Moonshots with Peter Diamandis - The Technology Bigger than AI w/ Jack Hidary | EP #68
Episode Date: October 12, 2023In this episode, recorded this year at Peter’s Executive Summit, Abundance360, Peter and Jack discuss exponential technologies of the future, such as Quantum technologies, entrepreneurship, and the ...transformative potential of innovative mindsets. 13:57 | Quantum Technology Now Accessible 1:12:38 | Molecular Medicines, Faster? 1:17:46 | The Software Quantum Revolution Jack Hidary is a renowned entrepreneur and technology visionary. He’s the leader of SandboxAQ, a company at the forefront of AI and Quantum tech through enterprise SaaS solutions. He's the acclaimed author of "Quantum Computing: An Applied Approach," a leading textbook in its field, and has co-authored AI research papers with MIT collaborators. As a serial entrepreneur, Jack co-founded several tech ventures, notably EarthWeb/Dice, which he led from inception to its IPO, and Vista Research, later acquired by S&P/McGraw-Hill. Learn more about SanboxAQ Learn more about my executive summit, Abundance360 _____________ I only endorse products and services I personally use. To see what they are, please support this podcast by checking out our sponsors: Get started with Fountain Life and become the CEO of your health: https://fountainlife.com/peter/ Use my code MOONSHOTS for 25% off your first month of Seed’s DS-01®. Learn More About Seed's DS-01® _____________ I send weekly emails with the latest insights and trends on today’s and tomorrow’s exponential technologies. Stay ahead of the curve, and sign up now: Tech Blog Get my new Longevity Practices book for free: https://www.diamandis.com/longevity My new book with Salim Ismail, Exponential Organizations 2.0: The New Playbook for 10x Growth and Impact, is now available on Amazon: https://bit.ly/3P3j54J _____________ Connect With Peter: Twitter Instagram Youtube Moonshots Learn more about your ad choices. Visit megaphone.fm/adchoices
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Quantum computer.
Quantum mechanics.
Quantum physics.
Yeah, that's a quantum processor.
And inside are these actual physical qubits.
There's many quantum technologies that are actually here and now.
These ideas didn't even exist not too long ago.
This is what's possible now, Peter.
Okay, we have quantum computers and quantum sensors and quantum security
and what what is going on here underlying all this is quantum
information science is QIS our world at a fundamental level is not the Newtonian
world that we're used to it's not the billion-ball world that we used to at a
fundamental level it is a quantum world we're used to. It's not the billion-billion world that we're used to. At a fundamental level, it is a quantum world. We're the first human generation
who can finally harness not just the world of bits and not just shaping
furniture and stuff in the macro world, but harnessing the ability to manipulate
the atomic and quantum world. We are that first generation.
Great to see everyone.
Wow!
This is not a conference, this is a happening.
This is, yes.
This is a community and a conversation
about how the world's changing.
And then importantly, Jack,
something that you care deeply about,
how do we use these extraordinary technologies
to make the world a better place?
But most importantly first, Peter.
Yes.
Before we actually speak about quantum,
one very important thing for a gathering like this.
Does everyone have a drink?
Yeah.
Okay.
Is the bar still open, by the way?
We find that quantum is more easily digested
with a little alcohol.
So you just closed $500 million
as like your seed round.
That's awesome.
That's epic.
And yeah, let's give it up for that.
Thank you.
God, we go back a long way.
And I'm so, I have no right to be this proud of you,
but I'm tremendously proud of you.
We go back, Peter, to the very early days of XPRIZE.
Yes, the early days.
There's some early XPRIZE's here.
Let's hear it for XPRIZE.
XPRIZE.
The look on Peter's face many, many years ago
when Anusha Ansari and her family,
where's Anusha?
The amazing Anusha.
There it is.
And her family stepped up and gave us enough money,
not for the prize, but for the insurance for the prize.
Hole-in-one insurance.
Hole-in-one insurance. Hole in one insurance and it happened.
Just weeks before the expiration, Burt Rutan and his team got up there to space and opened
up the private space industry.
The vision of Peter, incredible.
So thank you Peter for opening up.
Peter, to honor your commitment in opening
up space, we prepared a number
of very technical drawings
based on you going to space.
So I'm going to show this now.
This is Peter Diamantis
playing golf on Mars. Now,
one of the sides is terraformed. Mars
is already terraformed. That's why you have no spacesuit.
And the other one, I love
how Stable Diffusion created a golf caddy uh bag that is itself also a spacesuit i think that is just
fantastic and look at peter's form here on the right i mean just flawless impeccable well it's
one third grab it's 0.38 gravity so it's kind of tough. Go ahead. Yeah.
So we had Eric Schmidt on stage with us last year.
Yeah.
And this was just around the time.
We were just about to spin out.
Just before spinning out.
Just about to spin out from Alphabet.
And Eric's brilliant, and he's an amazing persona.
What's it like to have Eric Schmidt as your chairman?
Well, we were very lucky.
We started this inside Alphabet,
and Alphabet was an incredible partner and platform to build this out.
First and foremost, you have a lot of free sushi,
which fuels the team.
And in a little seriousness,
Sergei and the entire team,
Astro, incredible support
for more than five years
in stealth inside Alphabet,
building this out.
Five, six years ago, Peter...
So you were inside of X?
Of Alphabet, yeah.
And specifically housed inside of X,
the Moonshot factory.
And we've had Astro
like three or four times over the years.
And I remember I'd meet you there, right?
Astro was always on his rollerblades and he'd be there.
I was like, huh, why is Jack here?
Now we know.
And I'd be able to say some kind of very general things about,
yes, we're working on some interesting things.
That's about what we can say for five years.
And around 2020, Eric was wrapping up. First, he was CEO, of course, of Google, and then
chairman of Google and Alphabet for another eight, nine years. And in 2020, he was ready to wrap that
up. And he came to Sergey and myself, and he said, of all the things here at Alphabet, 150,000 people,
incredible projects, there's one I want to work on for the next decade of my life. And that is Sandbox. That
is this fusion, this convergence of AI and quantum, two twin engines that will change the world. And
we're going to talk about that tonight. And he said, if you'll have me, you know, I'll join you
guys. And I thought about it for a few months, no, for a few seconds. And Eric became part of the team. And so when it
was time to spin out, we all discussed it and we realized this is the moment. We needed to
drive this growth faster and adoption faster and needed to bring this out to the world.
And Eric then took on the role of chairman and myself as CEO. So one of our first things,
Peter, one of the first orders of business of any chairman and CEO was to go find an office space, right? That's a typical thing that we do, right? Yeah. I mean,
you know, you look at Palo Alto, you can look at a lot of great, I just came from Austin,
another great tech center. So we went scouting Austin. Any Austins here? Yes. Yes. Just as with
Jay, the president of UT Austin, incredible tech center brewing there. And so any guesses where
this location is? And any guesses? Any guesses? So I'll just give you a hint. It's the sun is
setting and rising at the same moment. Alaska is one good guess. Iceland, another good guess.
Little farther south. Antarctica. Yes. And so of course eric and i had to go down there uh recently
and check it out uh to scout for the various things but in all seriousness eric and i went
down there with we brought actually 15 scientists that we curated from around the world peter uh
glaciologists whale scientists penguin scientists scientists who cover the gamut of the, not
only the climate sciences, but all the biodiversity also.
And we'll talk more about that in a little bit.
And we have a lot of workers down there, a whole staff of people who are buttoned up
and dressed very, very nicely down there.
And here we brought a submarine down there, a research sub.
And this is one of the first expeditions to actually go underwater and be able to classify.
And we actually believe we had with us one of the foremost scientists who studies the Southern Ocean marine life.
We believe we may have actually discovered two new species on this expedition.
And the whole aim of the expedition was to...
With personalities and whatnot.
Yeah.
I mean geeks with personalities and whatnot.
Yeah.
The whole aim of the expedition was to bring AI and quantum science to climate change,
to the climate science, to the ice science, to the biodiversity science.
You sent me a WhatsApp from Antarctica.
Yeah.
And I'm like, I had no idea you were down.
I was like, what, are you going to search for cold for quantum computers or something?
So we actually realized that we can actually accelerate the science of understanding what's happening to our planet with both AI and quantum.
And hopefully we'll have time today to go more into that.
But we did come to a really big epiphany down there
that indeed we can make this happen.
And the beauty of our planet is very evident down there.
This is a snow petrel
flying by us and just an incredible place. If you want to take a time machine back to 10,
20 million years ago, I asked one of the scientists with us, I said, if we were here
10 million years ago, if we were here standing on this rock, the rock that we were
standing on right there, we don't believe humans have stood on, unfortunately, ever before. This
was covered in ice just a number of years ago. And according to the records, we're the first
expedition to have an icebreaker big enough to get in to this place and take recordings and data.
place and take recordings and data and so unfortunately um this this is a newly uncovered piece of land and what i asked a number of the scientists on on the trip i said because one of
them said hey penguins i said what's the origin of this penguins they said they split off and
speciated 38 million years ago i said all right 38 million years ago these penguins the adelies
the the chinchraps, the
Gentoo's, the three species that we were with right there in that, near that land.
And I said, if we were here 10 million years ago on this land right here near the penguins,
if we were here 20 million years ago, what would we see?
If we took our sub down 10 million years ago and saw the marine life there, what would
we see?
years ago and saw the marine life there, what would we see? And each one of them said, you'd see exactly what you're seeing right now, except for the fact that obviously the ice looked quite
different. And so it's amazing to kind of go back in time into a land beyond, into a place of
stillness, Peter, a place that captures what our planet was like for millions and millions of years.
And then to start to quantify using these new tools that we have now to understand the dynamics
of how we are impacting this planet. So that was really an incredible journey, both in place,
but also in spirit. And I encourage folks to go down there to experience this, but also
to contribute to the science. We'll talk later about
how people can get involved.
Those photos of Eric Schmidt there with his
camera and so forth
remind me, I took
Eric and Larry and Sergey on a
trip to Russia, to Kazakhstan
to see a Soyuz launch.
And it was extraordinary.
And he's just, with his cameras, I just love his photography.
Yeah.
So he's been great.
To answer your question, he's been incredible support.
And, you know, the philosophy that we had,
both when we were inside Alphabet and now outside,
is the moonshot thinking that we have, you know,
so developed at XPRIZE and at X.
And, you know, the moonshot thinkers in this audience,
everyone here is a moonshot thinker. you wouldn't be here right now everyone is
here and have self-selected yourself to come here to say how can I take this
kind of thinking but turn it into action right the folks I see a lot of friends
in the audience here the people here are doers and and that's really what we need to make this impact yeah amazing um let's talk about the
the basic concepts right now that we're going to be talking about you know everybody's heard
about quantum computers we've been talking about quantum computers for years uh the idea of like
quantum supremacy was a was a term that was used along the way.
