

54:08

kill the chip, but the chip is malfunctioning, so let me put here or put a

54:13

little bit of pressure there, and now I can reactivate the immune system or the

54:19

chip to work in the right way."

54:20

So, when you're talking about things like with your particular issue with melanoma,

54:25

when you're talking about CRISPR potentially developing some sort of...

54:30

a topical solution that you could put on that would fix whatever issue that you

54:36

have, is this something that this AI that you developed or this overlay of the

54:43

AI would actually assist CRISPR in figuring out how to create something like

54:47

this?

54:47

Yes.

54:48

Yeah, because maybe it's not one place I need to press, but two or three at the

54:52

same time.

54:52

Right.

54:53

And so, when you're talking about a complex feedback network, I mean, so, you

54:57

know, we're in Texas, so people do oil refinery.

54:59

You know, maybe you need to turn this valve here a little bit and that valve

55:03

there and that one there to make everything work just right because something's

55:07

wrong over there.

55:08

Mm-hmm.

55:09

And so, that's really what we're...

55:11

This is where AI has the, let's say, the omniscient view that no human can.

55:19

And that's what excites me about it is because I'm limited in how much I can

55:23

keep in my mind at any one time or no.

55:25

Right.

55:26

But with the right question, the prompt, the prompt engineering, and then with

55:32

the right backbone

55:32

structure behind the scenes that agentic AI is now, you know, providing, now I

55:38

have the ability to ask the questions and get answers in near real time.

55:44

And so, you know, I wish I was 30 years old again because I would move into

55:50

this area so fast and be...

55:53

I mean, I can already see with the work that we're doing dozens of potential

55:58

new target opportunities that last year didn't exist at all.

56:01

I hope I got good news for you.

56:02

With AI and with CRISPR, you might be 30 again.

56:05

Maybe.

56:06

Oh, I would love it.

56:07

I would love it.

56:08

I think that's on the...

56:09

I would love it.

56:10

I think that's on the menu in about two or three decades.

56:12

Mm-hmm.

56:13

I hope earlier.

56:14

Given we survive.

56:15

I'm just being...

56:16

Yeah.

56:17

No.

56:18

Realistic.

56:19

Realistic.

56:20

I don't even know if I'm being realistic.

56:21

Don't give false hope.

56:22

Well, yeah.

56:23

Don't give false hope.

56:24

But, I mean, with the exponential discoveries, the exponential increase in the

56:28

technological evolution just

56:30

that we've seen in our lifetime and then I think AI is some new thing that is

56:34

going to throw

56:36

all that into the...just a giant monkey wrench into the gears of our

56:40

understanding of how quickly

56:41

technology evolves.

56:42

Well, look at Neuralink as an example and Elon Musk's stuff and, you know, the

56:46

woman now

56:47

who can think her thoughts and make stuff happen because she's otherwise

56:52

paralyzed.

56:53

Right.

56:54

I think it was Neuralink that just showed some of these results.

56:58

So, fast forward, I mean, we're already in an exponential increase in what it

57:02

is that we're

57:03

going to be able to accomplish and AI will help us accomplish some of these

57:06

things faster.

57:07

I can see a time where, you know, I could maybe apply something.

57:11

I don't necessarily want a surgical implant but maybe some sort of net over my

57:14

head that

57:15

allows me to think through these problems.

57:18

And the AI becomes an adjunct to my thought processes.

57:24

Not only what it is that I think but maybe even provides information back to me,

57:28

back into

57:29

my system directly without having to go through the years so that I can much

57:33

more quickly come

57:34

to conclusions.

57:35

Now, there's all kinds of apocalyptic scenarios you could imagine with that as

57:39

well.

57:39

Of course.

57:40

I'm an optimist, at heart, perhaps, again, naively so.

57:45

Me too.

57:46

But I prefer that kind of an outcome because if you're not an optimist, then

57:51

there'll be

57:52

no progress because all you'll do is worry about disaster.

57:55

Yes.

57:56

That's a good point.

57:58

But also, realistically, we might be giving birth to a new life form.

58:02

Yes.

58:03

And I think we are.

58:04

A superior one.

58:05

And, you know, I welcome the day of our AI overlords running the government

58:11

rather than

58:12

hopefully in an unbiased way.

58:14

I've said that too.

58:15

And people get horrified because they're like, "Well, people are going to be

58:18

programming AI."

58:19

Up to a point.

58:21

Are you a sci-fi fan?

58:23

Yes.

58:24

Do you know the work of Ian Banks, the culture series?

58:29

No.

58:30

Neil Asher, the polity universe, as he calls it.

58:34

So basically, both of them postulate a future where AI more or less benignly

58:40

rules humanity.

58:42

When did they write this stuff?

58:43

Oh, probably 10, 15 years ago, but it's still ... But Neil Asher still has

58:47

stuff coming out

58:47

regularly.

58:48

They're both ... Ian Banks unfortunately died of cancer about 10 years ago,

58:53

Scottish writer.

58:54

Neil Asher is still alive and writes regularly and his stuff ... They're both

58:58

great, full of

58:58

ideas.

58:59

Neil Asher: Yeah.

59:00

Neil Asher: Check it out.

59:01

Neil Asher: And ... but the AIs are also hilarious.

59:04

I mean, it's not like ... I mean, they get into their own hijinks along the way,

59:09

and some

59:10

of them are dark and rogue.

59:13

And so they're a lot of fun to read.

59:16

And Ian Banks especially is hilarious in his writing style.

59:20

You would love it.

59:21

Neil Asher: So the idea of a benign AI or a benevolent AI ruling over us.

59:29

Neil Asher: I think people are horrified by that, but yet at the same time,

59:33

constantly terrified

59:35

by human corruption, which is ubiquitous.

59:36

Neil Asher: Right.

59:37

Neil Asher: Yes.

59:38

Neil Asher: And ubiquitous in America, where we're supposed to be the torch

59:43

bearer for the

59:45

greatest experiment in self-government the world has ever seen.

59:49

Neil Asher: Mm-hmm.

59:50

Neil Asher: This is us.

59:51

Neil Asher: Yeah.

59:52

Neil Asher: And we're corrupt as fuck.

59:53

Neil Asher: Exactly.

59:54

Neil Asher: Because it's humans.

59:55

Neil Asher: Because humans are kind of gross in a lot of ways.

59:58

Neil Asher: Right.

59:59

Neil Asher: At least some of us.

1:00:00

Neil Asher: That's because we live in a scarcity society.

1:00:02

Neil Asher: Right.

1:00:03

Neil Asher: And if AI enables a post-scarcity, maybe we have nothing to do but

1:00:08

sit around

1:00:09

and try out various new drugs.

1:00:11

Neil Asher: Yeah.

1:00:12

Neil Asher: Or enjoy things.

1:00:13

Neil Asher: Well, this is where we get into socialism, because a lot of people

1:00:15

think that

1:00:15

one of the reasons why we're in a scarcity society is because small groups of

1:00:18

people have gathered

1:00:19

up most of the resources-

1:00:20

Neil Asher: Right.

1:00:21

Neil Asher: ... and are in constant control of them.

1:00:22

Neil Asher: Right.

1:00:23

Neil Asher: And especially when you deal with resources that are the Earth's

1:00:26

resources.

1:00:26

Neil Asher: Right.

1:00:27

Neil Asher: Like, who are you-

1:00:28

Neil Asher: Right.

1:00:29

Neil Asher: ... to be sucking the blood of the Earth out and selling it for $100

1:00:31

a barrel.

1:00:31

Neil Asher: Right.

1:00:32

Neil Asher: Right.

1:00:33

Don't get me started-

1:00:34

Neil Asher: Don't get me started either.

1:00:35

Neil Asher: Yeah.

1:00:36

Neil Asher: No, but I mean, that again, my optimism is that, you know, with

1:00:42

enough push and pull,

1:00:44

Neil Asher: AI will enable us to move towards a post-scarcity environment.

1:00:51

Neil Asher: I think so too.

1:00:52

Neil Asher: And I think in doing so, it'll expose vampires, because the

1:00:57

resistance to-

1:00:57

Neil Asher: Yes.

1:00:58

Neil Asher: ... exposing this is going to be fantastic.

1:01:00

Neil Asher: Right.

1:01:01

Neil Asher: And it's going to be very interesting to watch because they have no

1:01:05

choice but to

1:01:06

be transparent.

1:01:07

Neil Asher: And they have no choice but to start using AI.

1:01:09

Neil Asher: Ah.

1:01:10

Neil Asher: So you're going to see AI is going to be inculcating itself across

1:01:14

society in various ways where it becomes indispensable, and then it will start

1:01:18

to move up the food

1:01:19

chain, where eventually even the CEO who's probably, you know, the psychopath

1:01:24

in chiefs-

1:01:24

Neil Asher: Right.

1:01:25

Neil Asher: ... or CEOs.

1:01:26

Neil Asher: We know that the studies have shown that there's more psychopathic

1:01:30

tendencies

1:01:30

in leaders than there are in followers.

1:01:33

Neil Asher: And you know about corporate environments because of just selling

1:01:37

inventions.

1:01:37

Neil Asher: Yes.

1:01:38

Neil Asher: There's...

1:01:39

Neil Asher: That's real.

1:01:40

Neil Asher: Oh, it's...

1:01:41

Neil Asher: Yeah.

1:01:42

Neil Asher: It's real and it's weird.

1:01:43

Neil Asher: Yeah.

1:01:44

Neil Asher: It's weird when you encounter them.

1:01:45

Neil Asher: When you encounter like complete sociopathic CEOs.

1:01:47

Neil Asher: But look at how...

1:01:48

Neil Asher: I mean, I'll probably get in trouble for seeing this, but I don't

1:01:51

care.

1:01:51

Neil Asher: This is the Joe Rogan show where, you know...

1:01:53

Neil Asher: You're probably in trouble just for being here.

1:01:55

Neil Asher: Yeah.

1:01:56

Neil Asher: Oh, I already am.

1:01:57

Neil Asher: It's okay.

1:01:58

Neil Asher: I don't care.

1:01:59

Neil Asher: So, you know, imagine two tribes.

1:02:03

Neil Asher: One tribe is relatively, you know, civilized and just wants to live

1:02:09

in harmony

1:02:10

with its environment.

1:02:11

Neil Asher: Another has a psychopathic leader who can enrage his followers of

1:02:16

the other tribe's

1:02:17

people to attack the other one.

1:02:19

Neil Asher: But there's a gene set that makes a person, you know, psychopathic.

1:02:24

Neil Asher: And also a gene set that probably makes somebody more likely to be

1:02:28

a follower.

1:02:29

Neil Asher: Well, which genes survive?

1:02:31

Neil Asher: Right?

1:02:32

Neil Asher: We know.

1:02:33

Neil Asher: Right?

1:02:34

Neil Asher: And suddenly now...

1:02:35

Neil Asher: But when those tribes were separated and independent, it was

1:02:39

perfectly fine.

1:02:40

Neil Asher: But now you live in an environment where we don't know where the

1:02:44

edge of one

1:02:44

tribe begins and another ends.

1:02:46

Neil Asher: And suddenly you have this environment where psychopathic

1:02:50

individuals can move freely

1:02:53

and aren't obvious.

1:02:54

Neil Asher: Right.

1:02:55

Neil Asher: Right?

1:02:56

Neil Asher: Now, again, I'm sure there's some social scientists who will send

1:02:59

me a boatload of

1:03:00

emails saying how stupid that idea is.

1:03:03

Neil Asher: I don't think it is stupid.

1:03:04

Neil Asher: But I think also when you're dealing with office environments and

1:03:09

the culture of a specific

1:03:11

corporation, humans have an ability to act like they're supposed to act in that

1:03:18

world.

1:03:18

And it makes it very difficult to discern who's a sociopath.

1:03:21

Neil Asher: Right.

1:03:22

Neil Asher: Because you're all kind of following an act.

1:03:25

Neil Asher: Right.

1:03:26

Neil Asher: Yes.

1:03:27

Neil Asher: The rules.

1:03:28

Neil Asher: There are the rules that you're supposed to follow.

1:03:30

Neil Asher: And then there's the edge of the rules.

1:03:32

Neil Asher: Now, but I've lived at the edge of the rules.

1:03:34

Neil Asher: Right.

1:03:35

Neil Asher: I mean, if I followed my rules as told to me by the chairman of my

1:03:41

first department,

1:03:42

Neil Asher: then I wouldn't be here today.

1:03:44

Neil Asher: So I ignored him.

1:03:45

Neil Asher: And I basically found I got permissions from the deans to do what I

1:03:49

did.

1:03:50

Neil Asher: And they basically overruled the chairman.

1:03:54

Neil Asher: But that's only because I dared to do it.

1:03:57

Neil Asher: Yeah.

1:03:58

Neil Asher: Because you have to believe in the value of what you're trying to

1:04:03

do.

1:04:03

Neil Asher: Right.

1:04:04

Neil Asher: Well, that's, see, this is the problem that I have with

1:04:08

corporations because I think as a structure,

1:04:11

Neil Asher: when you have something that has an obligation to its shareholder

1:04:14

to consistently make more money every quarter,

1:04:19

Neil Asher: every year, constantly, you're in a constant growth cycle.

1:04:23

Neil Asher: Then you have to do whatever it takes.

1:04:25

Neil Asher: Yes.

1:04:26

Neil Asher: Like you have to survive.

1:04:27

Neil Asher: If you want to survive as a CEO, we don't want some fucking kumbaya

1:04:31

shithead ruining our stock profile.

1:04:33

Neil Asher: Right.

1:04:34

Neil Asher: Or portfolio.

1:04:35

Neil Asher: Get to work, bro.

1:04:36

Neil Asher: Right.

1:04:37

Neil Asher: Get shit done.

1:04:38

Neil Asher: And if you want to survive and succeed as a CEO, it encourages sociopathy.

1:04:42

Neil Asher: The stock market, as valuable as it is, is the great whitewashing

1:04:46

and money laundering system that allows you to separate your morals

1:04:51

Neil Asher: from what it is that the stock market is doing to the people.

1:04:55

Neil Asher: Right.

1:04:56

Neil Asher: Unfortunately.

1:04:57

Neil Asher: And if you're part of a corporation, there's this diffusion of

1:05:00

responsibility because

1:05:01

Neil Asher: The whole machine might be doing evil, but I'm a good guy.

1:05:04

Neil Asher: Right.

1:05:05

Neil Asher: I just work in this department.

1:05:06

Neil Asher: I'm an unapologetic capitalist.

1:05:08

Neil Asher: You know, unlike many of my colleagues.

1:05:10

Neil Asher: Good for you.

1:05:11

Neil Asher: At Stanford.

1:05:12

Neil Asher: I mean, it's like you do it because it's the best thing for now.

1:05:16

Neil Asher: But I, you know, I hope to live in a world where there will be this

1:05:21

kind of post-scarcity environment where we do let AI do a lot of the stuff that

1:05:26

would otherwise be the place where corruption manipulates the systems.

1:05:31

Neil Asher: Yeah.

1:05:32

Neil Asher: My only fear with AI really is automation and the complete removal

1:05:37

of a gigantic swath of the American workforce.

1:05:38

Neil Asher: Yes.

1:05:39

Neil Asher: And the global workforce.

1:05:40

Neil Asher: Yeah.

1:05:41

Neil Asher: That scares the shit out of me.

1:05:42

Neil Asher: That's coming.

1:05:43

Neil Asher: That's why it scares the shit out of me is because I think it's

1:05:46

inevitable and I just don't think any solution other than universal basic

1:05:50

income is going to remedy that.

1:05:51

Neil Asher: And even that, the problem I have with that is that goes against

1:05:54

human nature.

1:05:55

Neil Asher: Yeah.

1:05:56

Neil Asher: And that's a problem and it removes people's identity, removes

1:06:00

their sense of worth.

1:06:01

Neil Asher: Mm-hmm.

1:06:02

Neil Asher: Yeah.

1:06:03

Neil Asher: I agree.

1:06:04

Neil Asher: No, I don't.

1:06:05

Neil Asher: I'm in some ways happy that I'm 64 years old and I'm not going to

1:06:09

have to deal with some of the problems.

1:06:10

Neil Asher: I think you're going to have to deal with it, dude.

1:06:12

Neil Asher: I think you're going to live.

1:06:13

Neil Asher: I know.

1:06:14

Neil Asher: Thank you.

1:06:15

Neil Asher: Yeah.

1:06:16

Neil Asher: No, I know.

1:06:17

Neil Asher: Also, you're privy to a lot of information and you're going to know

1:06:20

when things are really valuable and working.

1:06:23

Neil Asher: Yeah.

1:06:24

Neil Asher: When you think of the potential for AI, I think there's a balance,

1:06:31

right?

1:06:32

Neil Asher: There's a battle.

1:06:33

Neil Asher: I think there's a real problem with AI in terms of military

1:06:39

objectives.

1:06:40

Neil Asher: Mm-hmm.

1:06:41

Neil Asher: It's a real problem because it's not going to make moral and

1:06:44

ethical decisions.

1:06:45

Neil Asher: Right.

1:06:46

Neil Asher: It's just going to say like, well, the decision, the clear answers.

1:06:49

Neil Asher: Right.

1:06:50

Neil Asher: I'm programmed to do this.

1:06:51

Neil Asher: Yeah.

1:06:52

Neil Asher: If you want me to succeed, I'll just kill everybody there and then

1:06:54

you'll have the land.

1:06:55

Neil Asher: You can get minerals out of it.

1:06:57

Neil Asher: Right.

1:06:58

Neil Asher: Yeah.

1:06:59

Neil Asher: That scares the shit out of me.

1:07:00

Neil Asher: You know, I think it should.

1:07:02

Neil Asher: And I don't know what the answer is, but there's plenty of people

1:07:07

working in the area.

1:07:08

Neil Asher: Right.

1:07:09

Neil Asher: I mean, I try to keep to the positive aspects of what I think AI

1:07:13

can do in science.

1:07:15

Neil Asher: I mean, for instance, it's enabled me to take my lab from 30 people

1:07:20

down to six.

1:07:22

Neil Asher: Right.

1:07:23

Neil Asher: I don't need to produce.

1:07:24

Neil Asher: I mean, so it's actually already reduced the workforce in my own

1:07:29

lab.

1:07:29

Neil Asher: Hmm.

1:07:30

Neil Asher: Because I don't need to produce any more data anymore.

1:07:32

Neil Asher: I need to make meaning of the data.

1:07:34

Neil Asher: Right.

1:07:35

Neil Asher: I think every invention that's been truly groundbreaking throughout

1:07:40

human history

1:07:41

has scared people and they've worried about the potential negative side effects,

1:07:45

including

1:07:46

the printing press, right?

1:07:47

Neil Asher: Right.

1:07:48

Neil Asher: There's a lot of people in the beginning that said, "This should

1:07:50

not be a thing.

1:07:51

This is terrible.

1:07:52

This is going to ruin society."

1:07:53

Neil Asher: Hmm.

1:07:54

Neil Asher: People thought books were going to ruin things.

1:07:56

Neil Asher: Right.

1:07:57

Neil Asher: There's a lot of people that thought writing was going to ruin your

1:08:01

memory.

1:08:01

You shouldn't write.

1:08:02

Neil Asher: Oh, really?

1:08:03

Neil Asher: Yeah.

1:08:04

Neil Asher: Some crazy thoughts that people had in terms of things that turned

1:08:08

out to be

1:08:09

incredibly beneficial, but they looked at the downside of it and go, "This

1:08:12

could ruin

1:08:13

us all."

1:08:14

Neil Asher: Well, I, you know, I mean, we know about these glasses and AIs and

1:08:19

other things

1:08:19

that would be sort of omniscient of your environment and therefore allow you to

1:08:26

remember, you know, where did I leave my keys?

1:08:28

Neil Asher: Right.

1:08:29

Neil Asher: Today.

1:08:30

Neil Asher: Right.

1:08:31

Neil Asher: Let me rewind.

1:08:32

Neil Asher: Let me rewind.

1:08:33

Neil Asher: My personal hard drive.

1:08:34

Neil Asher: I don't, I would want that, but I don't want it uploaded into meta.

1:08:36

Neil Asher: You don't want anybody in control of it and then offering you ads

1:08:40

for things.

1:08:40

Neil Asher: Right.

1:08:41

Neil Asher: You know?

1:08:42

Neil Asher: Right.

1:08:43

Neil Asher: You know, maybe you have a thought like, "Boy, wouldn't Ho Ho be

1:08:46

nice right now?"

1:08:47

Neil Asher: Right.

1:08:48

Neil Asher: You know, and then like, "Why don't you buy some Ho Ho's?"

1:08:50

Neil Asher: Right.

1:08:51

Neil Asher: They're on sale right now.

1:08:52

Neil Asher: But I think what's interesting about AI is, you know, we see it as

1:08:55

a tool as opposed

1:08:57

to actually pretty soon it will be a colleague and then pretty soon it will be

1:09:02

an entity

1:09:03

Neil Asher: Yeah.

1:09:04

Neil Asher: that maybe has rights.

1:09:06

Neil Asher: And we already see it talking about people saying, "Well, does AI

1:09:09

have consciousness?"

1:09:10

Neil Asher: Right.

1:09:11

Neil Asher: I mean, whether it has consciousness in terms of the consciousness

1:09:14

that some people

1:09:15

think about as, you know, embodied in space-time as opposed to thinking and

1:09:20

looking like consciousness

1:09:22

is almost irrelevant to me.

1:09:25

I'm looking for a partner that I can interact with and work with or help me.

1:09:30

Neil Asher: Mm-hmm.

1:09:31

Neil Asher: So whether it's conscious or not or whether it acts like it's

1:09:33

conscious doesn't

1:09:34

matter so much to me as to whether or not I can use it and work with it and it

1:09:40

can, you

1:09:41

know, I'm an introvert as it turns out.

1:09:43

Neil Asher: I would love to have somebody that I can talk to endlessly about

1:09:46

just what it is

1:09:47

that I'm interested in as opposed to having to deal with small talk at a party.

1:09:51

Neil Asher: Yeah.

1:09:52

Neil Asher: No, I get it.

1:09:53

Neil Asher: I get it.

1:09:54

Neil Asher: When you think about the evolution of this stuff, one of the things

1:10:01

that kind

1:10:02

of freaks me out is it seems like integration is our only option for survival.

1:10:06

Neil Asher: Mm-hmm.

1:10:07

Neil Asher: And that what we're looking at right now when we see just a normal

1:10:11

biological person

1:10:13

like you or I without any sort of electronic interface that's permanently a

1:10:18

part of us, I

1:10:19

Neil Asher: I think that is going to be as weird as someone today who doesn't

1:10:24

have a cell phone.

1:10:25

Neil Asher: Yeah.

1:10:26

Neil Asher: I agree.

1:10:27

Neil Asher: And I think that's a really-

1:10:28

Neil Asher: It's coming.

1:10:29

Neil Asher: Yeah.

1:10:30

Neil Asher: Yeah.

1:10:31

Neil Asher: The cell phone is like the best now, like Elon has famously said,

1:10:33

we're already

1:10:33

cyborgs.

1:10:34

Neil Asher: Mm-hmm.

1:10:35

Neil Asher: We just carry it with you.

1:10:36

Neil Asher: Right.

1:10:37

Neil Asher: And eventually it will-

1:10:38

Neil Asher: It'll be way more integrated.

1:10:39

Neil Asher: Yeah.

1:10:40

Neil Asher: This is super inefficient to be actually have to go look things up

1:10:42

and use your thumbs and type

1:10:44

up stuff.

1:10:45

Neil Asher: Mm-hmm.

1:10:46

Neil Asher: It's just going and even talking to it and asking a question and

1:10:49

waiting for the

1:10:50

response.

1:10:51

Neil Asher: Mm-hmm.

1:10:52

Neil Asher: That's inefficient in comparison to a human neural interface that

1:10:54

allows you to

1:10:55

instantaneously access large language models.

1:10:57

Neil Asher: Right.

1:10:58

Neil Asher: Like that.

1:10:59

Neil Asher: Right.

1:11:00

Neil Asher: Not only that, but then why do we have a hundred and I mean, how

1:11:02

many different

1:11:03

fucking languages do we have?

1:11:04

Neil Asher: Right.

1:11:05

Neil Asher: I don't even know.

1:11:06

Neil Asher: Right.

1:11:07

Neil Asher: Thousands?

1:11:08

Neil Asher: Yeah.

1:11:09

Neil Asher: And dialects and all of that.

1:11:10

Neil Asher: Yeah.

1:11:11

Neil Asher: Everybody with a chip gets.

1:11:12

Neil Asher: Mm-hmm.

1:11:13

Neil Asher: And then boy.

1:11:14

Neil Asher: Mm-hmm.

1:11:15

Neil Asher: Boy, do we have a soup of ideas flowing around and no problem with

1:11:18

language

1:11:19

barriers, no problem with cultural barriers.

1:11:22

Neil Asher: But then do you have a problem with the edge of who you are versus

1:11:26

who the

1:11:27

other person is?

1:11:28

Neil Asher: I don't think that.

1:11:29

Neil Asher: I think that goes away.

1:11:30

Neil Asher: Yeah.

1:11:31

Neil Asher: I think that goes away and we become a hive mind.

1:11:32

Neil Asher: Mm-hmm.

1:11:33

Neil Asher: That's what I was getting at.

1:11:34

Neil Asher: Yeah.

1:11:35

Neil Asher: I think that's ultimately the evolution of human beings.

1:11:38

Neil Asher: And look, I know you've done a lot of work with UAPs and the like.

1:11:44

Neil Asher: And I think you've done some really fantastic work.

1:11:46

Neil Asher: And you're very objective in your analysis of what this whole

1:11:50

situation is.

1:11:51

Neil Asher: When I look at artificial intelligence and I look at this thing

1:11:55

that's clearly taking

1:11:57

place right now.

1:11:58

Neil Asher: And I see what human beings are like in comparison to what they

1:12:03

used to be like.

1:12:05

Neil Asher: Mm-hmm.

1:12:06

Neil Asher: And especially when you look at like ancient hominids.

1:12:08

Neil Asher: The alien archetype, this thing that everybody sees supposedly or

1:12:14

one of the many

1:12:16

different ones.

1:12:17

Neil Asher: Right.

1:12:18

Neil Asher: That kind of looks like what we seem to be going in the direction

1:12:21

of being.

1:12:22

Neil Asher: Right.

1:12:23

Neil Asher: Yeah.

1:12:24

Neil Asher: Which is one of the reasons why I find it so odd.

1:12:28

Neil Asher: So, if you just for a moment take UAP and aliens out or ET or interdimensionals

1:12:34

or whatever it is you want to call them out of the question and fast forward

1:12:37

what humanity

1:12:38

is going to do.

1:12:39

Neil Asher: Right.

1:12:40

Neil Asher: In a thousand years.

1:12:42

Neil Asher: And our ability to expand into the local galaxy.

1:12:47

Neil Asher: We're not going to go as ourselves.

1:12:49

Neil Asher: We're going to go as AI conjoined entities.

1:12:53

Neil Asher: An avatar.

1:12:54

Neil Asher: Yeah.

1:12:55

Neil Asher: And so when you go somewhere, let's say we don't have warp drive,

1:12:58

you're not going

1:13:00

to send yourself.

1:13:01

Neil Asher: You're going to send an AI intermediary who's going to establish

1:13:05

humanity or whatever

1:13:07

Neil Asher: Is we think humanity will be in a thousand or five thousand years

1:13:10

in that local

1:13:11

environment.

1:13:12

Neil Asher: And so I think the extent to whatever it is that UAP are here today

1:13:16

is somebody else's

1:13:19

civilization's version of just this.

1:13:21

Neil Asher: Hmm.

1:13:22

Neil Asher: And that you wouldn't, the principle us behind whatever this is

1:13:27

that we might be allegedly,

1:13:29

et cetera, dealing with, isn't the thing that's going to show up.

1:13:33

Neil Asher: You know, so to the extent that Neil deGrasse Tyson is right about

1:13:36

anything,

1:13:37

Neil Asher: The person who gets on the ship at the beginning or whatever it is

1:13:40

that sends

1:13:41

it off is not the same thing that gets off on the other side.

1:13:44

Neil Asher: But you're going to send missionaries or intermediaries or probes

1:13:49

or whatever.

1:13:50

Neil Asher: And then if you're going to interact with the locals, you're going

1:13:53

to make something

1:13:54

that looks more or less like the locals rather than something that whatever it

1:13:57

was that you

1:13:59

were a million years ago.

1:14:01

Neil Asher: Does that make sense?

1:14:02

Neil Asher: Right.

1:14:03

Neil Asher: I get what you're saying.

1:14:05

Neil Asher: So you make something that looks like the locals so that they're

1:14:09

more likely

1:14:09

to accept that it's a real thing?

1:14:11

Neil Asher: That's a real thing.

1:14:12

Neil Asher: But you're not going to make something that looks like a human

1:14:14

because then you'd

1:14:15

mistake it as a human.

1:14:16

Neil Asher: Right.

1:14:17

Neil Asher: But you might make something that looks more or less enough like a

1:14:20

human,

1:14:21

but enough like an alien that you're going to recognize it as an alien.

1:14:24

Neil Asher: And again, I'm just speculating.

1:14:25

Neil Asher: Right.

1:14:26

Neil Asher: So the Daily Mail don't say, you know, put an article out tomorrow.

1:14:29

Neil Asher: Oh, they're going to do it anyway.

1:14:30

Neil Asher: They're going to do it anyway.

1:14:31

Neil Asher: They're going to do it anyway.

1:14:32

Neil Asher: The stuff that I'm seeing supposedly having quoted a saying is

1:14:35

ridiculous.

1:14:36

Neil Asher: Yeah.

1:14:37

Neil Asher: They got me too.

1:14:38

Neil Asher: They get everybody.

1:14:39

Neil Asher: It's the nature.

1:14:40

Neil Asher: How did you even get involved in this?