And last year, you started saying,
no, it's about quantum technologies.
That's really what is hot and is going to drive revenue and immediate value.
Can you take a second and walk us through
the difference between quantum computers
and quantum technologies?
Yeah, sure.
So I think most people here
have heard about quantum computers.
You hear about it in the press. There's a lot of buzz around that. And there should be some buzz
around that. But that's going to be a longer term impact. To build these computers, we have to have
error correction. Every one of your phones right now that you're holding, every laptop that you
have has error correction in it. Believe it or not, these errors can come from a lot of different sources,
including muons from the cosmos can actually cause some errors in your computers.
And in most computers, we can get away with having three bits
for every one bit that we want to signify.
And so we kind of take a vote.
Two out of three bits say it's a one.
Let's go with the one in case there was an error in one of the bits.
But in the case of quantum computers, our ratio is 1,000 to one.
1,000 physical qubits to one logical or fault-tolerant qubit.
And what is a qubit?
A qubit is the logical computing unit of a quantum computer, a quantum bit or qubit.
And there are seven different ways to build these kind of
quantum computers. And they each have a completely different physics. Some are cryogenic, some are
super cold, minus 200, or even colder. And in one case, you have to bring it down to six to seven
millikelvin above absolute zero. Okay, so it's really's really really cold others are room temperature right
and so there's lots of different ways to build it you can use photons you can use ions you can use
neutral atoms lots of different ways to build it but in general we we're on a quest as an industry
to build these things we decided at sandbox peter not to build one of these computers because we saw
that there was a great ecosystem already building it.
We wanted to encourage this ecosystem.
Instead, we focus more on the application layer,
both on GPUs, the chips of today,
and QPUs, these quantum processing units.
But beyond quantum computing, Peter,
the big picture, one of the big takeaways
that I'd love to share with you all today
is that there's many quantum technologies that are actually here and now.
They do not require error correction.
They do not require the fault tolerance that we're talking about with quantum computing.
One of those examples is quantum sensing, sensors that can detect magnetic fields around us.
This blew me away. And we're going to talk about that today, tonight,
and talk about how magnetic fields are all around us,
including those that emanate from our bodies.
Every time you have electricity,
electrons on the move, electricity,
you have a magnetic field.
Faraday taught us that in the 1800s.
And so there's magnetic fields coming from our body.
Any ideas from the audience about an example
of a magnetic field coming from an electric. Any ideas from the audience about an example of a magnetic field
coming from an electric shock in your body that happens pretty often?
Any ideas of an organ in your body that is producing an electric shock pretty often?
About, say, 70 times a minute or 80 times a minute.
Any ideas?
The heart, right?
And so those pacemaker cells are causing a contraction of that big
muscle called the heart, just another muscle, and it contracts and squeezes and blood goes
everywhere, hopefully in the right places. And as that's happening, a magnetic field
is also being produced. Orthogonal to electric field is the magnetic field. And that magnetic
field is something that we can finally now sense using quantum sensors.
And so we'll talk about what the implications are.
And then there's another application
that really is global in nature
and something that we did down in Antarctica
with our quantum sensor right down there on that trip
just a number of weeks ago.
So quantum sensing, Peter, is something that's here today.
We're using it right now. And that has not not gotten the press so it's good everyone came to a
360 because you get the information right here right now in terms of the
quantum sensors there's also quantum simulation and quantum simulation is the
kind of breakthrough technology we need for digital twins of drugs and we'll
talk about that talk about that as well.
So all these technologies, quantum simulation,
quantum sensing, these are the kind of technologies
that we do not need quantum computers for.
We do not need error correction for.
And so these are the technologies
that we are focused on right now.
Which, to drive your business.
Well, not to drive business, but to drive impact, right? Because
you know, our philosophy is your philosophy, Peter, same one is that when you drive impact
for billions of people, you will have a business, right? You will have a very robust global business.
And our ambition is nothing short to be one of the most, if not the most impactful company on
this planet. It's not the biggest company. you don't have to be the biggest company anymore in fact what we're showing is that with smaller and smaller
teams you can have bigger and bigger impact given the forcing factors you have with both ai and
quantum so let's rattle them off as quantum computation we've talked about a little bit
uh i want to hit one more thing there and then we'll come back quantum sensing uh quantum communications yes quantum security yeah encryption yep uh do you
put quantum chemistry into this so quantum chemistry is that quantum simulation it's that
digital twinning of a molecule of if we want to do battery chemistry for clean energy it's a group
quantum medicine in that.
It's all in there.
All in there.
Yeah.
And so all that is happening right now.
Now, quantum computers, as they rise up, and we're encouraging them and working with these
teams around the world to make it happen.
How many quantum companies are there, you think, out there?
There's about four dozen really strong quantum.
That's about 50, by the way.
Yeah.
About four dozen quantum computing companies
out there uh they've gotten some good funding and most of them have spun out of really good labs at
universities uh we're encouraging them i mentioned there's seven different ways to build a quantum
computer and here's what's great news the great news is that we see a diversity of ideas out there
we do not see groupthink what we know for example from the history of technology
the last 50 60 years look at the ai winter look what happened in 1969 in the first ai winter
when a book was published perceptron that said ah this neural network idea not sure it has any legs
right anyone know the author of that of that book perceptron 1969 that killed off yep you got it and so that and the lighthouse
report in the uk um basically said hey neural networks cute idea brain inspired not going to
scale let's use reasoning and conditionals and if then statements that's how we're going to get
artificial intelligence and of course that was not correct and there was a few handful of
people who believed still in the idea of distributed networked ideas of neural
networks and those people went to the only country that was funding them
Canada CIFAR Canadian Institute for Advanced Research and that's why it's
not a coincidence that the folks who just got the Turing Award for being the deans of neural networks,
right? Jeff Hinton, Yeshua Ben-Gio, Jan LeCun, where did they do all their work? Which country?
Canada. Because that was the place where you can have a diversity of opinions and say,
there's another way of doing machine learning. And now we see, and I think you've discussed it
here yesterday about GPT and all the incredible things that we now see from that.
So it's very important.
We're watching very carefully in the quantum space, Peter, that we stay on course in terms
of avoiding groupthink and having a large number of opinions across the board.
That's critical to making sure that we don't too early get into a rut that can lead to the kind of AI winters we saw in such a key.
Imagine if we had 25 years of extra research on AI,
where we'd be today.
We lost 25 years of work.
So we want to make sure we don't repeat that again.
Amazing.
So why don't we jump into some of these?
I want people to appreciate what becomes possible because what you've described to me seems magical.
Do you want to start with quantum sensing?
Sure. Let's start with quantum sensing. And I think one of the big themes, Peter, that I'd love to share with you all tonight is the move from bits to bits and atoms.
with you all tonight is the move from bits to bits and atoms. And the tech sector, I'd give us a pretty good grade
for manipulating bits, moving bits, creating bits,
pattern recognition with bits right now, with all the AI
that's now generating new kinds of bits from other bits.
So in the bits column, I'd say pretty good tech sector.
But in the area of atoms,
the area that actually impacts our lives in a very deep way,
molecule to medicine,
battery chemistry for electric vehicles,
for stationary storage of solar and wind,
material science for new kinds of solar panels.
We're hitting a limit.
New catalysts.
New catalysts that do not depend
on rare earth and so on and so forth. This area, the actual world we physically live in,
this era, I would give ourselves in the tech sector a failing rate because we haven't done
much. If you look at the way that we develop and design drugs today compared to 10, 20 years ago,
basically roughly the same,
same time, same amount of money, same kind of failure rate. We'll talk about it in a minute,
but let's talk about sensing now. When we look at medical imaging, I started my career at NIH
combining physics and neuroscience and AI, bringing those disciplines together to help move forward a
field of functional neuroimaging, imaging that was not just static,
but looking at a moving image of the brain. Because we went in and with the help of Siemens
and Gee and Phillips, we opened up those machines and we tweaked them so we can take images much
faster with the physics inside. And those are actually quantum devices. And so we haven't seen
a lot more diagnostic revolutions until now. And so let me see if I can move on. And so we haven't seen a lot more diagnostic revolutions until now.
And so let me see if I can move on.
And so, yeah, so that's the bits to bits and atoms,
something that we need to get to.
And I want to now get to sensing here.
Let's just jump right here.
Okay, here we go.
So a number of really, really smart academics about 22 years ago, Peter, said,
hey, we want to build these quantum computers.
We just talked about different ways of building them.
But the thing with quantum computers is that to keep them coherent,
to keep them in those states of superposition and entanglement,
these very, very delicate states of the quantum world, is very difficult.
If there's a magnetic field around, it'll knock it off its pedestal,
and you have to restart that qubit. If there's stray photons around, you'll have to restart that qubit.
So some enterprising academics said, wait a second, let's turn that bug into a feature. Let's say,
hey, if it's so sensitive to the outside world, let's stop calling it a cube, but let's call it a sensor.
Fantastic. Okay. So they said, all right, we're going to call it a sensor. And what are some of the sensors they have? I'll give an example right here. It's a quantum diamond. We make these
diamonds with our partners. There's no mining of diamonds here. We've synthesized these, and this
is not the synthesis you'd imagine of taking some carbon and crushing
it at high pressures this is layer by layer the kind of way we we do with techniques that we take
from semiconductors and we create layers of carbon of course carbon is one of the primary constituents
right and in the case of normal diamonds the only constituent but here we dope in some nitrogen we
actually keep a spacer so we have a vacancy. And this nitrogen vacancy center in diamond,
in NV diamond, is a quantum system.
The electrons hanging out in that little center right there,
we can manipulate those electrons.
We can move them from a ground state
to a higher state, a quantum state.
And again, the thing to remember about quantum,
what is this world of
quantum? The idea of quantize is that it's discretized. These electrons cannot exist
anywhere between. It's like rungs of a ladder versus a ramp. A ramp, you can exist anywhere
along that ramp. But rungs of a ladder, you're either on this rung or the next rung. And that's
what we have over here. We have a quantum system that says if we pop in some green light to give
energy to those electrons, we'll move them from a ground state, says if we pop in some green light to give energy to those
electrons, we'll move them from a ground state, Peter, we'll move them to an excited state.
And when we stop our green light and we let those electrons come back down, of course,
conservation of energy, they're going to have to give out energy. They're going to have to release
photons. And those are the red photons you see over here and we can measure with great exquisite precision
Those red photons and what does that tell us? Well, what it tells us is
the magnetic field the strength of magnetic field that that diamond is in or near and
now we have a
Magnetometer a magnetic sensor such as we've never had on earth before with a level of precision how much
so specifically if we have someone's heart and let's now go to heart we know that heart is the
leading cause of death yes continues to be talking about that globally um particularly in europe us
we have tons of statins tons of procedures tons ofents. We still cannot seem to budge this.