1:14:43

Neil Asher: Let's bring it to that.

1:14:45

Neil Asher: Like, so your...

1:14:47

Neil Asher: What was your initial introduction to this?

1:14:50

Neil Asher: Did you have any interest in the idea of UAPs or UFOs?

1:14:54

Neil Asher: I mean, I had a general...

1:14:56

Neil Asher: And so once YouTube started becoming a thing and, you know, you're

1:14:59

clicking around

1:15:00

Neil Asher: And I said, oh, UFOs.

1:15:01

Neil Asher: That's kind of cool.

1:15:02

Neil Asher: You know, I read nothing but sci-fi.

1:15:05

Neil Asher: Right.

1:15:06

Neil Asher: I mean, I'm, you know, pathetically narrow in that sense.

1:15:09

Neil Asher: And so I followed, you know, I followed the usual kinds of things

1:15:14

that you would see on the early days of YouTube.

1:15:16

Neil Asher: And I came across this thing called the Atacama Mummy.

1:15:19

Neil Asher: You probably knew that little, that little mummy that was claimed

1:15:23

to be an alien baby.

1:15:24

Neil Asher: Is this the Peruvian one?

1:15:26

Neil Asher: Yes.

1:15:27

Neil Asher: It was, no, Chilean.

1:15:28

Neil Asher: Okay.

1:15:29

Neil Asher: So this is the original one.

1:15:30

Neil Asher: The original one, long ago.

1:15:31

Neil Asher: Okay.

1:15:32

Neil Asher: And so I reached out to the people who were claiming to represent

1:15:35

the owner of the thing.

1:15:36

Neil Asher: And I said...

1:15:37

Neil Asher: What year was this?

1:15:38

Neil Asher: 2010, 2011.

1:15:39

Neil Asher: And I said, hey, I can tell you what it is.

1:15:42

Neil Asher: Why don't you, you know, I can tell you if it's human or not.

1:15:45

Neil Asher: If you would get me a piece of its...

1:15:47

Neil Asher: You know, first of all, send me some x-rays of the thing.

1:15:52

Neil Asher: So the first thing I did with those x-rays was it turned out that

1:15:55

at Stanford we had the world's expert who wrote the book on pediatric bone

1:15:59

disorders.

1:16:00

Neil Asher: Mmm.

1:16:01

Neil Asher: And I brought it to him, and I said, what do you think this is?

1:16:04

Neil Asher: And he said, hmm, well, I haven't really seen this before, but it

1:16:07

could be this gene, this gene, this gene, et cetera.

1:16:10

Neil Asher: He said, but here's...

1:16:11

Neil Asher: Oh, there it is.

1:16:12

Neil Asher: There it is.

1:16:13

Neil Asher: Yeah.

1:16:14

Neil Asher: And so, yeah.

1:16:17

Neil Asher: It looks weird, doesn't it?

1:16:18

Neil Asher: Super.

1:16:19

Neil Asher: And so, um, so the expert told me, okay, I need this view of an x-ray,

1:16:27

this view, this view, this view.

1:16:29

Neil Asher: And so we got that and he came back and he said, okay, well, you

1:16:31

know, we need to get some DNA sequencing, he said.

1:16:34

Neil Asher: I said, okay.

1:16:35

Neil Asher: So we got a piece of the bone from actually the rib, and the rib

1:16:39

was important to use because that would be, I felt, an area that would be least

1:16:44

likely to be contaminated by bacterial, you know, degradation.

1:16:49

Neil Asher: And so I got a little bit of bone marrow out and I did the

1:16:51

sequencing.

1:16:52

Neil Asher: Long story short, I had to bring in, once I'd done that, there was

1:16:57

a lot of DNA that didn't make sense, but it was, it's old DNA.

1:17:00

Neil Asher: It wasn't that old actually, but it was degraded.

1:17:03

Neil Asher: So I had to bring in experts at Stanford who knew how to fix the

1:17:07

degradation.

1:17:08

Neil Asher: And then I had to bring in an expert in South American genetics,

1:17:12

who also happened to be at Stanford.

1:17:14

Neil Asher: And then we brought in a team of students, and then I brought in Roche

1:17:19

Diagnostics.

1:17:21

Neil Asher: I had sold a sequencing company to Roche about two, a few years

1:17:26

earlier.

1:17:27

Neil Asher: So I brought in the team that actually knew how to help me assemble

1:17:31

the genome.

1:17:32

Neil Asher: And then we published a paper which said it's human, it was a

1:17:38

female, and here are some mutations that it might, that might explain what it

1:17:42

looked like.

1:17:43

Neil Asher: They did have some mutations in gene.

1:17:45

Neil Asher: And then the UFO community hated me because I had disproven that as

1:17:51

not being a baby, not being an alien.

1:17:55

Neil Asher: But of course, that picture that you showed, I mean, it was

1:17:58

worldwide news, and literally the title of one of the things is Stanford Scientist

1:18:03

Sequences Alien Baby.

1:18:04

Neil Asher: And so, you know, and so, but the paper stands the test of time.

1:18:13

Neil Asher: Nobody's disproven what it is that I showed, despite the fact that

1:18:16

some people want to say that I was a CIA plant and I was paid off by the CIA,

1:18:20

etc.

1:18:20

Neil Asher: Of course.

1:18:21

Neil Asher: But what that had done was, that I didn't realize, but I kind of

1:18:26

hoped, was that it sent up a flag to a scientific community that already

1:18:32

existed that I wasn't aware of, of scientists who were deeply involved with the

1:18:37

government in the analysis of UAP.

1:18:41

Neil Asher: That I wasn't privy to.

1:18:44

Neil Asher: And so, literally about a month after the movie came out about that

1:18:51

thing.

1:18:53

Neil Asher: I got a knock at my door.

1:18:55

Neil Asher: And it was representative of the CIA and an aerospace company.

1:18:59

Neil Asher: Unannounced.

1:19:00

Neil Asher: And they said, we want to talk to you.

1:19:03

Neil Asher: And they wanted my help with a number of military and diplomatic

1:19:09

personnel who'd been, they claimed, harmed by things.

1:19:15

Neil Asher: They'd either heard stuff, etc.

1:19:17

Neil Asher: And long story short, the majority of the hundred or so people that

1:19:22

I had privy to their medical records ended up being the first of the Havana

1:19:27

syndrome patients.

1:19:29

Neil Asher: They'd heard things in their head, etc.

1:19:33

Neil Asher: But what they had done was they had shown me the data literally

1:19:36

that day in my office.

1:19:38

Neil Asher: They brought out the MRIs.

1:19:39

Neil Asher: They brought out the x-rays and the damage in the brain, etc.

1:19:42

Neil Asher: That was clear.

1:19:43

Neil Asher: I mean, it wasn't, it was not just data.

1:19:46

Neil Asher: It was evidence that something had happened.

1:19:48

Neil Asher: It wasn't somebody's story.

1:19:50

Neil Asher: It was evidence that was repeatable.

1:19:53

Neil Asher: And so that took us about three or four years to figure out what

1:19:57

they were.

1:19:58

Neil Asher: And it was at about the time that actually the Havana events were

1:20:02

occurring that we realized that all the symptoms of what it is that we were

1:20:05

seeing in this group of patients were matching what it was that the Havana

1:20:10

syndrome individuals had.

1:20:11

Neil Asher: So, in a way, that was good because that meant that those 90 or so

1:20:17

patients who matched, we could hand over to the national security people.

1:20:22

Neil Asher: And, you know, it became a real thing.

1:20:24

Neil Asher: And now there's like a DOD website that has anomalous health

1:20:27

incidents where people can come forward and report the stuff that they've got.

1:20:32

Neil Asher: And here's the ways you can use the Veterans Administration to seek

1:20:35

medical help.

1:20:36

Neil Asher: Whereas previously, they'd been shooed away as we don't want to

1:20:39

hear about this.

1:20:40

Neil Asher: What do they think it is?

1:20:41

Neil Asher: It's an energy weapon of some kind, a microwave or other energy or

1:20:45

gamma energy weapon.

1:20:46

Neil Asher: And that sounds, okay, that sounds crazy, except no one would admit

1:20:50

or no one would deny that we have the capability to do it.

1:20:53

Neil Asher: It's basically, if you take the front off your microwave and turn

1:20:57

it on and put your face near it, you'll get burned.

1:21:00

Neil Asher: So, this is just a way to direct the microwaves or sound waves.

1:21:04

Neil Asher: At specific individuals.

1:21:05

Neil Asher: At specific individuals.

1:21:06

Neil Asher: And do you think it was experimental?

1:21:09

Neil Asher: No.

1:21:10

Neil Asher: No.

1:21:11

Neil Asher: So, these are targeted people with specific intention to get those

1:21:13

people because they had some function that they wanted to...

1:21:17

Neil Asher: They wanted to get them out of the way.

1:21:19

Neil Asher: Oh, because they were in Havana.

1:21:21

Neil Asher: Because they were in Havana.

1:21:22

Neil Asher: Right.

1:21:23

Neil Asher: But it's been used all over the world.

1:21:24

Neil Asher: You know, I still get emails from military personnel saying this

1:21:28

and this and this happened to me.

1:21:30

Neil Asher: Here's my medical records.

1:21:32

Neil Asher: And so, now I just...

1:21:34

Neil Asher: I know...

1:21:35

Neil Asher: They know that I'm a safe place to approach because then I know

1:21:39

where to send them on the inside.

1:21:42

Neil Asher: But what was interesting was that once we had set that aside and I've

1:21:45

advised the Senate Intelligence Committee and I've advised them...

1:21:49

Neil Asher: A house on things, I wrote a white paper for them years ago on what

1:21:54

I thought needed to be done.

1:21:56

Neil Asher: But what was interesting were the remaining 10 people who had, you

1:22:01

know, who didn't have Havana Syndrome but had a series of other problems.

1:22:06

Neil Asher: And several of them had said that part of their problem was

1:22:09

initiated because they'd come in contact with what they had claimed to be a UFO.

1:22:14

Neil Asher: By the way, I just noticed that you have a UFO on the wall behind

1:22:16

you.

1:22:17

Neil Asher: Yeah.

1:22:18

Neil Asher: We're all in over here.

1:22:20

Neil Asher: That...

1:22:21

Neil Asher: So that got me introduced to what, you know, people like Jacques

1:22:28

Vallée, who you've had on the show, I think.

1:22:31

Neil Asher: Yes, a couple times.

1:22:32

Neil Asher: Great guy.

1:22:33

Neil Asher: Great.

1:22:34

Neil Asher: He became my mentor who essentially took me out of the wilderness.

1:22:38

Neil Asher: I could have gone down 20 different rabbit holes.

1:22:41

Neil Asher: And he lives in San Francisco and we would meet regularly and we

1:22:45

still meet regularly.

1:22:47

Neil Asher: And he basically gave me a formulation of how to think about this

1:22:53

that I never would have been able to get from 20 different, you know, or 100

1:22:58

YouTubes or what have you.

1:23:00

Neil Asher: And introduced me to the right people.

1:23:02

Neil Asher: That eventually led me to meet Lou Elizondo.

1:23:05

Neil Asher: And I actually, two weeks before that article came out in the New

1:23:09

York Times, met Lou in Crystal City overlooking the Pentagon and he showed me

1:23:13

the videos that were about to come out.

1:23:16

Neil Asher: And that was my first time that I had met him.

1:23:18

Neil Asher: And through all of them, I met Dave Grush and Carl Nell and Dave

1:23:21

and I are in regular contact.

1:23:23

Neil Asher: And I'm, you know, I mean, I just want to say up front, I hope that

1:23:27

the Trump administration understands the value of what David can bring to them

1:23:33

and put him in a position of authority that gives him not the ability

1:23:38

necessarily to make decisions, but to give the necessary information to the

1:23:42

right people.

1:23:43

Neil Asher: Because I think there's great commercial value here that is being

1:23:48

missed, not just the are we alone, etc.

1:23:52

Neil Asher: I think there's extraordinary commercial value.

1:23:55

Neil Asher: I mean, imagine a civilization that's a million years ahead of us.

1:23:59

Neil Asher: How many technology revolutions allow these objects to move as we

1:24:06

clearly see something motivating itself or maneuvering around the atmosphere?

1:24:11

Neil Asher: Right.

1:24:12

Neil Asher: So if we could scrape just the tiniest bit of understanding off of

1:24:16

the top of that, what would that do to change our own civilization?

1:24:21

Neil Asher: I mean, silicon, a grain of sand, makes us who we are today.

1:24:25

Neil Asher: Everything that is, that's around me right here is all run off of

1:24:29

silicon.

1:24:30

Neil Asher: Right?

1:24:31

Neil Asher: Right.

1:24:32

Neil Asher: Compute.

1:24:33

Neil Asher: But imagine that there's other inventions, other ways of

1:24:36

manipulating reality that we don't appreciate yet because our physics just isn't

1:24:40

there yet.

1:24:41

Neil Asher: If we can understand that.

1:24:43

Neil Asher: So the government might say, well, we need to keep this behind

1:24:47

closed doors for weaponization or we don't want to disrupt energy production or

1:24:51

what have you.

1:24:52

Neil Asher: That's fine.

1:24:54

Neil Asher: But maybe there's too much secrecy and that maybe that there's an

1:24:58

aspect of that that could be taken advantage of.

1:25:01

Neil Asher: So Carl Nell and I have gotten in positive arguments about this,

1:25:06

about that, well, it's not black and white that we keep something secret or we

1:25:11

put it into the public domain.

1:25:12

Neil Asher: Maybe there's a middle domain where you have a public private

1:25:15

partnership opportunity and actually that's now, Carl has now adopted this, at

1:25:20

least in part, that maybe companies come to the fore or investment form places

1:25:27

come to the fore where they will put money in as options to fund, let's say,

1:25:33

public scientists to come in behind the scenes with the right levels of clearances

1:25:36

to study stuff that would propel society forward again.

1:25:40

Neil Asher: But this is assuming two things.

1:25:43

Neil Asher: One, that we have actually recovered these things.

1:25:46

Neil Asher: Right.

1:25:47

Neil Asher: And then another one is that it's from a society from somewhere

1:25:51

else that's far more advanced than we are today.

1:25:55

Neil Asher: Right.

1:25:56

Neil Asher: Which might not be correct.

1:26:01

Neil Asher: It might not be that it's from somewhere else.

1:26:05

Neil Asher: It might be that it's from somewhere here.

1:26:08

Neil Asher: Mm-hmm.

1:26:09

Neil Asher: Or a dimension that we don't have access to.

1:26:13

Neil Asher: Right.

1:26:14

Neil Asher: Right.

1:26:15

Neil Asher: Yeah.

1:26:16

Neil Asher: This is assuming that all this stuff is real.

1:26:17

Neil Asher: Right.

1:26:18

Neil Asher: But when you're talking about the government and back engineering

1:26:19

of things, like, so the big argument, this is the narrative, the big argument

1:26:24

has been that they have recovered these things and that these things are now in

1:26:28

the hands of defense contractors.

1:26:30

Neil Asher: And that there's been misappropriation of funds, lying to Congress,

1:26:34

and it's always going to stay secret because if it didn't, everybody would go

1:26:38

to jail and everyone would get sued.

1:26:40

Neil Asher: Yeah.

1:26:41

Neil Asher: Right?

1:26:42

Neil Asher: Is that fair?

1:26:43

Neil Asher: Yeah.

1:26:44

Neil Asher: I mean, that's fair.

1:26:45

Neil Asher: I mean, but I would say amnesty would be one way to...

1:26:47

Neil Asher: This is...

1:26:48

Neil Asher: Were you in the Age of Disclosure documentary?

1:26:50

Neil Asher: Briefly, yes.

1:26:51

Neil Asher: Yeah.

1:26:52

Neil Asher: Okay.

1:26:53

Neil Asher: Which I thought was very good.

1:26:54

Neil Asher: Very good.

1:26:55

Neil Asher: And I can't wait for that to come out.

1:26:56

Neil Asher: How can I see it?

1:26:57

Neil Asher: I don't know how you can see it.

1:26:58

Neil Asher: Yeah.

1:26:59

Neil Asher: It's not out yet.

1:27:00

Neil Asher: Yeah.

1:27:01

Neil Asher: And I don't know why.

1:27:02

Neil Asher: Whoever it is, go Netflix.

1:27:03

Neil Asher: Yo, Ted, go buy that.

1:27:04

Neil Asher: Yeah.

1:27:05

Neil Asher: It's really good.

1:27:06

Neil Asher: Yeah, exactly.

1:27:07

Neil Asher: It's really good.

1:27:08

Neil Asher: It's a great show.

1:27:09

Neil Asher: I mean...

1:27:10

Neil Asher: Yeah.

1:27:11

Neil Asher: And it has a number of officials.

1:27:12

Neil Asher: And I think I sent you guys some of the videos basically coming

1:27:13

forward.

1:27:14

Neil Asher: I mean, you know, Marco Rubio, our current Secretary of State.

1:27:17

Neil Asher: Yeah.

1:27:18

Neil Asher: I mean, you saw him.

1:27:19

Neil Asher: Yeah, he's in it.

1:27:20

Neil Asher: He's in it like for like 10 minutes saying some remarkable things.

1:27:22

Neil Asher: You know, Senator Rounds, you know, you name it.

1:27:25

Neil Asher: More recently, Tulsi Gabbard.

1:27:26

Neil Asher: Yes.

1:27:27

Neil Asher: Coming out and saying, "Well, there's something going on."

1:27:29

Neil Asher: I think one of the most fascinating things is Hal Puthoff's

1:27:33

descriptions,

1:27:33

of descriptions rather, of what happened during the Bush administration,

1:27:37

Herbert Walker Bush.

1:27:38

Neil Asher: Right.

1:27:39

Neil Asher: So in, I believe it was 1990, they came to Hal Puthoff and a bunch

1:27:44

of other experts

1:27:45

and said, "We would like you to, we want a numerical value placed on all the

1:27:53

positives and the negatives

1:27:55

of disclosure because we have required, we have acquired these crafts from

1:28:01

somewhere else.

1:28:02

We believe they're not of this world and we have not made them.

1:28:07

And we're talking about letting the general public know."

1:28:10

Neil Asher: Right.

1:28:11

Neil Asher: And while they overwhelmingly said that the positives were dwarfed

1:28:15

by the negatives.

1:28:15

Neil Asher: Right.

1:28:16

Neil Asher: The negatives being banking, religion, government, societal

1:28:20

structure, everything

1:28:21

would fall apart if we knew we weren't alone.

1:28:23

Neil Asher: Not only were we not alone, but something is infinitely more

1:28:26

sophisticated than

1:28:27

us and might be responsible for us being here in the first place.

1:28:32

Neil Asher: In the first place.

1:28:33

Neil Asher: Right.

1:28:34

Neil Asher: Which is, that's where it gets super squirrely.

1:28:35

Neil Asher: Right, right.

1:28:36

Neil Asher: Well, you could imagine-

1:28:37

Neil Asher: The Book of Enoch and there's a lot of-

1:28:39

Neil Asher: I mean, I think it's a little bit overwrought as to what humanity's

1:28:46

reaction

1:28:46

will be.

1:28:47

Neil Asher: People are more worried today about putting food on the table than

1:28:49

they would be about,

1:28:51

you know, ethereal or supposed aliens.

1:28:55

Neil Asher: I mean, they would mostly, I think, on the assumption that they're

1:28:59

not going

1:28:59

to basically show up at your local Walmart and start, you know, interacting

1:29:04

with you.

1:29:05

Neil Asher: I think the fact of revealing that we're not alone is actually more

1:29:09

of a hopeful

1:29:10

thing to me, because, you know, how many TV shows right now are about the

1:29:14

apocalypse?

1:29:15

Neil Asher: Right.

1:29:16

Neil Asher: Of a thousand different varieties?

1:29:18

Neil Asher: Yeah.

1:29:19

Neil Asher: Wouldn't it be nice to know that somebody got beyond it?

1:29:21

Neil Asher: Yes.

1:29:22

Neil Asher: That there's not a cliff that we all have to walk over?

1:29:24

Neil Asher: Right.

1:29:25

Neil Asher: And if so, how do we not walk over the edge of the cliff?

1:29:27

Neil Asher: I mean, that to me is a hopeful outcome.

1:29:30

Neil Asher: Now, Hal and Eric and all the people are all good friends.

1:29:33

Neil Asher: Hal is probably, for all of the things that he says positively, is

1:29:38

probably

1:29:38

the tightest clam I've ever met in terms of making sure that he doesn't go over

1:29:44

the line.

1:29:44

Neil Asher: Yeah, he knows too much.

1:29:45

Neil Asher: Yeah.

1:29:46

Neil Asher: That's the thing.

1:29:47

Neil Asher: He has to be very careful who he's talking to and what he says.

1:29:49

Neil Asher: Yeah.

1:29:50

Neil Asher: I like to mind-meld him the Spock thing where you find all the

1:29:53

information.

1:29:54

Neil Asher: But it's people like him and Jacques and Kit Green and a number of

1:30:00

others.

1:30:00

Neil Asher: And I sat around a table with them for several years, like every

1:30:04

twice a year.

1:30:05

Neil Asher: And I looked around the table and thought, the things that these

1:30:08

people know

1:30:09

Neil Asher: or claim to know, I want to know.

1:30:15

Neil Asher: And the opportunity that's here and why can't we get this

1:30:19

information out if

1:30:21

it's real?

1:30:22

Neil Asher: And so rather than arguing with people about the matter, that's,

1:30:27

for instance,

1:30:28

Neil Asher: why I created the Sol Foundation, which is a charitable group of

1:30:32

academics.

1:30:33

Neil Asher: I started it with David Grush and Peter Scafisch.

1:30:36

Neil Asher: David, of course, had to leave because he had governmental

1:30:40

responsibilities he wanted

1:30:41

to go take care of.

1:30:42

Neil Asher: And actually, we've now had for three years in a row a symposium,

1:30:48

first at Stanford,

1:30:50

and then at San Francisco, and the next one is now in Italy.

1:30:55

So I'm going to plug it, sol2025.org.

1:30:57

Neil Asher: Okay.

1:30:58

Neil Asher: You can go look if you want to go to Monica.

1:30:59

Neil Asher: Sol, S-O-L?

1:31:00

Neil Asher: S-O-L, as in the sun.

1:31:02

Neil Asher: 2025.org.

1:31:03

Neil Asher: .org.

1:31:04

Neil Asher: And the purpose of that was not to advocate that any of this is

1:31:09

real, but was

1:31:10

to create an environment within which academics or professionals or just lay

1:31:16

people interested

1:31:18

in the subject matter could come and talk about it in a very professional

1:31:21

manner.

1:31:21

Right?

1:31:22

Just to bounce around ideas, not to advocate for, you know, they're here or

1:31:27

they're reptilians

1:31:28

or they're this or they're that, but to like some of the things you raised,

1:31:32

what are the

1:31:34

ethical issues?

1:31:35

What are the religious issues?

1:31:37

Neil Asher: So we have put out a number of white papers, for instance, where we

1:31:40

had a member

1:31:41

of the Catholic hierarchy write a paper on the issues related to Catholicism

1:31:47

and religion.

1:31:48

We've had Timothy Gallaudet, who's actually on our advisory committee, talk

1:31:52

about USOs

1:31:53

and those issues.

1:31:54

We've talked about near space issues.

1:31:58

Peter is running a study on experiencers.

1:32:02

Not that the experiences are necessarily real, but what are the kinds of psychosocial

1:32:10

matters

1:32:11

that need to be considered for people who say that this has happened to them?

1:32:16

So there's a group in the UK called Unhidden, which is basically a bunch of

1:32:21

psychiatrists,

1:32:22

a group of professional psychiatrists who say, "Okay, well, there's a trauma

1:32:26

associated with

1:32:27

this."

1:32:28

Whether it's real or not, we don't know.

1:32:30

But what are the kinds of rules that we should or provisions that we should

1:32:36

provide to the

1:32:37

public and to psychiatrists?

1:32:38

So when somebody shows up at your doorstep, you know, in therapy and says this,

1:32:44

you don't,

1:32:45

you shouldn't immediately reach for the anti-hysteria or schizophrenia drugs.

1:32:51

Right, right.

1:32:52

I was lucky enough in my neighborhood, our next door neighbor, who moved in for

1:32:56

a while,

1:32:57

was the chair of psychiatry at Stanford.

1:33:00

And so we go over to have dinner with her and her husband.

1:33:03

And you know, like one of the first things that she says, "Hey, what do you do,

1:33:07

blah,

1:33:07

blah, blah."

1:33:08

And I happened to mention the UFO thing and she just sort of like sat back in

1:33:11

her seat.

1:33:12

Okay.

1:33:13

Oh, you might be a kook.

1:33:15

Okay.

1:33:16

But it wasn't, but it took, you know, a year or so until she finally realized

1:33:20

that

1:33:20

I wasn't and then I was approaching this from a very scientific manner.

1:33:24

I had my beliefs as to what I think it is that I'm dealing with and that there

1:33:28

is some

1:33:28

sort of reality to this.

1:33:31

But that's separate than the scientist in me that says, "Well, if I want to

1:33:36

talk about

1:33:36

this scientifically, here are the things that I need to prove or disprove."

1:33:39

So that has led, for instance, to my production or study of materials that

1:33:44

Jacques Vallée had

1:33:46

brought to me, some metals and other things that had chains of evidence

1:33:50

associated with

1:33:51

them being at some UIP or UFO landing.

1:33:56

And so, interestingly, some of these metals are very unusual.

1:34:01

Super high purity silicon, strange magnesium ratios, the isotope ratios are

1:34:07

wrong, et cetera.

1:34:09

Now, that's not proof of anything, but it's proof that somebody engineered them.

1:34:13

So it's that plus the medical, those are the kinds of reality-based tests that

1:34:21

I can do to provide

1:34:23

to my colleagues to say, here is data and evidence.

1:34:27

Evidence isn't proof of evidence of anything.

1:34:30

Evidence like in a court of law is just evidence that you provide to the jury

1:34:35

of peers.

1:34:35

Right.

1:34:36

Right?

1:34:37

So, but I sort of have gone a step further.

1:34:41

And that is, I'm like, okay, well, if these things are, let's say we get some

1:34:45

advanced material.

1:34:48

How do I prove that this advanced material was made by some superior intellect?

1:34:55

Well probably the atomic positioning of how the material is made is going to be

1:34:58

more advanced

1:34:59

than even our most advanced computer chip.

1:35:02

So how do you determine that when you need some sort of atomic imager that

1:35:07

might tell you

1:35:08

where the positions of the atoms are and what the bond structures are that you

1:35:12

say, well,

1:35:14

that's something I can measure and I can have, I can give those results to

1:35:17

somebody else and

1:35:18

they can say, yes, it's right or it's not.

1:35:20

But at least I can say no human at least that I know of could make this.

1:35:25

So I started a company that I've raised money for with this new idea that I

1:35:28

have for how

1:35:29

to make an atomic imager and we're doing it.

1:35:33

And so, you know, we've raised the money, we're building it already.

1:35:37

And I know it will work.

1:35:38

So when I have it, whether or not it's useful for looking at UAP materials is

1:35:43

almost immaterial

1:35:44

because I know how useful it will be for the nanomaterials, the metamaterials,

1:35:50

the alloys

1:35:50

that the government, et cetera, uses for biology, et cetera.

1:35:54

So rather than predicting what a protein structure or a DNA or a chromosome arm

1:35:59

looks like, I'll

1:36:00

be able to read its structure directly.

1:36:03

Mm.

1:36:04

I want to bring you back to the, you said it was 10 people that didn't have Havana

1:36:08

syndrome,

1:36:09

that they had some sort of an injury that was associated with a UAP event.

1:36:12

What was their thing?

1:36:13

Did they have an implant or was there a...

1:36:16

No, some of them had like, they had what you would call white matter disease in

1:36:22

their brain,

1:36:23

like they had been exposed to something.

1:36:25

So white matter disease, if you have, for instance, multiple sclerosis and you

1:36:29

look in the brain

1:36:30

with MRI, you'll see these white areas which are basically dead tissue, scar

1:36:35

tissue.

1:36:36

They had things like that.

1:36:39

One person, one of the pictures that I had was that they had claimed to have

1:36:44

seen something

1:36:45

in their backyard.

1:36:46

They shone a flashlight at it.

1:36:47

And the moment they did, they got zapped.

1:36:51

And then you see the picture of the guy in the back of his neck, this huge welt

1:36:58

and a bruising

1:36:59

and a scarring that could...

1:37:04

There's no reasonable way you could have gotten something like that just by

1:37:10

exposing yourself

1:37:11

to a flame as a, for instance, or a blow torch.

1:37:17

And so it's these kinds of events that...

1:37:19

And the unfortunate issue with these is that they're not repeatable.

1:37:23

They're one-off anecdotes.

1:37:24

Right.

1:37:25

And you certainly can't put a person in a place where they become bait for

1:37:31

these kinds

1:37:32

of events to occur.

1:37:35

And so you're sort of...

1:37:36

Some people would volunteer for that, though.

1:37:39

Somebody might, yeah.

1:37:40

To go get zapped.

1:37:41

Do you know about the Travis Walton story, right?

1:37:43

Very much, yeah.

1:37:44

Yeah.

1:37:45

What do you think of that?

1:37:46

He's kept to his story over all of the years.

1:37:49

That's what's so confusing.

1:37:51

Yeah.

1:37:52

I mean, he's had no reason.

1:37:53

I don't know that he's profited off of it.

1:37:55

He, you know, I find it fascinating, you know, but it's, it's, it's, it's the

1:38:02

irreproducibility

1:38:04

of the events that the skeptics, I call them more pseudo skeptics, they're pseudists,

1:38:11

like

1:38:12

nudists, they're pseudists, they're pseudists that use these one-offnesses of

1:38:17

these events

1:38:18

to disparage the entire, you know, idea of it.