And one of the things that's holding us back when we interviewed cardiologists after cardiologists
and the folks at Cleveland Clinic and the folks at the leading universities and medical centers,
we need better diagnostic tools. How many times have we heard about somebody getting clean bill
of health at their great concierge medicine, three, four months later, heart attack, right?
you know, their great concierge medicine, three, four months later, heart attack, right? Why didn't we detect it? What happened there? EKG is not sufficient. The tools we have today are not
sufficient. Think about EKG. So there's leads on your chest picking up electricity. Now, where did
that come from? So that came from the pacemaker cells in the heart, which is not attached to the
chest. It's not at the chest wall.
So it's a very indirect measure.
And what we realize is we can actually build a box.
Here is our lovely subject, Stefan B., our scientist.
Notice that his shirt is on and there's no leads and there's no wires because we're picking
up the magnetic field coming through his bone and tissue.
The magnetic field is not dissipated by that bone and tissue. The magnetic field is not dissipated by that bone
and tissue. We're getting the real activity directly from the heart. And it turns out that
back in the 80s and 90s, an early quantum sensor known as a squid, a superconducting quantum
interference device, a squid, a cryogenic device, something that has to be liquid cooled.
You need a Faraday cage. You need a room the size of this stage, and you need to protect it and
shield it from the Earth's magnetic field. And then you have people come in. And in Cleveland
Clinic in Ohio, they have one of these. And it turns out that you can tell a lot about the heart.
And that's why Cleveland Clinic still uses it today, a device that was made 20, 30 years ago. But that form factor does not allow us to democratize it, to scale it, to take it out
to the world. One of the reasons why we're so committed to XPRIZE and all the XPRIZEs that
take technologies and blow it out to the world is the same reason why we want to take this
modality, magnetocardiography, MKG, not just EKG, but MKG,
and take it out in a form factor that's room temperature, that's small, that we can take to
clinics in rural areas, take to people all around the world, and of course, take to hospitals all
across the US, Europe, and other countries. And this allows us to do that. In fact, this is much
bigger than we had to make it. We took our initial designs to the hospital.
We showed them.
They said, don't make it that small.
We were going to make it the size of a Rubik's Cube.
And they said, our doctors will not take it seriously
for the size of a Rubik's Cube.
So can you put some air around it?
So 80% of that box near Stefan is air.
Then they said, put it on wheels
because anything that's wheeled around
is taken very seriously. If you wheel it around and it's white, it will be taken extremely seriously.
And so this device right now is at UCSF Hospital.
Anyone wants to be a test subject, clinical trial's open.
Join us.
We're building up the data now.
And here's the beautiful thing, Peter.
We don't have to prove its medical efficacy.
That's already done by Cleveland Clinic, by others,
using the previous generation of MCG.
But now all we have to show is that this form factor
also adheres to that kind of thing.
And in fact, already today, the standard of care for fetal cardiac diagnostics is magnetocardiography.
You can't get an EKG lead into a womb and say, how's your heart doing, Mr. and Ms. Fetus, right?
And so what you can do though is again passively listen just listen to the heart
magnetic field coming out there's nothing emanating from our box already presented to the fda and the
fda said we love this first principle do no harm of medicine you can do no harm because nothing's
coming out of your box this is a device that is just listening and waiting for the heart to give
it information a spin out from, a partner of Sandbox?
No, this is one of our devices.
This is one of your products?
This is one of our products, yeah.
Amazing.
And so let me now talk about how the AI, and Peter, you and I have talked about this,
where does the AI come in to quantum?
Well, this device is so sensitive.
Again, the name Sandbox, the A is for AI, the Q is for quantum, right?
Yeah, absolutely.
This is the convergence of these
two technologies we had to have both and one of the reasons why this beautiful technology did not
come to light until we got involved is that in the hands of the physics departments again brilliant
that they turn this bug into a feature making sensors but But look at, let me see, I don't think I have a,
no, okay. If you just look in the upper left, that's the signal coming out of the quantum
diamond. It's too much information. If Peter, you're standing just a few meters from the device
with your iPhone, you're going to set that thing off. You're going to add to the noise of the
device. In fact, our first version did not work. Our first version worked great in our lab. We brought it over to the hospital, failed completely. What happened?
We were about seven meters from the elevators of the hospital and the elevators go up and down and
have an electromagnetic portion, which was throwing off our design. Now we could kind of
ML it out. We said, you know what?
Let's go back to the lab and actually redesign it.
We did.
We're back in there now
and we don't have that interference,
but we have to build for noisy environments.
We don't want to build for a room
that has to be caged in with a Faraday cage, right?
We want to democratize it, bring it out.
So when you look at the upper left,
you're like, where is the heart signal?
And so it took us more than two years
of additional ML work
to bring it from the upper left
to the right where you see there.
ML is machine learning, just to make sure.
Yeah, where we can find the actual heart signal.
And so this is a combination of hardware
and physics and quantum
making these diamonds more pure,
more homogenous. When I showed you that one area of the nitrogen and the and quantum, making these diamonds more pure, more homogenous.
When I showed you that one area
of the nitrogen and the vacancy,
this is not just one of those in there.
There's a billion plus in one cubic millimeter.
A billion plus of those dopings
that we put in in one cubic millimeter.
Amazing.
And so this is exquisite technology
that I'm really proud of
the team having created but also the ml needed to go from complete noise to finding that heart
signal and so this is what's possible now peter to bring this out and to have this impact are you
able to speak about the navigation yes so so just to give a little secret okay just to give a little peek the heart you asked how sensitive is this this is 10 to the minus 12 Tesla
if you've been in an MRI machine everyone I'm sure here has you've been
in something that's either 1.5 Tesla 3 Tesla 7 Tesla maybe even if you felt you
had any kind of metal and was pulling like this to the machine that's like a
7 to 9 Tesla machine in research
I used to use these machines and one time I had
Small little piece of metal on my shoes and I almost lost my leg like this
to the machine when it was turned on but
That's one to nine Tesla. This is ten to the minus
Twelve Tesla, it's. So point and then 11 zeros and a little one.
That's how weak the magnetic field of the heart is.
And if we want to do the brain, then we have to even go even more sensitive.
And hopefully that's coming soon.
So let's now talk about navigation.
Well, what's happening right now in Ukraine?
Russia is jamming
the signal over Ukraine. And it's not just there. The signal of GPS, right? GPS, if you want to go
on eBay or other websites, you can buy for $700. Something that looks like a walkie talkie,
but like a big walkie talkie like this, we can jam GPS for the entire area of Terranea with one little device like
this because again you know we know the spectrum of the GPS satellites and we
can have you know destructive interference where we're sending out a
wave that exactly destroys that particular signal and you'll have no GPS
in fact Qantas Airlines just issued a warning just two days ago and they said we're getting jamming when we're near the PRC
when we're near China GPS jamming our flights with passengers on them have lost GPS due to jamming
now why would China be jamming the GPS signal near the straits of Taiwan any guesses okay I'll leave
it at that but the point is that Maersk, the large shipping company,
reported the same thing,
that when their ships are coming into the port of Shanghai,
going various places,
they lose signal for portions of their voyage.
This is a major issue because it's so easy to jam.
So what are the alternatives?
Well, you can do dead reckoning,
and that's been used for hundreds of years,
but we know the drift involved in dead reckoning, right?
You can get your astrolabe out, right?
If you can see some stars.
But what we realize is that we can be
like the bird I just showed you before.
There's a turn, an Arctic turn, a bird,
that travels 24,000 kilometers a year
in its migratory pattern from the North Pole to the South Pole. that travels 24,000 kilometers a year
in its migratory pattern from the North Pole
to the South Pole.
Other birds, of course, we know very well,
migrating during different seasons.
Whales using the magnetic field of the earth as well.
Even turtles, when those turtles are born
and they're running to the sea,
they're actually using magnetic gradient as well.
So nature has figured out that you can use,
you can leverage the earth's
magnetic field for direction, for navigation. Birds have figured that out. And maybe some
evidence that some humans have a little magnetite left in our brains. Maybe some people can do it,
but most of us, most of us cannot. And, and so, um, and so we rely upon GPS, but now
we have given humans that ability
by having a diamond sensor,
the kind of diamond I just showed you before for the heart,
the same diamond,
and matching that now,
not with machine learning that looks for the heartbeat,
but machine learning that looks for the unique fingerprint
of the Earth's magnetic field
in every square meter of this Earth.
And this was a revelation to us as well.
When we-
This blew me away.
Yeah. When we spoke, Peter, to the geophysicists and we brought them into our team and we realized
that actually, I know there's a lot of geeks here. Everyone here is a geek. Otherwise you
wouldn't be here. So I'll just, let's geek out for a second on geophysics. And it turns out that,
yes, we all learned in school about the liquid core. There's an inner core ball of iron, and around that is liquid molten iron,
a little bit of nickel in there, and that's sloshing around,
creating what's called a geodynamo.
And that geodynamo is creating the core field of our Earth.
But in fact, there's another modification of that magnetic field.
As lava comes up, and has come up for millions and hundreds of millions of years,
and then cools down, the magnetite, the hematite, the ferromagnetic materials in the mantle as it cools down modifies locally that core field.
And you now have a fingerprint, a unique signature on that spot on Earth.
So every square meter of the planet has a unique magnetic signature that you could map and then use for navigation from then on.
Correct. And so right here, this square meter, that square meter, every square meter on Earth.
And you could navigate a thousand meters underwater.
That's correct. So when you're underwater, you can't navigate.
One of the reasons why the scientists were asking for help down in Antarctica
is because when they have their underwater drones,
the British Antarctic Survey, BASS as it's called,
had two underwater drones at the cost of two million British pounds each.
Both of them now are broken.
Why are they broken now?
Because they did dead reckoning and they couldn't see where they're going
and they bumped into various walls and underwater seawalls
and they're both broken right now.
Giving the opportunity to have true absolute navigation,
not dead reckoning, not inertial,
but absolute navigation underwater.
You can't get GPS signal more than a meter underwater.
And so when you want to go deep more than a meter,
you've got to have some way of navigating.
And this now allows us to do that.
Remember we said about magnetic field, we said about bone bone and tissue it's also true of the water we can detect that
underwater so this becomes peter and right now i'm happy to say that this device that we created
is flying as we speak now on a test plane of one of the largest airplane manufacturers on the planet
right now and um there's actually a button that was a very emotional moment
for us was when they sent us a picture from this company and they added a button on the dashboard
of the plane, on the avionics. It's a button called Sandbox AQ. When they flip that button up,
up comes a magnetic navigation. And we're not saying don't use GPS. Of course, have GPS.
But if it's getting jammed, if you lose that signal, you can lose it for other reasons,
not just jamming.
You better have some kind of global backup and it better be absolute navigation.