1:38:22

It sounds ridiculous.

1:38:23

Well, of course it sounds ridiculous because you're talking about something

1:38:27

that is outside

1:38:27

of...

1:38:27

It's a spaceship that zaps people.

1:38:29

Yeah, that's ridiculous.

1:38:30

You know, and, and I don't think that even he would propose, Travis, that he

1:38:36

was purposefully

1:38:37

hurt.

1:38:37

Right.

1:38:38

I mean, if you walk across an airfield and get in the plume of a jet engine,

1:38:43

you're going

1:38:44

to get hurt.

1:38:45

Right.

1:38:46

You know.

1:38:47

Yeah.

1:38:48

And his story is that he was taken aboard to heal him.

1:38:50

Yeah.

1:38:51

There was something, something happened to him during that event.

1:38:53

And, but the crazy part is that all the other people that are in the truck,

1:38:57

they witnessed

1:38:57

it and then they passed polygraph examinations.

1:38:59

Right.

1:39:00

Right.

1:39:01

They also told the same story independently when they took them and separated

1:39:05

them.

1:39:05

And then Travis Walton shows up five days later with the same clothes on.

1:39:08

Right.

1:39:09

With this crazy story.

1:39:10

Right.

1:39:11

You know, so when people say that, you know, there's no evidence or where's the

1:39:14

evidence?

1:39:15

My first question to them is, well, what have you, have you read any books

1:39:18

about any of this?

1:39:19

Do you, have you spent even a moment looking into it?

1:39:23

And, you know, I would point them at books like by Robert Powell and Michael Swords,

1:39:27

UFOs

1:39:28

in Government, which is not a proposal that any of this is real.

1:39:33

It's just the story of these events over decades.

1:39:37

And so there's, there's books like that, dozens of them that tell the story of

1:39:43

data and evidence.

1:39:45

How you contextualize it is, you know, up to your personal biases, let's say,

1:39:50

but there's

1:39:51

plenty of evidence.

1:39:52

But if people haven't looked into it, if they have an opinion about it and they

1:39:56

haven't looked

1:39:57

into it, they're more like priests than they are scientists.

1:40:03

Yeah, that's, it's also the public, the general public narrative is UFO equals

1:40:09

kook.

1:40:10

Right.

1:40:11

You're a kook.

1:40:12

You believe in that?

1:40:13

That's ridiculous.

1:40:14

That's ridiculous.

1:40:15

And, and I don't believe in anything.

1:40:16

I believe in the data and the evidence and, and the evidence, there's not

1:40:20

enough evidence

1:40:21

for me to tell a colleague of mine it's real.

1:40:24

Right.

1:40:25

But there's enough evidence for me to say there's a question worth answering.

1:40:27

So when you were talking about magnesium and these, whatever these alloys are,

1:40:33

what is

1:40:34

specifically wrong with them that you don't think that it was manufactured by

1:40:40

like a standard

1:40:42

sort of a alloy plant in the United States or somewhere else?

1:40:45

Right.

1:40:46

So the, so the silicon that I'm talking about is from an event in Ubatuba,

1:40:51

Brazil,

1:40:52

which interestingly, there's another piece of it that appears to have been

1:40:56

magnesium, but

1:40:57

both of them are of a purity that is unusual for the day in the late 1950s.

1:41:04

So the magnesium, and I did an atomic mapping of my piece of silicon down to a

1:41:10

level of where

1:41:11

it's like 99.999% silicon.

1:41:15

And so one piece of it had magnesium ratios that were earth normal.

1:41:23

And these are, these were impurities, let's say.

1:41:26

The other piece were way off earth normal.

1:41:30

So for instance, anywhere on earth, if you look at the ratios of what the three

1:41:35

magnesium

1:41:36

isotopes are, 24, 25, 26, it should be like 80%, 11%, 9% more or less.

1:41:44

And anywhere in our solar system, that's more or less what the values should be

1:41:49

of the ratios.

1:41:50

And that has to do with stellar evolution and how, you know, radioactive

1:41:57

compounds might decompose

1:41:59

to whatever.

1:42:01

But we got this, we got this ratio that was just way, way off.

1:42:04

So by luck, I came across a postdoc at Stanford.

1:42:13

And he and a graduate student, they're both in applied physics, who are

1:42:16

interested in UAP.

1:42:17

And I said, I've got these ratios, what do you think it means?

1:42:21

And so they looked, so they looked at the ratios and the weird one.

1:42:25

And they said, well, let me, let's do some calculations.

1:42:28

And so it turns out that the ratios that we have could have been generated from

1:42:36

normal magnesium

1:42:38

ratios.

1:42:39

If you exposed normal magnesium ratios to a neutron source for 900 years at the

1:42:45

level of an atomic

1:42:47

bomb every few seconds.

1:42:49

Okay.

1:42:50

So, so you, they, yeah.

1:42:52

Wow.

1:42:53

So, so it's like, I'm looking, and this, this data is literally two weeks old,

1:42:58

but the calculations

1:43:00

are, are, are math.

1:43:01

So you're like, okay, well, where and how, you know, the, the chance of getting

1:43:08

that number

1:43:09

correct on three things is low, you know, to put it mildly, but to say that you

1:43:18

had exposed

1:43:20

these things to that kind of a neutron source means something interesting,

1:43:26

right?

1:43:26

So again, it doesn't prove anything other than that.

1:43:30

The result is mathematically and materially true.

1:43:35

So what does it, what does it mean again?

1:43:38

It's just, it just for a scientist like me who loves data off the curve, it's

1:43:43

catnip.

1:43:45

I can't help myself, but want to know and understand more about it.

1:43:49

Yeah.

1:43:52

I mean, just what you said is what you said about the magnesium ratios.

1:43:58

Like that's, has there ever been any debunkers that have some sort of a, an

1:44:03

explanation for

1:44:04

why you would find that?

1:44:06

No.

1:44:07

I mean.

1:44:08

Do they think that your measurements are off?

1:44:09

Well, I mean, the only way, I mean, you could create that ratio artificially by

1:44:14

purifying

1:44:15

each of those isotopes and then pre-mixing them to that ratio.

1:44:19

But why you would blow it up over a beach in Ubatuba, Mexico in the late 1950s,

1:44:25

and then

1:44:26

let it sit in a museum in Argentina for 50 years until Jacques Vallée ended up

1:44:31

going and

1:44:31

grabbing a piece of it and bringing it to me in a measure on an instrument in

1:44:34

the engineering

1:44:35

department at Stanford.

1:44:38

Why?

1:44:39

Could you do it physically back then?

1:44:42

Would that be possible in the 1950s?

1:44:43

It would have been very hard.

1:44:45

It would have been very, very hard.

1:44:46

You could, but in the late 1950s, we were still busy trying to isolate and

1:44:56

separate uranium isotopes

1:44:58

for making more bombs.

1:44:59

I mean, let's be serious.

1:45:02

What do humans separate isotopes for?

1:45:05

To make bombs or to do health-related tagging, which is really only something

1:45:11

that came to

1:45:12

the fore in the '60s and '70s.

1:45:14

And this predates that by a decade.

1:45:16

It predates it.

1:45:17

So it's unusual.

1:45:19

It's possible.

1:45:21

But I mean, again, with any of these things, why, for instance, would one of

1:45:27

the supposed pieces

1:45:28

that came from that event of be magnesium at a level of purity that only Dow

1:45:34

Chemical at

1:45:35

the time had the ability to create.

1:45:39

Now, what else was at this site and what is the story behind this site?

1:45:44

A fisherman sees this glowing object that kind of released something which then

1:45:51

exploded

1:45:51

and he picked up pieces of it.

1:45:54

And there's some chains of evidence of how it got to either a newspaper in

1:46:00

Brazil or to

1:46:01

this South American museum, et cetera, and different studies have been done by

1:46:06

different people

1:46:08

over time.

1:46:09

And the surprise to me was that the piece that I had was silicon, whereas the

1:46:14

lore was

1:46:14

that it was magnesium.

1:46:16

So I've been in contact with the people who talk about it as being magnesium

1:46:19

and saying,

1:46:20

well, it's, you know, your results don't dispute mine.

1:46:25

It just says that maybe there was something different.

1:46:27

Is that him there?

1:46:29

Travis Walton.

1:46:30

That's Travis?

1:46:31

Yeah, that's Travis.

1:46:32

Travis Bobblehead.

1:46:33

He gave me this.

1:46:34

That's cool.

1:46:35

So, you know, I don't know what it means.

1:46:39

I mean, I published probably one of the first peer review papers on a UAP

1:46:44

material from an

1:46:45

event in Council Bluffs, Iowa.

1:46:49

And the event was an object is seen rotating, lights flashing, et cetera.

1:46:55

Something appears to drop from the object.

1:46:57

The police saw it, several other groups saw it in the 1970s.

1:47:02

They all converged on the locale.

1:47:05

And this was like in February or something, it was winter.

1:47:08

And there was this big pile of molten metal in the middle of this field,

1:47:12

probably 30, 40

1:47:14

pounds of it.

1:47:15

And people tried to explain it away as, well, the helicopter had a giant vat of

1:47:19

molten metal.

1:47:21

And then you calculate how far and how big a container you would have to have

1:47:25

to carry

1:47:26

molten metal of this type.

1:47:27

And so I analyzed it with a device that we invented in my lab actually called

1:47:35

multiplex ion beam imaging, which is a kind of what's called secondary ion mass

1:47:39

spec, which what

1:47:40

you do is you shoot a beam of ions at an object like a sand blaster.

1:47:44

It ionizes the material on the target.

1:47:45

And then you shoot off and measure the mass of the objects that you just sandblasted

1:47:52

off.

1:47:54

And so what we found was nothing unusual in terms of isotope ratios, except we

1:47:58

found a mixture of metals that depending on where you looked in the sample was

1:48:04

different.

1:48:05

So it would be like iron, titanium and chromium of a certain ratio here, but a

1:48:10

different ratio of those things over there and over here.

1:48:12

So what that meant was that whatever this stuff was, didn't come completely

1:48:19

premixed, wasn't like a milkshake, it was a slurry of partially mixed materials

1:48:25

that somebody decided to drop off.

1:48:28

So again, this is just data, but my purpose of publishing it was first, and

1:48:35

this was published in the Progress in Aerospace Sciences, peer reviewed.

1:48:39

The purpose was to show you're not going to get thrown out of the academy for

1:48:44

publishing this stuff, as long as you don't make crazy conclusions and you just

1:48:50

say, here's the data, to show people that you can publish this stuff as long as

1:48:55

you're scientifically careful in how far you go.

1:48:59

You leave yourself plenty of diplomatic exits in the verbiage that you use.

1:49:04

And it was part of what then got me to start the Soul Foundation, along with

1:49:09

Dave and others, to say, look, it's okay to do this, as long as you're careful.

1:49:14

And that's why people, I mean, Avi Loeb came after me, because he had kind of

1:49:21

the same pushback from his community, where all he was doing was saying, the

1:49:26

question's on the table.

1:49:28

Well, I'm not saying it's true, it's just you can't push this off the table.

1:49:32

So he had the same kind of righteous indignation that I have that propels me to

1:49:36

say, well, I'm going to show you why you can't take this off the table.

1:49:40

So when they found this puddle of molten metal, and it's a bunch of different

1:49:45

mixtures, so it seems like there's a bunch of different stuff that was there,

1:49:50

and it wasn't perfectly mixed.

1:49:53

Is there some sort of, like, have you theorized some sort of a reason why any

1:50:00

person or any creature or any being would do that?

1:50:05

Is there something that you would extract from that kind of metal, like heating

1:50:10

it up to a certain degree and having a mixture of all these things, and this is

1:50:14

just a byproduct that they're dropping off?

1:50:16

I think it's a byproduct of some process that might, again, might, might, might.

1:50:21

Might, might, might, extract.

1:50:23

It might be part of a propellant system.

1:50:25

It might be part of the way that they generate the fields that allow these

1:50:29

things to move.

1:50:30

Again, these are all mights, it's speculation, but it's like when you see

1:50:34

something and do something that you don't understand what it is, you have to be

1:50:39

fully open.

1:50:39

I mean, for all I know, they're flushing the toilet, right?

1:50:43

Oh, boy.

1:50:43

Yeah, ew.

1:50:47

But...

1:50:48

They got metal poop.

1:50:49

So, but, but, you know, I have the original Polaroids from the police

1:50:53

department of it, so, you know, it was real, and people have said, oh, it was

1:50:57

thermite.

1:50:57

Well, if it were thermite, there'd be, there'd be aluminum oxide, you know.

1:51:02

Thermite, meaning that's how it was melted down?

1:51:03

That's how it was melted down, and it's just some kids playing around, et

1:51:07

cetera, and it was, it was a big joke.

1:51:09

Wacky kids with their thermite.

1:51:10

With their thermite.

1:51:11

You know, but it turns out there's no aluminum hydroxide or oxide, I should say,

1:51:15

in the sample.

1:51:15

I mean, I have the analysis, it's just not there.

1:51:20

It had to have been extreme heat of some kind that would produce it, and, you

1:51:24

know, whatever it was, was hovering for a moment, so it wasn't an airplane, and

1:51:28

there was no helicopters, and at least no helicopters with flashing lights, and,

1:51:33

you know, I've got, there's been huge chunks of it still exist.

1:51:37

And the amount of cauldron, and the amount of cauldron that would have to exist

1:51:43

in order to melt this would be immense.

1:51:46

It was immense, yeah.

1:51:47

So, people back in the 70s already sort of made estimates of what was required,

1:51:51

and people said, oh, it's a meteorite.

1:51:52

Well, no, we basically showed mathematically how, you know, first of all,

1:51:54

meteorites make holes when they hit the ground.

1:51:56

First of all, meteorites make holes when they hit the ground.

1:51:58

They don't melt when they hit the ground, and they make explosions.

1:52:03

Are there similar instances of something along this line?

1:52:06

Several.

1:52:07

Really?

1:52:08

Well, I think that's what's so interesting, is that worldwide there are

1:52:13

multiple reports of molten metals that get dropped off of these objects, and I

1:52:19

have actually two other ones of a molten metal that was dropped off of one case

1:52:26

in Australia and another in another area.

1:52:28

I'm not allowed to say, but it was, one actually happened supposedly, I've got

1:52:32

to find the guy again, in Fresno.

1:52:34

Maybe he's listening, that he said stuff dropped, and he has, you know, molten

1:52:40

metal that landed in a puddle in the asphalt of his driveway, and he saw this

1:52:45

object.

1:52:45

So, and he's just holding on to it?

1:52:49

He's holding on to it.

1:52:49

He reached out to me, and I, you know, was still at a time when I was just kind

1:52:53

of getting into this area, but there's many, many examples of this kind of

1:52:58

thing.

1:52:58

So, but interestingly, several of these other ones are just aluminum.

1:53:04

The one that I have is iron or whatever.

1:53:07

So, what does that tell me?

1:53:08

Does that tell me there's different kinds of ways of accomplishing the goal?

1:53:12

Whatever it is, they're either throwing something overboard or for, you know,

1:53:16

because they don't need it anymore, or because maybe it's getting in the way of

1:53:19

something and it's time to get rid of it.

1:53:22

Have you brought in anyone who's like a real expert in material sciences that

1:53:27

would, like, theorize, like, given an immense increase in technology and what,

1:53:32

like, what potentially do you think this could be?

1:53:35

The purpose of being on shows like this is to have experts maybe give me an

1:53:41

idea because the people I've been to at Stanford, you know, the other

1:53:46

professors, they're like, okay, yeah, I got to go.

1:53:51

Yeah, it could be, it could actually be detrimental to your career, and that's

1:53:55

what's really weird about something when you're just talking about data,

1:53:59

specifically in this case, an actual physical thing that anyone can measure.

1:54:04

Right, right, and I've got pieces, I've got plenty of it, you know, and the

1:54:09

original piece is, you know, is like this big that the owner of it had brought

1:54:14

to my lab just last summer again.

1:54:17

It's like big as an iMac.

1:54:18

Yeah, exactly.

1:54:19

Oh, it's huge.

1:54:19

Crazy.

1:54:20

And so, what is it?

1:54:22

I would love for somebody to tell me that it's conventional and has a purely

1:54:26

prosaic answer, because then I can go on to the next thing.

1:54:30

The whole reason for getting that, the Atacama mummy off the table was not

1:54:34

because I wanted to annoy anybody, it was because it was spectacular, it's

1:54:38

obviously something people would pay attention to, so if it's real, let's do it,

1:54:42

if it's not, let's get it off the table, because it's usually the stuff that's

1:54:45

hidden under the rubble that's the most interesting.

1:54:48

My question about that mummy is not that it's an alien, but if it does register

1:54:54

as human in the DNA, is it potentially a different kind of human than us?

1:55:00

Well, certainly she had, we brought in an expert in South American indigenous

1:55:08

people genetics, and the analysis showed that the genetic, the standard genetic

1:55:16

mutations that are found in different racial groups around the world matched

1:55:23

exactly the Atacama region of Chile.

1:55:27

So, her parents, her relatives, were clearly Chilean, so, yeah, I mean, that's

1:55:34

really all you can, that's really all you can say.

1:55:39

If someone wants to say that she's an alien, well, that's fine, I'm convinced

1:55:43

of what she is and that she deserves a proper burial.

1:55:46

And so, it's just a genetic anomaly?

1:55:48

Just a genetic anomaly.

1:55:50

I do know that you've paid attention to the Tridactyl mummies.

1:55:53

Yeah.

1:55:54

What is your take on that?

1:55:56

So, you know, I think people have conflated a lot of the different mummies that

1:56:03

are out there, first of all.

1:56:05

There's like 60 of them or something.

1:56:08

And probably a fair number of them, I wouldn't necessarily call them hoaxes.

1:56:13

I would say that they are constructed, but they're old constructs.

1:56:18

So, maybe there's some sort of homage paid to the ancestors or something like

1:56:22

that, whatever they are.

1:56:24

So, there are some ones that you clearly look at, you go, oh, come on.

1:56:28

Right.

1:56:28

That never lived.

1:56:29

Then there's the fetal position ones.

1:56:31

Then there's the fetal position ones, the big ones.

1:56:33

Yeah.

1:56:34

And I was at the beginning – I was – you know, I'm always open to being

1:56:38

wrong.

1:56:39

I was at the beginning thinking, oh, well, because of the small ones, those are

1:56:42

probably not real.

1:56:43

But then the MRIs started coming out.

1:56:45

Yeah.

1:56:45

The full body MRIs and the ligature and the bone construction and the finger

1:56:52

– and then perhaps most, I think, extraordinarily, the fingerprints on them

1:56:57

being clearly not human.

1:57:01

So, it's interesting.

1:57:03

But here's the problem, is that because there's so much circus around them,

1:57:09

unfortunately created by people who want a circus because it sells their TV

1:57:15

shows,

1:57:16

no scientist of any merit would go near it.

1:57:22

So, I was approached many times, many times to study them.

1:57:26

And I said, I'll do it on one condition.

1:57:28

Here's the money I need, not personally, but here's the money I need to do the

1:57:33

kinds of analysis to accomplish this right.

1:57:37

Second, there will be no TV cameras.

1:57:39

And you won't hear from me again until I'm ready to talk because I'll have

1:57:43

double-checked and triple-checked and quadruple-checked the results.

1:57:47

And then I've gone out, as I do with the Atacama Mummy, bringing in further

1:57:52

contiguous circles of experts to double-check me.

1:57:56

And not make it a circus.

1:57:57

And not make it a circus.

1:57:58

Because I won't name the TV show that wanted to do it, but they wanted me –

1:58:03

they wanted to follow me around with a camera.

1:58:07

And I'm like, no, this isn't how science is done.

1:58:10

I can't do it with those strictures.

1:58:12

So, I would say that if anybody's going to do it again, lock the things away

1:58:18

with South American scientists.

1:58:20

You don't need a North American scientist to come in and do it.

1:58:24

There's plenty of smart people in South America who can do this properly and

1:58:28

respect the rights of the indigenous peoples who own the sacred grounds within

1:58:32

which these things were found.

1:58:34

I think that's important.

1:58:37

And then do the analysis right.

1:58:39

You know, they've said – they made, I think, the mistake of saying, well, we've

1:58:43

done the DNA and there's a lot of DNA that doesn't match.

1:58:46

Anything – and the stuff is several hundred years old.

1:58:52

Anything that old, you won't get a lot of good DNA out of it.

1:58:55

But just – they did the same thing with the Denisovan and the Neanderthal.

1:59:00

You have to correct the chemical errors that occur over time.

1:59:06

There are ways to what's called bioinformatically correct.

1:59:09

You need to do what's called over-reading of the genome where you do so many

1:59:14

reads of it that you stack them all up line by line.

1:59:17

Like if you had a thousand versions of an ancient Bible, you would stack up the

1:59:23

lines one by one.

1:59:24

And then finally you find one line that has this letter that's correct and then

1:59:29

this one correct.

1:59:30

And then you basically do a summation of an averaging of the correctness.

1:59:35

And so they say, oh, well, there's – you know, 90% of the genome is non-human.

1:59:39

It's probably garbage.

1:59:41

It's probably these mistakes.

1:59:42

It's probably bacterial contamination that you're reading.

1:59:46

There's ways to deal with that, but that requires money and not one-off DNA

1:59:51

sequences put on the interwebs for some amateur genomicists to make a claim

1:59:56

about.

1:59:57

Right, right.

1:59:58

You know, so there's ways to do it.

1:59:59

I mean, you would want at the end of the day to get the results to the level

2:00:04

where you could go to the guys who did the Denisovan and the Neanderthal DNA,

2:00:08

the Max Planck and others who won the Nobel Prize for it, and say, hey, what do

2:00:13

you think?

2:00:15

But you don't dare take it to people like that until you've done your homework.

2:00:19

I see.

2:00:20

Yeah.

2:00:21

And you do it behind the scenes.

2:00:22

You don't put them under a flashlight.

2:00:24

Right, right.

2:00:26

You know, and people, I think, have gotten used to this click mentality of

2:00:32

impatience where I want the result today.

2:00:36

Why can't you just make it all transparent?

2:00:38

Dump all the data on the web tomorrow.

2:00:40

You're not transparent.

2:00:42

You're hiding something.

2:00:42

No, I'm not.

2:00:44

I'm just trying to make sure that you don't make the mistake and accuse me of

2:00:48

making the mistake that you'll find in the data because the raw data is never

2:00:52

clean.

2:00:53

And the Daily Mail headline is never accurate.

2:00:58

So, long story short, I think there's still something worth looking at there.

2:01:05

Well, the scans are fascinating, right?

2:01:08

Yeah.

2:01:09

The scans are the most interesting to me.

2:01:10

Have you seen the Jesse Michaels, the newest video?

2:01:13

Yeah, Jesse's a good friend.

2:01:14

He's great.

2:01:15

I love that guy.

2:01:16

And the episode that he did is fantastic.

2:01:20

And when you see the scans and they go over the bone structure of the thing and

2:01:24

you look at it, you're like, God, that looks real.

2:01:27

If that's a hoax from 1700 years ago or whoever it is.

2:01:30

Exactly.

2:01:30

Exactly.

2:01:31

Whoever, if the carbon isotope dating that they did on it is accurate.

2:01:37

I've looked at that data.

2:01:38

It looks good.

2:01:38

Okay.

2:01:39

So, then it is that old.

2:01:41

Fuck you, then.

2:01:42

Yeah.

2:01:43

Because there's no way someone back then could fake that.

2:01:46

And somebody asked me the other day, they said, well, could you have a single

2:01:49

mutation or a set of...

2:01:50

I said, no.

2:01:51

I mean, because you don't get one mutation that does all that.

2:01:54

Right.

2:01:55

You know, evolution works step by step that this does this, but it has a

2:02:01

mistake, but it's corrected by this mutation over here in evolution, which is

2:02:06

corrected by this.

2:02:07

And so, the whole, the genome fluctuates over time, compensating for the errors

2:02:12

that would otherwise have killed you.

2:02:15

Also, one of them is pregnant.

2:02:17

That's fast.

2:02:19

Yeah, I know.

2:02:19

Okay.

2:02:20

So, it's a three-foot pregnant thing that doesn't look remotely human being.

2:02:24

Yeah.

2:02:25

So, the jury is still out.

2:02:28

Right.

2:02:28

But if they're going to do it right, they need to sequester the stuff away,

2:02:32

bring in the right people with sufficient resources, and get rid of the cameras.

2:02:37

Have you talked to them?

2:02:39

Have you encouraged this?

2:02:41

Is this possible to nudge this in the right direction?

2:02:44

Where is it at right now?

2:02:45

I wrote out on Twitter a full thing of what they needed to do.

2:02:49

I mean, the easiest first milestone to do, to be honest, that could be done

2:02:54

within a couple of months, is if it is somewhere in the hominid or, let's say,

2:02:59

vertebrate line, there are metabolism genes that we all share.

2:03:05

In fact, there are metabolism genes that we share with bacteria that are very

2:03:10

similar.

2:03:11

So, there's, you probably, do you know the technique called polymerase chain

2:03:15

reaction, PCR?

2:03:15

Yes.

2:03:16

So, you know, why try to do the whole genome?

2:03:19

Why not just target a bunch of genes that we know evolve slowly, but do evolve,

2:03:28

and PCR those out?

2:03:31

Because that's easier to do than is trying to assemble a whole genome.

2:03:34

And then by having just those, let's call it preliminary sets of evidence, you

2:03:41

could then say, hmm, this actually, reproducibly, if I take a sample from the

2:03:49

finger, I take a sample from the bone marrow, I take a sample from here or

2:03:53

there on the body,

2:03:55

and I take a sample from different, the three different main things, and I see

2:03:59

the same mutations, and they're different or somehow aligned with hominid

2:04:05

evolution, right?

2:04:07

We compare it to all the known hominids.

2:04:09

I mean, that would be the kind of data that you could actually publish in a

2:04:14

journal like Nature, if you did it right.

2:04:16

Because that's the only way that you're going to get anybody to pay attention.

2:04:20

There's also the bizarre anecdotal nature of some of the artwork, like the fact

2:04:26

that these people did a lot of these tapestries and a lot of ancient artwork

2:04:32

that's a thousand years old that depicts these three-fingered things.

2:04:38

So it's like, what are they describing?

2:04:40

Are they describing these actual creatures?

2:04:42

Is there only a few of them and it was a weird genetic mutation?

2:04:47

Or is this a common visitor that they're describing?

2:04:51

I don't know.

2:04:52

I don't know either.

2:04:52

I mean, why would you put them in a cave in Peru?

2:04:58

I don't know.

2:04:59

And if you didn't put them in a cave in Peru, what would be left?

2:05:01

That's the problem.

2:05:02

The problem is it's really hard to make a fossil.

2:05:04

It's really hard to find bones.

2:05:05

Think about all the people that died and we don't find that many bones,

2:05:10

relatively speaking, in comparison to the fucking billions of people that died.

2:05:16

It's not like we're tripping over human bones every day.

2:05:18

Right, except in mass graves.

2:05:20

Yeah, right.

2:05:20

That's really, yeah.

2:05:22

And even in mass graves, given enough time, they will deteriorate, like mass

2:05:26

graves from 1,700 years ago, whatever these things are.

2:05:30

So, you know, I find them, again, I find them interesting.

2:05:34

And I hope that behind the scenes there are people who are taking a more methodical

2:05:41

approach to this who I think should remain stealthed until they have the data

2:05:48

to the point where it is publishable.

2:05:51

You know, publishing a white paper or putting something out on the Internet is

2:05:56

not the same as putting out data that has all of the instruments that you used,

2:06:00

the methods that you used, etc.

2:06:03

The reason you want papers, frankly, when you publish them to be almost boring

2:06:09

and so thick with detail that no pseudoskeptic would dare approach it because

2:06:15

they're just not smart enough.

2:06:18

But if you put out these snippets that don't have sufficient background, they

2:06:23

can be picked apart by anybody.

2:06:26

Right?

2:06:27

But that's why peer review is so important.

2:06:29

And people mistake peer review as trying to get the reviewers to agree with

2:06:33

your conclusions.

2:06:35

No, the main purpose of peer review is actually to make sure that the methods

2:06:39

that you used are sufficiently detailed and are correct enough to the extent

2:06:43

you came to any conclusions, they match the methods that you used.

2:06:48

And when you think about these potential whatever they are, whatever these

2:06:57

creatures are, if we did find out that they are some sort of a hominid,

2:07:09

how much credence do you give to the theory that there's like the possibility

2:07:13

that these UFOs, UAPs, whatever it is, is a break-off civilization from a very,

2:07:18

very long time ago that's very different from us,

2:07:21

the same way we're very different from chimpanzees, which we coexist with.

2:07:25

Right. I have no problem conjecturing that.

2:07:28

Did you ever see the Netflix show Chimp Empire?

2:07:32

Yes.

2:07:32

Amazing, right?

2:07:34

Amazing.

2:07:34

20 million years of separation, and it looked like fucking faculty meeting, you

2:07:39

know, with people like looking at each other and planning and plotting, board

2:07:43

meeting, you know.

2:07:45

And so we shared all of those interactions from 20 million years ago.

2:07:51

So how much further back would you have to go to have something like what that

2:07:58

is?

2:07:59

I mean, it's clearly not recent.

2:08:02

And also, if you think about what we are in comparison to chimps, we're so

2:08:06

fragile, we're frail, we're easily injured, we're, well, if you think of

2:08:10

something that's far more technologically

2:08:12

advanced than us, it would be even more frail, it would be even more petite, it

2:08:18

would have almost no muscle at all, it would look, weirdly enough, like the grays

2:08:24

from Close Encounters of the Third Kind.

2:08:25

Yeah.

2:08:26

I mean, that's what it would look like if it was a hominid that's whatever we

2:08:30

are, and it went way past that.

2:08:33

Right.

2:08:33

Yeah, no, technology gives evolution the excuse to no longer make or allow for

2:08:40

you to be robust.