And finally, we can empower scientists as well with underwater navigation and allowing
them to do the exploration and data collection that we all need to find out.
Amazing.
Everybody, I want to take a short break from our episode to talk about a company that's very important to me
and could actually save your life
or the life of someone that you love.
The company is called Fountain Life.
And it's a company I started years ago with Tony Robbins
and a group of very talented physicians.
You know, most of us don't actually know
what's going on inside our body.
We're all optimists.
Until that day when you have a pain in your side, you go to the physician in the emergency
room and they say, listen, I'm sorry to tell you this, but you have this stage three or
four going on.
And, you know, it didn't start that morning.
It probably was a problem that's been going on for some time.
But because we never look, we don't find out. So what we built at Fountain
Life was the world's most advanced diagnostic centers. We have four across the U.S. today,
and we're building 20 around the world. These centers give you a full body MRI, a brain,
a brain vasculature, an AI-enabled coronary CT looking for soft plaque, a DEXA scan,
an AI-enabled coronary CT looking for soft plaque, a DEXA scan, a grail blood cancer test,
a full executive blood workup. It's the most advanced workup you'll ever receive. 150 gigabytes of data that then go to our AIs and our physicians to find any disease at the very beginning.
When it's solvable, you're going to find out eventually. You might as well find out when you can take action. Fountain Life also has an entire side of therapeutics. We look around
the world for the most advanced therapeutics that can add 10, 20 healthy years to your life.
And we provide them to you at our centers. So if this is of interest to you, please go and check
it out. Go to fountainlife.com backslash Peter.
When Tony and I wrote our New York Times bestseller, Life Force,
we had 30,000 people reached out to us for Fountain Life memberships.
If you go to fountainlife.com backslash Peter,
we'll put you to the top of the list.
Really, it's something that is, for me,
one of the most important things I offer my entire family, the CEOs of my companies, my friends.
It's a chance to really add decades onto our healthy lifespans.
Go to fountainlife.com backslash Peter.
It's one of the most important things I can offer to you as one of my listeners.
All right, let's go back to our episode.
And this is probably just a fraction of the potential applications you haven't thought about yet.
Yeah, there's so many other applications, but I think just sharing hopefully tonight,
the promise of where this is going and the fact that we're doing this right now. This is something
that we invite folks who have ideas. If you have an idea for what we can do with quantum sensors,
we're open to, you know, brainstorming ideas. That's always been the philosophy at XPRIZE and always been our philosophy as well to partner with folks and think about new ways of helping the planet in this way.
So that's, in a nutshell, quantum sensing.
Where do you want to go next?
Yeah, let's give it up to quantum sensing.
I mean, but I just appreciate, again, how these ideas didn't even exist not too long ago, right?
And what this is going to unlock.
I remember when Scott Madry at International Space University, one of the early geolocation pioneers, was showing me the idea of geoposition systems.
And little did I could imagine of Uber or Google Maps, right?
All the applications will be born on top of these things that we can't even imagine yet.
And this is magic.
And ultimate cost of this is... Oh, that's the idea.
To democratize this,
we have to make sure that it's very accessible.
If it's once again a multi, multi-million dollar device
like you see in hospitals, we have failed.
Yeah, cool technology, but not impact.
The standard we hold ourselves to
is the impact that we have.
And by making these devices
room temperature and really small and portable, low power, by the way, to power one of these
devices is a couple of D batteries, probably even maybe just four or five AAA batteries, but
it's really low power. We don't even have to use lasers. I showed an example there with lasers
because it was easy to visualize. But now, actually, we've converted to LEDs.
You know how cheap LEDs are.
So a green LED, and then it comes out as red, and we detect that.
So that's really, really easy.
But maybe, Peter, we should now turn for a few moments to quantum security, to cybersecurity,
because I know that's on the minds of a lot of people, protecting our data.
And then just a few moments on that, and maybe then we talk about medicine and how we can
really revolutionize drugs does that make sense yeah so I mean we have had this buzz in this
conversation year on year about is quantum computing quantum encryption or de-encryption
going to unlock all of our wallets should we we be worried about that? And the answer will eventually be yes,
but before then, you have some solutions. Yeah, this is a serious topic that
a lot of really good brains are working on it right now around the world. And we're very privileged, Peter, to
be collaborating with incredible centers. I just came from Delft in Amsterdam, near Amsterdam,
where there's a tremendous center for quantum information. And one underlying theme, Peter,
I hope to share with everyone here tonight, is that underlying all this stuff, it sounds like,
okay, we have quantum computers
and quantum sensors and quantum security. What is going on here? Underlying all this
is quantum information science, is QIS. And if we had a moment, just like the graduate,
the movie, and we want to say one word to the next generation, let's say QIS to the next
generation. I know it doesn't roll off the tongue like plastics, but it's something that is fundamental to our world.
Our world at a fundamental level
is not the Newtonian world that we're used to.
It's not the billion ball world that we're used to.
At a fundamental level, it is a quantum world.
And quantum, ultimately,
now that we're the first human generation,
the first generation of people
who can finally harness,
not just the world of bits and not just shaping furniture and stuff in the macro world,
but harnessing the ability to manipulate the atomic and quantum world. We are that first
generation. Amazing. And it's no less than landing on the moon. It's no less than any one of those big breakthroughs
that were both conceptual, mental breakthroughs,
as well as the kind of technology breakthroughs.
So let's talk about security for a minute.
So Peter, as you said correctly,
quantum computers can do many, many positive things in the world.
But one thing they also do,
we know from a 1994 paper from Peter
Shore, a brilliant mathematician who's now at MIT, then was at Bell Labs in New Jersey, and a young
researcher there, he's in his cubicle and he's checking out various papers that are brewing in
this new field of quantum information. And he realizes in the epiphany that this computer,
once built, will break the encryption that we all use.
And already by that time, in 1994,
this encryption, an example of that is RSA,
extra credit, what does RSA stand for?
Extra credit, anyone here?
Revest?
Shamir?
Someone help him?
A?
A, A, A? Edelman, yes, good, Excellent. So Ravesh, Amir, and Edelman,
three brilliant folks from the seventies and eighties came up with this incredible public
key encryption, the ability for us to share information over this wild west of the internet
without having to meet in secret. Before public key encryption, what did we have to do? We had to meet in a bunker
and we had to say, here's our one-time pads. We are spies in East Berlin and we're going to share,
Peter, our one-time pads. On Monday, we will use this key and you will use the same key Monday.
And then Tuesday, we move to the next key and we call it a pad. We take off, we tear off the pages
of the pad and we use those. I've seen this movie. Yes.
Bridge of Spies.
And what we found is obviously that that's not scalable.
If you want to build a global economy, such as we just did since the 70s and 80s, that global economy was fueled by a number of things.
But one of the key drivers was public key encryption.
Can you imagine if Jeff Bezos set up an incredible company,
Amazon, in the Seattle area, and we had to all go take flights to Seattle. Every time we wanted to
give him a credit card, we had to go there, drive there, take planes there, ride bikes there, and
say, Jeff, here's my credit card. We're in secret. I'm now giving you my credit card. I will now go
back home and wait for my package. No, that would not be scalable. But instead, because of RSA, because of this encryption, this asymmetric encryption, why
asymmetric, Peter? Because my public key, which I published over the internet and Amazon uses,
and now in this case, I want to send them a credit card. So I find their public key. I encrypt my
credit card with their, with the Amazon public key.
Of course, I don't have to consciously do this anymore.
The browser does this for us.
When you see that little lock, that's what it's doing.
And it's sending Amazon.
And with their private key,
a different key than the public key,
it is decrypting that.
So the whole basis of RSA
is what we call a one-way trapdoor function.
A function that's easy to go one way,
but very difficult to go back unless you have the trapdoor function. A function that's easy to go one way, but very difficult to go back
unless you have the trapdoor, the private key.
And that's been the basis of global commerce.
Without that, we wouldn't have
the incredible economy that we have right now.
And so that standard started in 1978,
and even right before that with Diffie-Hellman
and some precursors to that,
but basically late 70s, early 80s, we had that.
And here comes Peter Shore, a researcher,
Bell Labs, 1994, writes a paper, puts it out.
And first a few mathematicians read it
and then some cryptographers read it
and then some security people read it.
Then the government reads it and then others read it.
And everyone realizes, oh my God,
this whole edifice we have
just built one day will come crashing down. And nobody knew at that time in 94 would it be possible
to build these computers. And so for many years it went by not really gathering much attention until
in the last number of years it became very clear that these seven ways of building a quantum
computer that we just talked about were gaining traction. People were announcing new engineering barriers being
hurdled again and again, here, there, everywhere, all around the world. And so it became clear,
we will build these computers and encryption will fall. And that means that all of us in this room,
everyone on the planet will have to migrate over.
And here's the good news.
It's not often, Peter, we can point to a government program and say, that worked.
But in this case, we can.
Because six years ago, a number of governments around the world came together and said,
whoa, boy, we better have a solution for this because this train is coming at us hard.
And so they got together, made an open call, transparent process,
and said, come all ye who have an idea for a better protocol that would not be killed by quantum computers. That was more or less the statement. And sure enough, people came in and
it was 82 different ideas of how to have a protocol for securely transmitting information,
just the way we do right now. But to do so, that is not breakable
by a quantum computer.
We call it quantum-safe cryptography
or post-quantum cryptography, PQC.
Different words, different jargon,
but means the same thing.
And in fact,
after three rounds of culling
on July 5th this past year,
about eight, nine months ago,
the global governments came together
with us in the industry and the academics.
Everyone said, kumbaya, we have found it.
And so the process actually worked.
We now have a standard that we'll all be using that is a different kind of encryption.
Instead of the hardness of factoring large numbers, that's what RSA is based on, having very large numbers as the public key, and it's very hard to go back the other way to find the two factors that we use to multiply
them together to make this big number. That would take billions of years on today's computers, but
only a millisecond on the quantum computer. Instead of that regime, we're moving to something called
lattice-based cryptography, a format that is not subject to this kind of quantum attack. And so,
a format that is not subject to this kind of quantum attack. And so, and so we now have the pathway forward, but now the real work begins. This cannot happen overnight. It's not going to
happen overnight. In fact, it's going to take a number of years to happen, but now we have a
roadway, a roadmap to make it happen. I just put this slide up, Peter, just to show that
when you look at banks, banks have been in the news recently, and among the other things,
not just the balance sheets and the number of bonds and the interest rate of the bonds and
where the interest rate swaps and other things, but also the IT infrastructure because of the
amalgamation of M&A that led to all these large banks. And we can say the same thing about pharma
and the M&A and pharma, and we can say the same thing about other industries, telco,
as an example. Does anyone remember some of the early telco players? Bell Atlantic, anyone? Nextel. Nextel,
Ninex. Okay, anyone? Okay. So all these, when they're merged, it looks good on paper. Lawyers
get paid. Fantastic for them. But who actually harmonizes the IT backends? It often never
happens. And so what we find when we go in there with forensic tools,
we find old protocols,
protocols that are not just subject to quantum attack,
protocols that have been broken,
and we can break it by an iPhone, MD5, SHA-1.
These are hashing protocols,
protocols used to store your passwords,
passwords that we don't want out there.
And so we find this in banks around the world. We find this in governments around the And so we find this in banks around the world.
We find this in governments around the world.
We find this in hospitals around the world.
These are protocols that have been broken already.
And we need to go in there and identify these vulnerabilities
and then migrate them over to better standards.
So quantum is a great catalyst.
This is the positive news.
Quantum is a great catalyst.
This is the positive news.
It's a wonderful catalyst for us to finally fulfill this obligation to secure our data.
Every time you hear about a breach,
you say, oh, how did that breach happen?
How did 100 million records and credit cards
and social security numbers get out there?
It was probably the case that
not only was there a firewall issue,
but once they got in there,
that should have been encrypted.
It was not properly encrypted.
So there's been a lot of focus on viruses
and malware and ransomware
and of course firewalls,
but we now need to pay attention
to the nature of how we encrypt the information,
not just how we transmit information back and forth.
That's one encryption called data in motion,
but also how we store information,
data at rest. And so this is an opportunity, that's how we see it, of engaging with our world,
engaging with our key data that we own, that is our data, our healthcare data,
our banking information, our personal data. And so this is the moment now to re-look at all that
in the next three, four years, and we now need to re-establish the foundation so that we can continue to grow this economy.
Otherwise, the whole thing comes crashing down, or we can all take trips to Seattle every time we want to buy something from Amazon.
So that, in a nutshell, is quantum security.
Amazing.
Thank you.
that in a nutshell is quantum security explained by a brilliant genius thanks um how far are we from quantum computers breaking today's standard rsa yeah um it's a great
question and that's why i want to put up this slide here.
So there's a lot of efforts around the world to build quantum computers. And it's not exactly as if the business plans of these companies is, hey, venture capitalist Peter, I have a quantum
computing idea. We're going to build a quantum computer. And the reason we're going to build it
is to break the world's cryptography. That's not necessarily the business plans that you see being
pitched. But the fact is that no matter why
you're building your quantum computer,
once it gets to a certain scale,
we will start seeing encryption fall.
And there are also state-sponsored efforts,
maybe adversarial,
that are building quantum computers
and they're open about it.
And they have thousands and thousands
of engineers and scientists on this. And this is open information now on the internet and we look at
that information and realize that there is no way to control it anymore the genie is out of the
bottle this will be built because the prize the brass ring is simply too big too valuable the
ability to have a computer that cracks everyone's encryption is simply too
valuable. It will happen. There is no regulation. There is no way to stop it at this point.
And one of the reasons why we're urging around this now is this slide here, SNDL, store now,
decrypt later. Because if I know, Peter, that one day I will have such a computer,
and I want to know the secrets of that company,
of that government, of that individual.
I don't wait until then.
What I do is I siphon off.
I don't even have to break into your network.
I just say, I know Peter lives in the LA area
and I know that he's probably on this ISP.
And so I'll just go to a hop over here.
I'll tap in and I'll just start
siphoning information. And somewhere in there is Peter's communications. And I'll just make a copy,
just make a copy, make a copy. I can't read it today because you're using RSA or a similar
encryption, but I'll just store it now. I'll store it now. And then in a number of years,
I'll have such a computer and I'll decrypt it later. And then when I decrypt
it, I say, oh, Peter, FYI, you owe me $5 million in ransomware because I have your data. Otherwise,
I'm going to release it. Oh, you're a pharma company. Ah, yes. I have all your molecular
formulas that you've been transmitting to your factories. I have everything. I know you transmitted
them securely at that time, but retroactively now, and there's probably a Hollywood script in here
somewhere, that retroactively, none of it was secure at all. So this is the concern we have now.
This is the concern that governments have. This is why you hear various governments, including our
own in the United States, issue directive after directive. In fact, Congress passed a law on December 9th this past year,
and amazingly, the Senate passed it unanimously. Does that happen every often? No, it doesn't.
Unanimously, 100 Yais said, we approve this law that requires our federal government to move
to the new standards because of the concern about SNDO. That law is now signed.
It's now the law of the land.
And now the federal government is on the move to make this happen.
So the good news is that we have a response.
We have a roadmap.
But this is the concern.
The concern, Peter, is that over the next number of years,
these quantum computers will get bigger and bigger and more powerful.
And it's not just little companies making them.
There are state-sponsored adversaries who have intense moonshot manhattan projects yes that are making these quantum computers and did we announce that we had broken enigma back in
world war ii did we announce that to the world i don't think we did so we may not know when somebody has this computer. But it's too late.
The companies have sent this all and they are.
So, but we now have quantum encryption.
Yeah.
That's quantum safe encryption.
That's right.
And here's the good news, Peter, that we don't need a quantum computer in our hands to be safe against quantum computers.
We can do this encryption using your current cell phones, using the current servers.
Don't throw out your machines.
But what's the date before which all of that's...
We know that adversaries probably started siphoning data
in great levels probably around three years ago.
Probably around three, four years ago,
they started to siphon data.
But every day that goes by is another day. And of course, that the world's and you've talked about this that the the growth
of how much data we produce in medicine and other areas you know and so this is the moment to start
to start changing now because of sndl yeah and have the major telecom companies start doing
they're starting right so if you have a vpn if anyone here has used VPN, that P in VPN, the private, virtual private network, that P is currently secured
by RSA or similar protocols. So we have to upgrade the VPNs. We have to upgrade telco.
All this ecosystem has to be upgraded. It's a huge amount of work. And this is the work that
has to be done collectively. There's no one company or individual
who can make this happen.
This is a ecosystem that has got to come together.
And the good news, I think, Peter,
is that this is a moment to relook at all this encryption
and say, let's batten down the hatches
and let's make sure we have deep security and privacy.
Privacy is absolutely critical
and to have privacy,
you need encryption. So this is a moment, I think, for us to strengthen the entire infrastructure
and take care of years of stuff we should have done because of all this M&A that went on.
Tomorrow morning is our dive into longevity. We have eight phenomenal longevity conversations. And one of the things that
we've been talking about is this decade is different than past decades in terms of our
ability to begin to understand at a molecular cellular level why we age and how to manipulate that. Super pumped about this.
We heard a presentation earlier from Alex Zavronkov,
the CEO of Insilicon Medicine,
and the work that he's doing in global drug discovery
using generative adversarial networks.
Talk about this, because this is something
that you're super passionate about, and I am too.
So I think everyone here is familiar with the stats on this slide.
And one stat that people may not be familiar with is not only is there a
two thirds rate of failure in clinical trial.
I think most people know that what people may not know is that 40%
fail in phase three. Now, phase three, Peter,
we did phase one
and that was our safety phase, right?
We did phase two.
We showed some efficacy.
Otherwise, we wouldn't get permission
to go to a pivotal
or to go to phase three.
And now we're in phase three.
It's the cherry on top.
It's confirmatory.
We're just here to say, yes,
it works now in more than
just 50 or 100 people.
We're now at a few thousand people or more.
We just want to make sure, yeah,
but we have a lot of good news coming in to phase three.
Otherwise, are we going to spend
the four or $500 million on a phase three?
No, we would not.
And yet we do.
And so if somehow I said to you,
hey, Peter and I have a new company.
Peter makes a company every week
and I make a company once in a while.
But let's say we had a new company.
We had a new company that's a construction company
and the audience comes to us, Peter,
and it says, build us a new hotel.
Build us a new building.
We have a construction company.
But we say, hey, audience, sorry.
When Peter and I build this hotel for you, there's a two-thirds chance it will fall down in the first 30 days.
That would not be a very promising startup that we have.
But in fact, this is what we accept in the biopharma industry.
This is what we live with.
And I started my life helping to run clinical trials at NIH.
And this is what we lived with NIH. And this is what we
lived with then. And this is what we have now. We have not materially improved the situation
in decade after decade after decade. We have a lot of new tools. We've talked about this,
talked about that tool, this tool, but in point of fact, net net, any guesses on average per year, how many new drugs are
approved by the FDA?
Any guesses?
I'll start the bidding at 10 new drugs.
38, 50, 100, 10,000?
No, 10.
So this is a very savvy audience. Yes. About 48, 49, about 50 drugs. And of those,
more than half are Me Too drugs. More than half are, hey, Peter, we're on the board of a great
drug company. I think we need a new statin on the market. Yeah. There's only 17 of them.
And so I think you and I should make a new stand we should modify one of
the current stands patent it we should make a new stand shouldn't we a billion dollars a year revenue
why not and so why don't we see the breakthroughs why don't we see it what's happening why don't we
see more effort go into pancreatic cancer into very difficult cancers it It's very risky. It's very, very risky. How do we change
the game here? In silico medicine is one of the companies changing the game. We need a set of
tools that completely transform the way we think about going from molecule to medicine. This is not
working right now, be it for small molecule or for biologic, for proteins or small molecules, it is not working. And so how do we change this game? And people have heard about digital twins.
And so what we realized is we needed to put together a team, Peter, that had the expertise,
had the knowledge of how things are done now, but also had the knowledge of AI and quantum,
had the knowledge to say, we now need to take an AI and quantum
approach a physics based approach that is driven by AI initially but the last
mile must be quantum why because when one molecule meets another molecule
here's an example I have right here and so here in this case K Truda is a
synthetic antibody that you see right in the middle of the diagram here.
It's an antibody not made by the body, but an antibody made synthetically to plug up that receptor,
that PD-1 receptor that you see right there.
We want to plug that hole.
We do not want the tumor to insert the ligand into that receptor. Because if that tumor inserts that ligand into that receptor like a locking key,
what does it do to that T cell? What does it do? What can tumors do to T cells? T cells are there
for the fight. They've come to the fight. They're here to do what our immune systems want to do,
to destroy pathogens. And in this case, it's a different kind of pathogen, right? It's not a
bacterium. It's not a virus. This is something that was a human cell.
And so it has a locking key to turn off the T cell, to put it into sleep mode for enough time for the tumor to grow out of control. And that helps us understand why the conundrum of why our
immune system has not been more powerful in helping us take care of cancer. We know it's doing
a pretty good job. We know the stats that when people are taking immune suppressive drugs,
Peter, as you will know, as a physician for having a, say a transplant of an organ in the two years
following that period in that period where they need to take immunosuppressive drugs,
their rate of cancer goes way up. So we know that when the immune system is there, it is pretty
active. It is helpful, but in all too many cases, the cancer is able to run away and to evade. And this is one
of the methods it uses. That blue and that red spike allow it to go into that receptor and turn
off the T cells that came to the fight. And so Keytruda from Merck and other drugs like this
do a great job of plugging up that hole and saying, no, we won't
let that happen. But unfortunately, this drug does not work for everyone and not for every cancer.