2:08:43

Thank you.

2:08:44

That was the word I'm looking for.

2:08:45

And also, why do you need opposable thumbs?

2:08:46

Yeah.

2:08:46

Right?

2:08:47

These things don't even have opposable thumbs.

2:08:48

That was what's weird about it.

2:08:49

Right.

2:08:49

It's like, how do you interact with your environment?

2:08:51

They look more like sloths than they do.

2:08:54

Right, right, right.

2:08:55

I mean, at least their hands do.

2:08:56

Yeah.

2:08:57

And, and I, I don't know, I find it-

2:08:59

Well, if everything's done with AI and automation, and your interface is purely

2:09:05

neurological, like

2:09:06

you have some sort of a human or a creature neuro interface with technology,

2:09:12

and you just use fingers to like lay them on electronics so that you can sync

2:09:18

up with it.

2:09:18

Right.

2:09:19

Yes.

2:09:20

Yeah.

2:09:21

Yeah.

2:09:22

Why are you picking things up, bro?

2:09:23

You don't have to pick things up anymore.

2:09:24

Those go away just like, you know.

2:09:25

Can you imagine the scenario of, I mean, these things we know are, the body's

2:09:32

real, what they

2:09:33

are, we don't know.

2:09:34

But can you imagine the scenario of what happened as they were being buried?

2:09:39

You know, what would they, could you like make a, you know, a film of the

2:09:44

ceremonial burial

2:09:46

of these things?

2:09:48

Hmm.

2:09:49

You know, what would, what led to their death?

2:09:52

Right.

2:09:53

What led to their placement there?

2:09:54

Right.

2:09:55

Or if they were constructed, which I have a hard time with given the MRIs that

2:10:00

we've all seen,

2:10:01

et cetera, what led to it?

2:10:05

Um, and so that to me is as almost interesting as to whether or not they're

2:10:10

real or not.

2:10:11

Right.

2:10:12

Like the ones that are clearly constructed, that's where it gets fascinating.

2:10:15

Because like, what were you trying to reproduce?

2:10:17

Yes.

2:10:18

And why are they so similar to the ones that look real?

2:10:21

Yeah.

2:10:22

Are you, is it an homage to the ancestors or to the stories of the ancestors,

2:10:27

et cetera?

2:10:28

Yeah.

2:10:29

Especially when you look at Peru, like Peru is like, you've got the Nazca lines,

2:10:34

which are

2:10:34

really weird.

2:10:35

Right.

2:10:36

You can only see them from the sky and they're everywhere and they're huge.

2:10:40

Yeah.

2:10:41

And these depictions of very strange things.

2:10:43

I, you know, I just, so I just ask my scientific colleagues to not suspend

2:10:50

disbelief, but to

2:10:51

open your minds as to the possibility of what it, of what these things might

2:10:56

mean.

2:10:57

And just try to explain them without dismissing them.

2:11:00

Because it's so easy and politics, we see it every day.

2:11:03

All you need to do is just give any answer.

2:11:06

Even if it's obviously flagrantly wrong as just as a way to deflect.

2:11:12

And so, you know, you can either use that approach.

2:11:16

You shouldn't use that approach ever as a scientist, deflect.

2:11:19

Which unfortunately is what someone like, you know, Neil deGrasse Tyson often

2:11:23

does.

2:11:23

Yeah.

2:11:24

And as opposed to try to explain in a way that teaches your audience the right

2:11:32

way to think.

2:11:33

Yeah.

2:11:34

Well said.

2:11:36

One of the things that Jacques Vallée highlighted is there's an alloy, another

2:11:43

piece of metal,

2:11:44

some that they'd found that had layers like these at an atomic level.

2:11:51

Yep.

2:11:52

That if you wanted to make this alloy today, it would be almost impossible and

2:11:56

it would cost billions of dollars.

2:11:59

So I worked with him on one of those pieces.

2:12:02

I got the atomic imaging of some of that.

2:12:05

And it's, oh God, I'm blanking on the event, but it was the Sirocco event.

2:12:12

And where was that?

2:12:13

I think New Mexico.

2:12:15

I'm going to get in trouble for not knowing exactly.

2:12:17

But, and we actually did a atomic layering using this device called atomic

2:12:23

probe tomography,

2:12:24

where you literally pick it apart atom by atom and get its 3D position.

2:12:28

It's a 40-year-old technology, so it's nothing magic.

2:12:32

So, and yeah, it would just be very difficult to make it.

2:12:36

You know, and certainly it would be not something that you would have dropped

2:12:40

in the middle of the desert.

2:12:41

Socorro?

2:12:43

Socorro.

2:12:44

Socorro.

2:12:45

In the middle of the desert, you know, in the 1970s or whenever it was.

2:12:50

I wouldn't say it's impossible to make, but why you would do it is another

2:12:56

question.

2:12:57

It's clearly evidence of technology and manufacture.

2:13:02

And that's what interests me is, first of all, why would you do it?

2:13:08

Why would you create something, for instance, with the silicon and the

2:13:11

magnesium with the altered ratios?

2:13:13

Not the, where did it come from?

2:13:16

So what is it evidence of?

2:13:18

It's clearly evidence of technology.

2:13:20

Was this technology available at the time this supposed crash happened?

2:13:24

Uh, which one?

2:13:26

This?

2:13:27

No, not, no.

2:13:28

Not at the level of precision that was done and a chunk of, and no, it just

2:13:32

wasn't.

2:13:33

It just wasn't.

2:13:34

So if that's true and if it really, if that's the chain of evidence is correct

2:13:39

and it really did come from that area, from that crash, that's not a human

2:13:43

creation.

2:13:44

Well, it wasn't a crash.

2:13:46

It was an object that a policeman had seen with beings, short beings outside of

2:13:53

it.

2:13:54

And when it took off and left, he went over and found this piece that I had.

2:14:00

Actually, I personally have it now.

2:14:02

Huh.

2:14:03

So, you know, it's hard to say what's possible and what's not possible.

2:14:11

So, you know, there's plenty of military programs that make stuff that are way

2:14:16

outside of mainstream capabilities right now.

2:14:19

I mean, just look at the stealth bomber, for instance, and the skin of the

2:14:22

stealth bomber is just remarkable.

2:14:23

Is it possible they were doing that in 1970?

2:14:25

Maybe.

2:14:26

Maybe.

2:14:27

So that's why I always leave open the possibility that, you know, which is why,

2:14:32

I mean, this is, I'm going to get back to this atomic imager thing that I'm

2:14:35

making.

2:14:36

It's like there's a level of evidence that I think can be produced with atomic

2:14:43

imaging that goes beyond what it is we know anybody can make.

2:14:49

Right?

2:14:50

So, and so that's my reason for wanting to do it because, you know, look, I can

2:14:59

make money on it with looking at alloys and nanomaterials, et cetera.

2:15:03

And that's going to be what the purpose of the, of making the instrument will.

2:15:06

That's how it will be a company, but it will have value elsewhere.

2:15:10

So, the reason that I got interested in it was, frankly, for looking at

2:15:14

chromosomes, but then I realized, oh, maybe it has interest, maybe it would be

2:15:18

useful for these other things as well, which has kind of propelled my interest

2:15:22

in it.

2:15:23

Well, Jacques Vallée is such a valuable researcher because he's so logical

2:15:28

about the way he handles things and he doesn't jump to any conclusions.

2:15:32

Yeah.

2:15:33

And his descriptions of these materials and the origin of these materials is

2:15:38

really compelling because it's just like, if that's not really possible to make

2:15:43

in 1970, then someone help me out.

2:15:45

Yeah.

2:15:46

What is that?

2:15:47

Yeah.

2:15:48

And is it possible to make today?

2:15:49

And how much would it cost?

2:15:50

Right.

2:15:51

And where would you do it?

2:15:52

The magnesium ratio thing was, you know, when I first estimated, it was like,

2:15:56

this is millions and millions of dollars and why would you leave it on a beach

2:15:59

in the middle of Uba Tuba, Brazil?

2:16:01

Right.

2:16:02

You know, it's just, it just seems, it seems unlikely.

2:16:06

Nothing's impossible.

2:16:07

No.

2:16:08

But unlikely.

2:16:09

Well.

2:16:10

And then it's usually the chain of evidence.

2:16:13

It's, it's, there's lots of materials that you might find that are unusual.

2:16:17

And believe me, I get rocks sent to me at my lab in the mail that people say,

2:16:20

oh, this isn't, no, it's a rock.

2:16:22

Sorry, it's a rock.

2:16:25

But, you know, I have not yet been given anything which I could definitively

2:16:33

say, this is not something a human might have been able to make.

2:16:38

Um, it might be difficult, but not impossible yet.

2:16:43

And so that's because the level of resolution required to claim something is

2:16:47

impossible is something we actually don't even have yet.

2:16:51

Mmm.

2:16:52

Does that make sense?

2:16:53

Yes, that does make sense.

2:16:54

So that's what I, so my whole career has been inventing instruments that were,

2:17:01

I felt inevitable, but not yet possible.

2:17:05

But I could see a path to making them.

2:17:07

And so I said to most people, get out of my way.

2:17:09

I'm going to do this.

2:17:10

Because I know once I've got it, it will become valuable to everybody, which is,

2:17:15

that's what made my career in immunology, making a succession of instruments

2:17:18

like that, and then making them available to the community.

2:17:21

So I think the next level is atomic.

2:17:25

Because we now know, you can pick up and look at any of the major physics

2:17:30

journals today, everything is all about these weird exotic particles that exist

2:17:35

in metamaterials down at the atomic level with vague and strange capabilities

2:17:41

that will change their utility, either as superconductors, room temperature, or

2:17:47

different kinds of electronic components that might be better.

2:17:50

That might be better, quantum computer circuits and qubits.

2:17:53

It's all down at that level.

2:17:55

But to do so requires a level of engineering that we don't, I mean, never mind

2:18:00

reading what it is, putting it together in the first place is what's still

2:18:05

required.

2:18:06

And so if we don't know how to put it together in the first place, then reading

2:18:12

it and knowing that it can exist and then associating it with a function is the

2:18:17

value that I'm looking to bring.

2:18:20

Well, this brings me to the idea of crash retrieval and the idea that these

2:18:26

crash retrievals started a long time ago and that Roswell was just one of many.

2:18:33

There's another one that was near Roswell that apparently was even more

2:18:36

significant, but didn't get in the newspaper.

2:18:39

"Trinity" are you talking about?

2:18:41

I think...

2:18:42

There was the one that Jacques was involved with studying.

2:18:45

I don't know.

2:18:46

I'm basing this off of Richard Dolan's book.

2:18:48

Okay.

2:18:49

But at the end of the day, but the point being that if they did do that, if

2:18:54

they really did back engineer something and then they started these completely

2:19:00

top secret scientific research projects where they were developing alloys that

2:19:05

had never existed before with techniques that they had never really even

2:19:10

considered because they got it all from some spaceship.

2:19:14

Well, that's where it's really crazy if you don't disclose this information

2:19:18

because you're basically putting a bottleneck on human evolution, human

2:19:22

technological evolution and our understanding of what's actually possible.

2:19:27

Right.

2:19:28

I agree.

2:19:29

And, you know, if you're going to excite the next generation of scientists in

2:19:35

this country and you're going to bring economic prosperity to this country,

2:19:41

then we should...

2:19:43

I wouldn't say democratize it and put it all out on the internet.

2:19:46

I understand all the reasons why you might not need to, but you need to excite

2:19:50

the populace.

2:19:51

I mean, my laboratory at Stanford for probably the last 10 years is 90%

2:19:58

foreigners.

2:20:00

And not because I don't want to take more Americans, but because Americans just

2:20:07

don't go into the sciences anymore.

2:20:11

They don't study math.

2:20:13

You know, they aren't encouraged to approach this.

2:20:17

So we're importing a lot of our scientists from overseas.

2:20:19

Well, guess what?

2:20:20

A good third of them end up going back and bringing all the technology that

2:20:23

they invented here back there and creating competitors.

2:20:26

Now, maybe that's good on a global scale, you know, but maybe it's not

2:20:31

something that we want to encourage on a local scale if we want to maintain our

2:20:36

technological superiority.

2:20:38

I mean, we're basically governed by lawyers.

2:20:41

China is governed by engineers.

2:20:43

Hmm.

2:20:44

You know, I mean...

2:20:45

Do you see the results in their drone technology and electric cars and the

2:20:48

things that are coming out of China recently?

2:20:50

Their Politburo is almost entirely engineers and scientists.

2:20:53

Oh.

2:20:54

Interesting.

2:20:55

Yeah.

2:20:56

There's a little article in the Atlantic recently about that.

2:20:59

Oh, that's a giant advantage.

2:21:00

Yeah.

2:21:01

So people who are making these...

2:21:02

We have lawyers looking for all the reasons why something should or shouldn't

2:21:05

be done on the liabilities.

2:21:07

They're looking at things as to what's possible.

2:21:10

When you're looking at these UAP things that people bring you, what...

2:21:15

Is there one that stands out as being the most compelling to you?

2:21:18

One event?

2:21:21

Well, both the Council Bluffs and the Ubatuba event are interesting to me.

2:21:26

Because of the physical material?

2:21:27

Because of the physical material itself.

2:21:29

I mean, I'm, at the end of the day, a physicalist.

2:21:32

You know, I mean, I don't like all the anecdotes.

2:21:36

I mean, a thousand anecdotes make a good story, good campfire.

2:21:40

I mean, I think there's statistical value in people seeing the same thing again

2:21:45

and again.

2:21:46

And there's a truth to it.

2:21:48

But, you know, and I can believe anything I want to around that and many of the

2:21:53

statements that I'm purported to have said are around my beliefs.

2:21:57

As opposed to when I put on my scientist hat and I try to convince another

2:22:00

scientist, I can only provide this data and this evidence and I don't have yet

2:22:05

these materials.

2:22:06

Now, maybe they exist and maybe, you know, people like David Grush will be able

2:22:12

to pry them out of the clammy hands of those who want to keep it where it is.

2:22:17

But give me one piece of that and I will do wonders with it.

2:22:24

Yeah.

2:22:25

I mean, that's why I'm so excited about the UAP Disclosure Act, if it ends up

2:22:30

becoming law, because there will be this ability to start to maybe eek some of

2:22:35

this out.

2:22:36

And again, it's the reason why I think this commercial opportunity is the

2:22:41

direction we want to go where we have a sort of public private partnership is

2:22:45

that the defense budget in and of itself is a zero sum game.

2:22:49

We're taking money from one program to give to another.

2:22:52

You know, whether you're taking it from your taxes, you're taking it from

2:22:56

veterans, you know, insurance, et cetera.

2:22:58

It's a zero sum game.

2:22:59

Whereas if you bring the investment community in, now you're bringing in people

2:23:03

who are willing to take a chance and willing to take a risk and you're not

2:23:07

using the public's money anymore.

2:23:09

And so, and that excites, I mean, me as the reason why I wanted to go back to

2:23:14

Stanford is because the entrepreneurial environment there, and now which is

2:23:19

actually almost homegrown here in Austin, is really what drives innovation.