So we need to experiment and make new drugs that work for more people, more cohorts of folks.
For melanoma, where this was first approved, it works for about 32% of the melanoma patients.
It helps them. But in about two thirds of cases,
the cancer after a while of remission progresses.
And so when molecules meet molecules,
what language do they speak?
They speak quantum.
And so while AI-based, AI-driven drug discovery
has been very helpful to us,
and in terms of taking a landscape, Peter,
of 600 million, say, potential compounds
and narrowing it down to, say, a few thousand.
Now that we have a few thousand,
we must ask the next question.
When that, not just molecule,
but now let's drill down further.
When we have the atom on the edge of the molecule
and on the edge of that atom, we have an electron
and that electron meets another electron,
does it bind together
do they meet do they bind and with what binding affinity and with what
characteristics and what's the confirmation and what's the shape and so
and so forth all these are quantum characteristics and now with the first
again generation right here in this room and around the planet that can now
understand this quantum language. Now you might
say, how about the quantum computers? I thought we needed a quantum computer to make this happen.
And what we realized and others realized around both academic and industry circles is that the
GPUs were getting so good. The same GPUs that have led to chat GPT three and then four and soon to come six and seven.
Those same GPUs that initially started as what?
What's the G and GPU?
Graphical graphics.
They started for better video games.
So every time a teenager is playing video games, thank that teenager because that teenager
is saving our butts.
That teenager is responsible for the rise of the GPU,
which initially was not made for AI,
was not made for quantum simulation,
but once we in the AI community realized that
the matrix algebra, matrices times matrices,
matrix times a vector, this matrix algebra
that was inherent in how we can have better video game rendering,
we can hijack that for representing neural networks.
Neural networks can be represented
as an image coming in as a vector,
and we can multiply it by the matrix of weights
in our neural network and our multilayer network.
That is the same mathematics in the firmware
of an NVIDIA chip, of an Intel chip,
of a Tesla D1 chip, a great GPU that Tesla uses.
Amazon has one, Alphabet has one.
Many companies. And what we saw five, six years ago is that the GPU wars were growing so rapidly that we would get a GPU that not only was great for graphics for video games and not only was
great for AI leading to the GPT revolution we see now. But what we surmised five years ago within our
team was that by 2021, 2022, we would have GPUs capable of doing a quantum simulation.
Amazing.
Of simulating this interaction. And sure enough, we published various papers just two years ago
and the first time in the world's record for doing that quantum chemical simulation,
showing hundreds of thousands of electrons, meeting hundreds of thousands other electrons
in like a speed dating, and allowing us to understand what that interaction would be.
So this, Peter, is what is now possible. And this is already impacting the folks,
the biopharmers we're working with in terms of neurodegen diseases.
That's the first one we're tackling right now, Alzheimer's and Parkinson's.
We've had 35 years of failure in neurodegen, 35 years.
And we need these kind of breakthroughs.
We all know in this room how much we need these breakthroughs.
But we're not going to get it unless we need these breakthroughs but we're not
going to get it unless we bring all the tools to the table and now the
combination of both AI and quantum finally coming together to say let's
down select from the large numbers that we have out there and use generative AI
as well to offer up new ideas but then test them through the funnel of quantum interaction to say,
let's de-risk this molecule, Peter, before we go to animal, before we go to human. Let's walk into
the clinical trial with a much better chance than two-thirds failure. Everybody, I want to take a
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All right, let's get back to our episode.
So what do you think in terms of price reduction and speed increase?
Well, great question.
I think if we, let me go back here.
If we look at these super depressing numbers,
the average right now is $2 billion to get molecule to medicine.
The average is 13 years to get molecule to medicine.
And so we need to bring this down to, you know, under a billion dollars.
Certainly we're hoping for four or
five hundred million dollars instead of two billion dollars, so a 70 plus percent cut in cost.
We're hoping for a dramatic decrease in the number of years. The majority of those 13 years are not
the clinical trials. The FDA and other regulatory bodies have actually done a pretty good job in the
last number of years recognizing the cries of the families the cries of the patients the cries of the clinicians they've said we're going to accelerate
if you have a breakthrough that we can accelerate let's do that if we can go with a pivotal phase
two and not even go to a phase three let's do that and look what happened also in terms of
even during the vaccine era a fast acceleration of approval as well. So what we see is that we've actually compressed the
time of clinical trial from seven, eight years. We can now get that done in about three to four
years in some cases, if it has an orphan disease or various other kinds of breakthrough status.
So that's not the issue anymore. We still need those human trials. It's the eight, nine, ten
years of pre-trial work, pre preclinical work that we need to really
compress down.
So that's what we need to impact right now.
That's where we need partners.
That's where we need collaboration to make this happen.
And this is-
Take me a decade forward here of the potential.
Yeah.
In terms of understanding.
I mean, the complexity of the immune system,
the complexity of even the intracellular mechanisms
and intracellular mechanisms, communications, is massive.
We understand a fraction.
Is this going to give us, I mean, we are quantum systems on a...
On a fundamental level, yes.
on a on a fundamental level yes um is how much will we unlock as we begin to dive through with these tools um is this where you expect to see the majority of the breakthroughs a decade out from now
i think it's the human body continues to surprise us the cellular pathways continue to surprise us
if you've ever seen a
complex subway chart of the metro in Paris or New York City, imagine that times 10 if you want to
look at cellular pathways. Times 100, right? Yeah. So, you know, all these different cellular
pathways. So we keep getting surprised every time we think, oh yeah, we've got that down,
nailed down, something else pops up. In neuroscience in particular, we're still at a very early phase of understanding.
We know so little in terms of neuroscience. We keep getting shocked by new discoveries.
Basically, the rule I have is that if I go back to my neuroscience textbooks,
I had the privilege of being taught by Eric Kandel, who later won the Nobel Prize because of the work I did. No, no joking. Nothing to do with me at all.
Eric Kandel was an incredible mentor for me, and also his bow ties are incredible too.
And I go back to that textbook. Yeah, I go back to that textbook, and it gets thicker and thicker as the additions go. But every time you go back to a textbook and um you know it gets thicker and thicker as the
additions go but every time you go back to a textbook and read a word read a phrase peter
that says never this never happens this always happens that's when you know a breakthrough will
happen because when we learned in our early textbooks that the brain never creates new
neurons after a certain age well guess what guess what? That fell down, right?
As a never.
And so we keep getting shocked and surprised.
So what I would say is let's take a humility approach,
a humble approach to the body and to the biology.
And let's say that let's go step-by-step
in understanding the systems.
And the body is an incredible system.
We know the tremendous healing power that the body has when you let it use its systems. And the body is an incredible system. We know the tremendous healing power that the body
has when you let it use its systems. And that's why immunotherapy, what I was showing before with
Keytruda, that is not chemotherapy. It's not there to, in a toxic matter, break down and kill off so
many cells, but it's there to help your T cell keep fighting, right, in a natural way.
That is the kind of therapies I hope we can bring out. But we need a deeper understanding.
When we get to the quantum level of understanding, this interaction of molecule to molecule,
we're just again at the precipice. As Newton said, I'm just at the tip of the ocean as the waves just come in. I've had the opportunity to play with a few pebbles and rocks on this wonderful beach.
And this is how we feel right now.
Amazing.
We're just at the beginning of this ballgame.
I'd love to go to some of your questions.
Please head on up.
Okay, Steve, you are fast, my friend.
Steve Brown, what do you got for Jack here?
So you talked a lot about the physical layer of quantum technologies,
and that's where it feels like all the action is right now.
And I'm curious in what ways should we be starting to reimagine
the software models based on quantum information theory.
For example, an undecided voter is like in a superposition of two states,
probably entangled with other people, probably in a contextual field nudging one way or another.
It sounds a lot like the same kind of mathematics that you're using for quantum information science.
And I'm curious when we start to reimagine the software side of this based on quantum
information theory, and you marry that with the quantum technologies, what do you see
in that combination?
And what should we be reimagining on the other side of this?
Thank you, Steve.
Great, profound question.
So Claude Shannon, famous for information theory, also at Bell Labs, years before Peter Schor, of course.
And his papers founded the field of information theory,
the field that we needed to establish computer science,
information science.
And then a number of years later,
others came after him and quantized that information theory.
And Claude Shannon, as you remember, was working for a telco, working for Bell Labs. And his task given to him by his manager was, help us understand
the communication of information over a noisy channel. And so he did that, and he did that
brilliantly. But now we understand that information is much more fundamental. One of the best processes of information is not on this earth right now.
It's not a GPU, it's not a TPU, it's not an IPU, it's not a quantum processor.
Well, it is a quantum processor, but not the ones we're making here.
It's a black hole.
A black hole, well, we understand a black hole in physics now.
We see it as the most efficient processor of information that we have in our
universe. And so we've now reimagined black hole physics in this informational sense. So I just
want to relate that because that's how profound Steve's question is. This is a deep, deep question
that goes to the heart of our new understanding of our physical universe. That at the fundamental layer,
we have an informational driven layer
that drives and helps us understand the context
of everything from a black hole
to a quantum computer on this planet
to our own biology.
And so coming back now to your question,
yes, a lot of companies are focused on the physics
of building these quantum computers. I alluded to the fact that we chose not to do question. Yes, a lot of companies are focused on the physics of building these quantum computers.
I alluded to the fact that we chose not to do that.
And one of the reasons is because of your question,
that while those folks are doing God's work
to build these quantum computers,
and we're encouraging them to do that,
others of us, including ourselves,
need to start focusing on the information layer,
the software layer.
And one of the things I love about the GPT revolution is that finally we can start getting really good code in a more scalable way
without artisanal coding. I call today's coding artisanal because Peter, in five or six years,
when I say to you, Hey, next Saturday, I'll be doing some coding. What you'll know is that I'm
doing that in the same way. If I told you today, I'm riding a horse. I'm not riding a horse because I need to get somewhere. I'm riding a horse in a nostalgic,
artisanal way. And so coding will become that way as well. And this is the opportunity now
where we need to create meshed code, hybrid code, code that is a series of lines of information.
And part of that code runs on the GPU, part of it
runs on a CPU, and part of it runs on a QPU, on a quantum processing unit. And this code should be
smart code. I don't want to have to put in brackets, hello computer, please run this next code on the
quantum computer. It needs to know that. So we can think of a quantum computer now in a new way,
as a subroutine to our main code.
Because quantum computers are not good at everything.
Please don't run an Excel spreadsheet on a quantum computer.
Please don't.
You'll not have a speed up.
You'll have a slow down.
And so, but there's certain things
that quantum computers do extremely well.
And they leverage the physics
of these quantum systems to do that.
These are not transistors.
They're not just representing ones and zeros.
They're doing something physically.
And one of the exciting things now about quantum computers is we're starting to use them in education.
And we haven't talked about education yet, which I'd like to get to at some point after some questions.
But now in our physics courses, when we teach students, we don't just say, oh, something could be in a superposition,
one of the concepts, Steve, that you mentioned.
It could be in some combination of state zero and one.
We ask the students to take this code that we give them,
or they write themselves, and run it
and make a real superposition on this planet,
right now in a, say, five or 10-qubit machine.
That's real.
That's not modeling it.
That is a real physical system in a state of
real superstition. Before us, students can never do that. We never had the ability before this
generation to actually have students do that. So back to now your fundamental question. Even as we
build the physical devices, we are giving more and more thought to how do we program these devices?
How do we mesh these devices into the larger
context? Because a quantum computer has no hard drive. It has no screen. It has no keyboard. It
has no compiler. It has no memory. It has nothing except the ability to do these incredible things
and then return back in information, a piece of classic information back to you, the GPU.
And so that kind of architecture needs new kind of software architects.
And so I'm sure it was said here in the AI panel yesterday that it's not so much that AI might replace all of us.
It's that we need to now adapt and use these AI tools so that we are not replaced by others who know how to use AI tools.
And the same thing now could be said in quantum.
We need to make sure that students today, that we ourselves, up-leveling,
up-skilling ourselves, none of us in this room have to know how to code. We need to know what
the computer is capable of and how to architect a quantum system into the system that we are
designing. Thank you, Steve, for that question. Amazing. Corey, let's go to you next.
Thank you. My name is Kurt Maxmein-Haling from Australia. I've got a question
about your sensor. And I don't know if many people know, but to get to net zero 2040, 2050, we need
four times more metals than we mine and recycle today, and six times more by 2050. Like, you know,
16 times more metals to build an offshore wind farm than a gas-fired power plant for the same
scale. And one of the challenges... Metals for batteries, things like that you're talking about.
Batteries, steel.
Like, it's something that even if you build a new material,
you need millions of tons of this material to build those things.
And to find these resources is very hard.
So about 20 years ago, Falcon magnetometer flies.
Very hard to find it.
So is your sensor capable, because given the sensitivity,
to detect more and find more of these resources?
So we pick better places to mine is the question.
Yeah.
Well, great question. And I'll let you broaden that question beyond just sensing for mining, but also sensing in general on a geophysical scale.
geophysical scale. So imagine you wanted to know underneath the earth, what the densities of the materials are underneath the place on earth that you're hovering over. Maybe you have something
called a balloon that you're hovering over a piece of land. And you want to know, is there a
different density that might house a certain thing called a missile underneath that thing, if you wanted to do that.
Or you might be looking for mining for metals.
In your case.
And so if you wanted to do these things,
you can then use this kind of quantum sensor.
And it would be advantageous to use that quantum sensor
at different altitudes, and so that's one reason why we think about these different platforms of passing sensors over different
parts of the earth. And also, of course, underwater, you'd want to know what the composition was
of the mantle underneath, right? The crust underneath that sea, that ocean to understand
what's there as well. And so these sensors do give you not just, you know,
through the magnetometry and then through adaptations, bringing it to gravimetry,
you can actually detect what the density of the materials are in different spots. Just like we
talked about how every spot on earth has a different magnetic fingerprint, every spot on
earth has a different density fingerprint as well. And so this is
absolutely possible. More work needs to be engineered in terms of the harness or the
capabilities that you might want to put around it. But certainly what you'd want to do is adapt the
same sensors we talked about here, adapt the GPU chip that goes on board, and then just train the
machine learning models. Instead of looking for the heartbeat, like we talked about, instead of
looking for navigation signals, you're now looking for the heartbeat, like we talked about, instead of looking for navigation
signals, you're now looking for a different signal.
And that's the beauty of machine learning, that we can adapt to that new context.
And so absolutely already, there's been a number of papers going around in terms of
detection of what's going on underneath the earth, again, for various reasons, not just
mining, though.
Thank you. Amazing. Jared, not just mining, though. Thank you.
Amazing.
Jared, let's go to you.
Hi, thank you so much for all you do, both of you.
So I have five-year-old twins with spinal muscular atrophy, which is kind of like ALS
in children.
And though there have been some amazing breakthrough drugs just recently in the last few years,
anyone like my children who did not get that treatment really early on, like in the first
few weeks of life, a lot of neuron damage has occurred. And there's a huge need therein in
all neurodegenerative diseases for neuron regeneration and drugs or methods that would
do that. I have a healthcare doctorate,
but I'm not a research scientist. I don't have a lab or I'm not an AI expert. And I've made some
really exciting connections here and have some ideas about how I'll move forward. But I wanted
to ask you, what would you do if you were in my shoes? How would you move forward to help your
children and others like them for neuron regeneration. Do you want to start?
We're going to have a few presentations tomorrow morning.
It's really, we have two presentations tomorrow.
One on a company that's basically in the regenerative medicine side of the equation from a stem cell exudate basis of how do you actually get these going another one which is based on technology
out of tufts that is regenerating limbs and i think the question becomes does the body have
the ability to regenerate complex systems because
you're not just regenerating the muscle but it's the nerves and the connections there is the
information for that early embryogenesis still there and can it be reactivated so there's a
company called pharmaceutical morphocyticals um uh and michael huff, the CEO, acting CEO, will be here to speak to that.
I don't know if Michael's in the room tonight by any chance. I would start with him and we'll
have those conversations more tomorrow. Do you have anything you want to add there?
I just want to add that, again, I would have a lot of hope. This is a difficult pathway.
In the foundation we set up, we help a lot of different families with very difficult chronic illnesses.
And so we've seen a lot over the years.
You know, when we think about the ability for neurogenesis, the ability to go back to the state that we were when we were creating lots of neurons and neurons were following a gradient and finding their place within the wiring, both in the brain and then the rest of the nervous system.
There's a delicate balance because obviously we don't want to revert everything back and then go into an explosive fetal growth phase.
But we're getting better at understanding this balance. We're not there yet, right? Those tools are not there today. Our hope is that by modeling this with better
tools, we can create this digital twin that allows us to understand those processes. So what I would
say is that it's about collaboration. Where I've seen this work, it's collaboration, it's patient
advocacy, it's associations, it's getting the dollars, but not just the dollars. Lots of dollars have gone to
lots of things that have not borne fruit. It's connecting with a community like this. And I've
always been very positively encouraged every time that Peter holds a visioneering, every time he
holds a gathering like this, I come away super pumped up because this is a crowd this is
a group that says yes when everyone says no yeah i do i think thank you for that having that that
point is really important um having the entrepreneur's mindset of saying i refuse to just let it be and to take it on, right?
We've had Martine Rothblatt speak here before,
who, you know, her daughter was dying from a lethal disease and she started with a high school textbook
and found a medicine to treat her, daughter Genesis,
and then said, well, this medicine is going to keep her alive.
Now I have to go and actually learn how to regrow lungs because the only cure is a lung
transplant and she's been building her company and building basically an abundant supply
of organs.
Hans, are you in the room?
Hans Kirsten?
Hans is the CEO of Immunist
and he'll be speaking tomorrow morning as well.
We've connected.
What's that?
We've connected.
You have connected.
Okay, fantastic.
Yeah.
The tools to understand
and begin to take our lives
and our health in our own hands are finally coming of age
at an atomic and molecular genomic level. And so the only time it becomes impossible is when you
give up. Thank you. Thank you for your question. Hey, everybody, this is Peter, a quick break from
the episode.
I'm a firm believer that science and technology and how entrepreneurs can change the world is the only real news out there worth consuming.
I don't watch the crisis news network I call CNN or Fox
and hear every devastating piece of news on the planet.
I spend my time training my neural net the way way I see the world, by looking at the
incredible breakthroughs in science and technology, how entrepreneurs are solving the world's grand
challenges, what the breakthroughs are in longevity, how exponential technologies are
transforming our world. So twice a week, I put out a blog. One blog is looking at the future of longevity, age reversal, biotech, increasing your health
span.
The other blog looks at exponential technologies, AI, 3D printing, synthetic biology, AR, VR,
blockchain.
These technologies are transforming what you as an entrepreneur can do.
If this is the kind of news you want to learn about and shape your neural nets with, go
to dmandus.com backslash blog and learn more.
Now back to the episode.
All right.
First of all.
Yeah.
Thank you so much for a beautiful evening and the energy is amazing.
So thank you for that.
I just want you to come back to what you were presenting with, you know, immunology and the checkpoint
inhibitors. And you were talking about reducing the time to develop those things, which I think
are important, no question about it. But to my knowledge also, you know, a number of them have
been developed and each time the cancer cells found a way around it, right?
So it's not just a question of blocking PD-L2, PD-L1 with scotruda.
It's, you know, iterative.
And that takes, you know, even if you reduce the time for development,
it's going to take decades before we, you know, outsmart the tumor.
So my question to you, and I think, you know, Peter hinted to that, is can we use the tools of, you know, you have developed today the superpower tools to perhaps not understand fully the biology of the tumor itself, the cellular tumor, because it's so complex, but at least get a hint of what's going to be the next thing to hit the, you know, the immune system in this case, you know, with another type of checkpoint inhibitors or what have you, or maybe even start thinking about different
mechanism of action rather than try to counter, you know, this molecule, try to, I know that
there's some technologies that are being developed around that, but, you know, uncovering more and
more of the mechanisms where you can attack the
production of Pdl2 and Pdl1 inside the tumor itself through new mechanism.
And so using this amazing power of computing power to really understand better the tumor
at the molecular level.
So not to understand everything, but the key element that allowed it to escape and allowed it to survive synthetic
killing, you know, synthetic lethal. As you know, oftentimes if you hit two different pathways,
the tumor cannot handle that. Can we use those tools to really uncover that faster that will
allow us to develop tools that are a bit more effective? Thank you, Francois. So just to hit
one key point on that right away, because you're absolutely correct. Part of what we know about cancer as we delve more and more into it as a
society is that we also have to look at the context of the cancer. Correct. So an example is not only
the microtumor environment, but also, for example, the microbiome. Naveen is here with Viome and
other people here are involved in the microbiome. Microbiome now, there's several papers that have
come out over the last five years
indicating that that's one of the modulators of the response of a human to checkpoint inhibitor immunotherapy.
That the reason why we have a third of people doing really well in melanoma on checkpoint inhibitors
and then two-thirds not doing so well in terms of dual response after a year is partly one reason.