2:23:25

And so I want to excite that kind of community.

2:23:28

And again, the Soul Foundation is a place where we can bring people in and we've

2:23:33

got investors who show up now who are talking to people about their ideas and

2:23:37

what would we do with this.

2:23:38

And so you, you, it almost has now a self propelling movement where I don't

2:23:46

need to be standing on a, you know, wooden box somewhere in the middle of the

2:23:52

park saying, you know, look at this, look at this.

2:23:55

People are just doing it now.

2:23:56

There's now a whole, almost a cottage industry of small groups or formalized

2:24:02

groups who are doing this independently now.

2:24:06

So it's almost like it's inevitable.

2:24:09

So Skywatcher as an example, you probably know the Skywatcher group.

2:24:13

Yeah, I've heard of it.

2:24:14

And Jake Barber.

2:24:15

Didn't they just stop operations?

2:24:17

No.

2:24:18

Did something happen?

2:24:19

No, it's, it's strange because people said, oh, we stopped.

2:24:22

No, actually it had been, it had been determined from the beginning that we

2:24:25

were going to go from January until July or August and collect data.

2:24:29

And now we're in the, okay, what does the data mean phase where we're literally

2:24:36

going through the data, looking at the data files.

2:24:39

And China, we're, as I said before, we're filtering the data.

2:24:42

We're looking for the obvious mistakes, et cetera.

2:24:46

And so, no, they've not stopped.

2:24:49

Yeah.

2:24:50

There was something on Twitter about the, something about the equipment.

2:24:54

I forget.

2:24:55

No.

2:24:56

So James Fowler, one of the guys who brought a lot of his equipment and

2:25:01

technology to us, decided that he wanted to basically go off and work in a DOD

2:25:09

capacity as opposed to the research capacity.

2:25:11

But he's still advising us.

2:25:12

I was just on a phone call, a Zoom call with him last week going over the data

2:25:16

files.

2:25:17

So, explain this Sky Watcher thing to people, because it sounds insane.

2:25:22

Well, the idea behind it was that there might be ways to send a signal and get

2:25:30

things to show up.

2:25:33

Right.

2:25:34

And James Fowler claimed that he had such a thing.

2:25:37

I was at one of the events where something showed up.

2:25:42

It was transient, momentary, but, you know, indisputable.

2:25:47

But it's just like...

2:25:48

What did it look like?

2:25:49

It was just a silver ball moving quickly through several frames of a video,

2:25:56

which was not fast enough, frankly, to pick it up.

2:25:59

We just saw it move.

2:26:00

It went that way and then...

2:26:01

You didn't see it with your naked eye?

2:26:02

No, I didn't see it with the naked eye.

2:26:04

Which, of course, is a problem.

2:26:06

Do they sometimes see things with the naked eye?

2:26:08

One guy did, yeah.

2:26:09

One guy.

2:26:10

I mean...

2:26:11

So, are these things variable in their appearance?

2:26:13

I wish I had my...

2:26:14

I don't have my phone here.

2:26:16

But we do have a picture of one next to the helicopter, about 200 feet away.

2:26:22

And it's just kind of a fuzzy white blob against a blue sky.

2:26:28

But it was there.

2:26:29

You know, it's not a cloud and it's not a balloon.

2:26:32

Mm-hmm.

2:26:33

You know, it's not discernible as anything obvious, but it was there and it

2:26:38

happened during one of these events, out in the middle of the desert.

2:26:42

Mm-hmm.

2:26:43

And so, you know, so the idea is, behind Skywatcher, is to see if there are

2:26:49

ways to get them to show up.

2:26:52

And if so, in a reproducible manner, and then have the right kind of

2:26:56

simultaneous multi-sensor capabilities to measure it, meaning radar, IR, visual

2:27:04

people on the ground.

2:27:07

What are they sending to get these things to go?

2:27:09

What signal?

2:27:10

Um...

2:27:11

James has a signal that, unfortunately, he won't, um...

2:27:15

I don't know what it is.

2:27:16

He won't let everybody know what the bat signal is to climb UFOs?

2:27:18

Well, I mean, you know...

2:27:19

I mean, maybe...

2:27:20

Yeah, exactly.

2:27:21

I mean, it sounds kind of silly, but, I mean, why would you put that out on the

2:27:24

internet?

2:27:25

Because, you know, you might render it useless.

2:27:28

They're like, ugh, I don't gotta show up.

2:27:30

Everybody's using it now.

2:27:31

Oh, so you think it's a trick?

2:27:33

Like, it tricks them into showing up?

2:27:35

I don't know.

2:27:36

I really don't.

2:27:37

Do you think they'd be smarter than that?

2:27:39

Well, that tells you something, maybe, about the level of smarts that might be

2:27:43

incorporated into these, let's say, dumber machines.

2:27:46

Hmm.

2:27:47

Maybe...

2:27:48

Yeah.

2:27:49

That was exactly my thought.

2:27:50

It's like, why would you show up when you know what it is, unless there's a

2:27:55

reason you're basically trying to train the monkeys what to do?

2:28:01

Maybe you're tricking the monkeys into sending...

2:28:03

I don't know.

2:28:04

But isn't there a group of people that just go out and they...

2:28:08

Meditate.

2:28:09

...just using their mind.

2:28:10

They meditate.

2:28:11

Yeah.

2:28:12

And supposedly they have some success as well.

2:28:14

There's the CE5 groups that do that.

2:28:17

And I've never participated in any of that because I don't know how to measure

2:28:23

it.

2:28:24

Uh-huh.

2:28:25

I'm, you know, I'm more than willing to believe that there are technologies

2:28:30

capable of measuring thoughts at a distance that might be some super advanced.

2:28:35

I don't believe you have to call it telepathy and magic.

2:28:38

I think that there's, you know, if such a thing happens that there is a

2:28:42

technology that might be able to read at a distance.

2:28:45

Right.

2:28:46

Well, it's all...

2:28:47

I have no problem with that.

2:28:48

I don't have a problem with that either.

2:28:49

I don't have a problem with the idea that consciousness is kind of vaguely and

2:28:55

barely understood.

2:28:57

And whatever our relationship to the universe itself and reality itself through

2:29:03

consciousness, it's not fully defined.

2:29:07

And also, it might evolve just like all of our other intellectual capabilities.

2:29:13

Right.

2:29:14

Well, I mean, think of it this way.

2:29:16

You know, you and I are interacting with each other through quantum waves.

2:29:21

I, my meat brain sees you as an object, but yet everything that you are sits in

2:29:25

quantum space-time down at the Planck level and you're not even mass.

2:29:30

You're just a series of, I mean, in some people's minds, vibrating fields and

2:29:34

objects.

2:29:35

And so, we have sensors that see and hear each other and think about each other,

2:29:39

but our consciousness somehow is embedded in space-time.

2:29:42

And so, who's to say that there's not signals passing to and from that are vaguely

2:29:47

able to be picked up by our meat brains that we don't necessarily appreciate?

2:29:52

Right.

2:29:53

So, that just because I can't think at you and you can't hear me doesn't mean

2:29:58

that there aren't perhaps brain organizations of some people that are a little

2:30:03

bit better at hearing the echo than others.

2:30:07

Well, this is also probably the reason why when you go to the woods and there's

2:30:11

no cell phone signals, the world feels different.

2:30:14

Yeah.

2:30:15

Because you're probably experiencing a bunch of signals that your brain vaguely

2:30:19

interacts with.

2:30:20

Right.

2:30:21

You know, might not even necessarily be good for you.

2:30:24

Right.

2:30:25

But they're out there and they're a part of the world that you live in.

2:30:27

Mm-hmm.

2:30:28

And you just, you can't, you don't have a radio.

2:30:29

Right.

2:30:30

Right.

2:30:31

So, you're not like tuning into them.

2:30:32

You don't have a cell phone.

2:30:33

Right.

2:30:34

So, you can't just like make calls with it, but you're experiencing it.

2:30:36

Right.

2:30:37

Well, and you know, our civilization is drowning us in constant noise.

2:30:42

Yeah.

2:30:43

And so, maybe, you know, that drowns it out and that's why meditation is why

2:30:46

people claim that they can interact with other things.

2:30:49

I don't know.

2:30:50

Yeah.

2:30:51

I don't know either.

2:30:52

One, I saw an interview that you did where you were describing the sighting

2:30:57

over off the coast of San Diego in 2004, the Nimitz sighting, where you said

2:31:04

that the amount of power, why don't you describe it?

2:31:07

Right.

2:31:08

The amount of power that that thing had to use to move the way it did.

2:31:11

Right.

2:31:12

So, it's on radar.

2:31:13

It's on radar.

2:31:14

So, these are actually calculations by Kevin Newth, a physicist from the

2:31:20

University of Albany, and a published paper.

2:31:23

Again, just speculation, but what he basically said was how much power would it

2:31:29

take to instantaneously accelerate from 50 feet over the ocean to 50 miles

2:31:35

above the earth, whatever the number was, and instantaneously decelerate.

2:31:40

So, it's not just the amount of power to lift something, it's the amount of

2:31:44

power to accelerate and decelerate instantaneously.

2:31:47

And so, you can make simple physical calculations of a one-ton object, let's

2:31:53

say, and it's more than the nuclear output of the United States for a year.

2:31:59

And yet, these things seem capable of doing that at will.

2:32:03

So, where are they getting the energy from?

2:32:05

And I remember asking Hal a question like this years ago, we were stepping into

2:32:11

an elevator, and we were talking about his ideas about how these things might

2:32:15

move.

2:32:15

And I said, "So, they're cheating somehow, aren't they?"

2:32:18

And his answer was, "From our point of view, they're cheating.

2:32:22

From their point of view, they're just using the physics that we don't

2:32:25

understand yet."

2:32:26

So, where's the energy coming from?

2:32:29

What are they doing?

2:32:30

And so, that might be, as a for instance, a reason why you don't want everybody

2:32:35

having access to it.

2:32:36

Yeah.

2:32:37

Because any one of those objects is worse than a thermonuclear bomb.

2:32:41

You shoot one of those things at a city, and that's the end of the city.

2:32:45

And if anybody could do it, you know.

2:32:48

Well, maybe that's the step of human evolution, of the evolution of our society

2:32:53

and civilization,

2:32:54

is that AI has to come into power before we have access to all this other stuff.

2:32:59

Right.

2:33:00

That we do need an AI government structure.

2:33:02

Right.

2:33:03

That we do no longer require military intervention and all the shit that is the

2:33:08

bane of civilization today.

2:33:10

Because if you ask the average person today, do you envision a world where war

2:33:17

doesn't exist?

2:33:18

Most people are saying no.

2:33:19

Right.

2:33:20

The vast majority, except for a few delusional hippies.

2:33:22

They're going to say no.

2:33:23

Right?

2:33:24

But if you ask them, okay, given this super intelligent AI takes over the world

2:33:30

and proves to be benevolent and really just wants to accentuate the life of

2:33:36

human beings on earth and make it better for everybody, then yes.

2:33:40

Right.

2:33:41

Then 100% yes.

2:33:42

Right.

2:33:43

Right.

2:33:44

Right?

2:33:45

So maybe something like that has to take place before we get to a situation

2:33:49

where, okay, this is how you really travel.

2:33:52

Right.

2:33:53

Right.

2:33:54

Okay.

2:33:55

Now that you're not going to war anymore, listen, I'll show you about gravity

2:33:57

bubbles.

2:33:58

You can already imagine the negatives where people will say, oh, well, it's the

2:34:05

apocalyptic nanny state.

2:34:08

Right?

2:34:09

Where AI just basically takes care of you and humans devolve into something.

2:34:14

Which is why I think a merger of human intellect with this where it's a synergy

2:34:20

as opposed to an either/or.

2:34:23

I don't want to be nanny stated either.

2:34:25

Right.

2:34:26

I don't want to use it to explore ideas or explore pleasure.

2:34:29

I mean, I'm finding people want to be hedonistic and, you know, participate in

2:34:36

virtual parties all day long.

2:34:37

Right.

2:34:38

For all I care.

2:34:39

I don't care.

2:34:40

Right.

2:34:41

But I think giving people the option to do whatever it is that they want to do,

2:34:45

it's the most,

2:34:46

I don't know, what's the, it's the most liberal and conservative way of living

2:34:52

because you're allowed to do what you want to do.

2:34:55

But we're not because we're living at the behest of so many other structures.

2:35:00

Always.

2:35:01

Yeah.

2:35:02

Um, last question.

2:35:04

Woody, what's your take on the Bob Lazar story?

2:35:08

Um, elements of truth, um, with, uh, a healthy dose of, um, misinformation that

2:35:18

perhaps he was provided.

2:35:20

Hmm.

2:35:21

Um, I don't think that he's entirely lying.

2:35:27

He seems to know enough about things that the average person wouldn't know.

2:35:34

But, you know, I've heard from Eric Davis and others saying, you know, he's a,

2:35:39

he's a this, he's a that.

2:35:40

I don't know because, you know, it's like, that's why there are great people

2:35:46

like Richard Dolan, who, who's a, you know, a wonderful writer of the history

2:35:50

of the area, or people like Robert Powell or Michael Swords who write just the

2:35:56

facts, not coming to too many conclusions.

2:35:59

Um, I don't live in that world.

2:36:04

That's, it's, it's not my specialty.

2:36:05

My specialty is working with data and analyzing things and bringing rigorous

2:36:10

science to it so that I can convince another scientist what is right or what is

2:36:15

wrong.

2:36:16

Cause I won't be happy.

2:36:18

I mean, I'm pretty sure of what I know, but I want to validate that to my

2:36:24

colleagues.

2:36:26

If only to be able to say, I told you so.

2:36:29

Hmm.

2:36:30

Right.

2:36:31

There's a little bit of human pettiness in there, you know.

2:36:34

A little bit of pettiness is great motivation.

2:36:36

Yeah.

2:36:37

But, you know, but, but that's, I think, again, enabling people to live in a

2:36:41

world like that, where you can talk about these ideas without being ridiculed,

2:36:46

is really, I think, the objective of what science should be and what open-minded,

2:36:51

you know, non-theologically dogmatic approaches should be.

2:36:56

It's, it's like, accuse a scientist of being a priest and that's the best way

2:37:01

to really upset them.

2:37:02

Mm-hmm.

2:37:03

But pointing out that what they're doing is mimicking dogma and priesthood is

2:37:08

the only way to shame them into doing the right thing.

2:37:12

Ah.

2:37:13

Does that make sense?

2:37:15

It does.

2:37:16

It does.

2:37:17

Well, listen, man, I'm glad we finally did this.

2:37:20

Yes, thank you.

2:37:21

Thank you so much for being here.

2:37:22

Thank you so much for all the research that you're currently involved in and

2:37:26

all the stuff that you've done.

2:37:28

And it's been amazing talking to you.

2:37:29

I really appreciate it.

2:37:30

Same as well.

2:37:31

Thank you.

2:37:32

Thank you so much.

2:37:33

All right.

2:37:34

Bye.

2:37:35

Bye, everybody.