Again, it's never one silver bullet, but of dual response after a year is partly one reason again it's never
one silver bullet but one reason could be the microbiome and so it's very important for us to
delve into that microbiome has not traditionally been part right of standard standard of care right
and so as it becomes more mainstream more and more places now will incorporate that into an
integrative way of understanding cancer, that becomes another tool
in the tool chest. So what we find with cancer and the reason why it's so elusive is we love to say
that it's just one mechanism and just looking at this one narrow thing and that's the way to get
your PhD and your postdoc and so on and so forth. But unfortunately, that's not what cancer cares
about. They don't care about your PhD. What cancer wants to do is it wants to survive. It's its own organism. It now wants to move and survive. And so it will do
anything to do that. And so looking at that larger context, that's where we've had now some more luck
in looking at that larger context. So I agree with your premise. And that's why these tools
that can model much more high dimensional kind of systems are so critical. I want to make
sure we get to more people though. So thank you. Thank you very much, Francois. I would like to,
we have five questions standing. I'd like to do them quickly so we can wrap and let people.
I want to end on education though. I want to make sure we get education.
We'll do that. Mike. Yes, I'm just wondering, does your diamond sensor sense the direction
as well as the magnitude of the magnetic fields?
Great question.
Yeah, so it is a vectorized sensor.
It's a great question.
And we didn't have time to go into it today.
But in the heart, for example, why would you want to know direction and not just the picture?
Well, blood flow, for example, obviously, you'd want to see the direction of that blood flow to start looking at the health of not just the overall heart picture, but the valves and looking at is the blood pumping in this way and the different
chambers of the heart. All that is because it has a vectorized sensor, not just the magnitude. So
you're absolutely hitting on a key point. Again, with EKG and other kinds of sensors,
we don't have that kind of vectorization, so we can't see it. And
so that's part of why Cleveland Clinic and all these places are excited about and have been
using this technology a long time. But now it's time to take vectorized cardiac diagnostics out
to the masses. Great point. Thank you. Annie. Thanks so much. I wish that I had a teacher
like you when I was taking material science engineering.
Quick question. There are so many challenges that you can choose to just dive into at this point.
How are you choosing the use cases and the challenges? Because I can't even imagine how
you're doing that. And then number two, I used to work at Genentech. Do you see quantum solutions
supplanting animal testing eventually?
Yeah, so great questions.
On the first question, how do we choose?
You're right.
It's a tough thing because quantum sensors alone, just one part of what we do, there's so many applications.
And one of the, Kirk, before, you know, asked the question about using it in a totally different way, which, again, is very, very exciting.
We've chosen to focus on cardiac care and navigation to start with. We've chosen to say, if people want to partner with us, we're happy to
partner with them to look at other applications. We can't do everything. There's just no way we can
do that, but we can offer some fundamental stacks that other people can then use. I'm a fundamental
believer, and Peter and I have talked about this over the years, of making sure that we can get the core stack technology out on a licensing basis to lots
of academics and lots of startups out there. And let evolution take its course.
Yes, exactly. And so one thing we're doing, we're actually now investing in young startups,
right? So if folks have ideas or if there's venture capital folks in the room, we like to
co-invest with
startups alongside them and say, hey, let's invest in this startup and maybe they can use
this technology in a totally new way. I think that the old, you know, B school of the 1980s thinking
is, you know, this company must do this and must focus on this and then keep your all IP in the
big moat and things like that. I think we've now seen,
you know, that there's a different way of doing things. Elon famously gave away the patents,
opened up the patents to the Tesla because he wanted to see more people out there. I think
that is the way to go. The way to go is to publish out to, you know, we publish as many papers as we
can to show people what we're doing. We are offering up the stack out there so people can
license it and run with it. And we'll even give them money, you know, to invest in them and run
with them. So that's in a sense of what the best way, you know, to go with that, to go with that
is. Yeah. Thank you, Annie. All right, Nora. Hi. In the image where you showed the noise, what is the reason why you couldn't just take a baseline read without a human in the room of what the noise was like with the elevators and then take a second one and delete it or triangulate with three?
triangulate with three? Yeah, no, great question. So one of the reasons is, yeah, certainly you'd want to take a baseline reading and you want to get a sense of the noise in the room. And
we do try to do that. But even the human body offers a lot of noise. That's part of the issue.
One of the things that's producing magnetic fields is also our brain. It's a very weak magnetic field,
but it is a magnetic field as well. so and the other humans in the room also you
know could also be be offering up new noise as well so there's a lot of noise factors there so
we have to have you know better and better machine learning tools to really understand here's the
good news though because the heart has this pattern to it right where it's beating x number of times a
minute it's we have a way to anchor ourselves
into ground truth right um it would be much more difficult if the heart were this chaotic
kind of ball game that we couldn't you know understand at all but in fact we can understand
the regular heartbeat and that actually allows us to go into um chaotic fibrillation as well
and understand that because once we lock onto the signal down, then the ML
algo is like, that's my signal. I'm going to that. And thank God, again, these GPUs,
when you have a device like this, you cannot be going to the cloud and sending processing to the
cloud, both for privacy reasons and latency reasons. You need to do everything on board.
And again, five, six years ago, these GPUs were not powerful enough to do that. But today, we can do that.
Thank you.
Okay.
Anusha.
Jack, as you mentioned, this is one of the most powerful technologies that will transform our world.
And how can we make sure that this is not blocked up in certain countries or certain large corporations?
locked up in certain countries or certain large corporations, and it's truly democratized, and every person in every part of this world can get access to it and innovate with it and take
advantage of it. Well, this is what Peter and I, we didn't get to this topic, but Peter and I wanted
to talk about the growing quantum divide. I think all of us in this room were at the point 20 years
ago, and we remember the launch of efforts to attack the digital divide, right?
Where digital divide is, if you don't have a cell phone starting 20 years ago, and then starting 10
years ago, with the rise of the smartphones and all the services you can get, you were blocked
off from health education, you're blocked off from financial services, you're blocked off from
e-commerce, and selling your wares onto Etsy, and you know, lots of places around the world,
you're blocked off from taking loans. I served on boards of microfinance banks for 10 years, and the rise of the smartphone was
a critical tool for us to get to people and to engage with them with their loans and give them
financial education so they could actually build their businesses with the loans that we were
giving them. But all that was cut off from you if you were in the billions of humans who did not have access
to that and now 20 years later finally at the rate of about 250 million people a quarter right now
people are joining the internet for the first time right now and so we're now squeezing that
digital divide down but as that is happening we've opened up unfortunately a quantum divide a divide
where there's about 20 countries in the world that have national blueprints.
Australia is one of them with incredible quantum science in Australia, UNSW and many universities there, US, UK, Canada, so on and so forth.
But 170 countries do not have quantum programs.
And we are very, very concerned because those have-nots will then have to pay rent to the haves in terms of the medicines, the battery chemistry, the material science, the quantum sensors for medical diagnostics, the quantum sensors for navigation.
All this, the have-nots will have to then find from the haves.
That is a problem.
And so what fundamentally it comes to is the topic that Peter and I wanted to focus on,
which is the educational topic. The good news is we don't need 100,000 people per country to know quantum. You need literally just a few thousand people in each country to know this. And the
question is, how can we do this? We have a new initiative with the World Economic Forum, many
others as well, not just us. It's a global issue. And we want to nip
this one in the bud way before we did the digital divide. I would say I failed in the digital divide
just to take personal responsibility that I tried, I worked on it, and I did not make much of a
difference at all in the digital divide. I went to many, many countries where we were doing
microfinance banking, and we tried to get programs going, and we worked with Grameen Bank and others, and great efforts.
But ultimately, we didn't have much of a difference.
We didn't make much of a difference.
And one of the things that animates me now about this is my failure in digital divide, and I hope we can do a better job here.
Amazing.
All right, guys. a better job here. Amazing. All right guys last one standing
here. All right thank you very much. Maximilian yes please. You mentioned early on that the climate
change issue is I mean you had the epiphany and it seems to me that that's a very important use case
for your tools and I would like to ask you whether you could elaborate a little bit on that.
What is it we're talking about?
Are we talking simulations to decarbonize the economy?
Yeah, let me just briefly touch on that.
I also want to thank Shiv Kempka, who might be here tonight, who came with us on the Antarctica
trip and had great contributions on that trip as well. But what we realize is that
using these tools, number one, we need to get beyond just lithium ion in terms of battery
chemistry. If we want to scale battery chemistry, not just for electric vehicles, which is critical,
but also for stationary, the larger impact is stationary batteries, right? To store not just
solar and wind, but even whatever electrons you have by getting them at
night and off peak and storing them in a building like this and then using them by day that arbitrage
right allows us to shave the peak and to have better more efficient use of whatever electrons
we're making this battery chemistry there's many proposals out there in the academic literature
zinc air aluminum different different ideas of material
science for the anode, the cathode, the electrolyte, the membrane, all this kind of stuff. But this
needs quantum simulation. We need to do the billions and billions of combinatorial runaway
in terms of making that new chemistry happen. Again, just like clinical trials, if we physically
build each one of these batteries, we'll never get get there and that's why we're still stuck with the current uh you know there's no moore's law when it comes to battery
chemistry right uh there's e room's law anyone know what e room's law is e room's law is moore's
law backwards um and so okay it's slowly getting out there okay um and and so we haven't seen
moore's law in terms of battery chemistry, in terms of the density, power density, energy density, any way you want to cut it.
We now need to use these tools and look at and model billions of combinations of chemistry so that we can have the breakthroughs.
Not instead of lithium ion.
We'll use lithium ion.
But alongside that, we need specific chemistries for other use cases.
So that's an issue for climate change.
Perovskites.
Does anyone know perovskites?
Any ideas what perovskites are used for?
We've talked about perovskite here.
Good.
So perovskites for solar.
We're still stymied by critical issues of stability.
After just six or 12 months, sometimes these things are breaking down.
We need to do the combinatorial billions of simulations to get perovskites more stable, as an example, and get the lead out and cadmium out, so on and so forth.
And that's what we need to do.
So for climate change, that's one thing. boat, towed it with us, and did magnetic readings underneath the Southern Ocean, in the Southern
Ocean, so that we can do better ROV, better underwater drones, so we can take better
measurements of how the sea is changing. And so this is all part of a more advanced climate science
that we can get to. Thank you. Thank you. Jack, you're amazing. Thanks.
Let's give it up for this man.
You know, I write books for popular consumption.
He writes this quantum computing and applied approach.
I'm flipping through it. This is a beach read, Peter.
And this is giving me nightmares.
For these people in this room, it's a beach read, I think.
This is bringing me back to...
We have a sophisticated audience here.
Bringing me back to my quantum physics
and complex calculus classes
that were not a cakewalk for me, as they were for you.
Buddy, thank you.
Are you able to stick around for folks
to spend a few more minutes with you?
Yeah, we do have to fly out tonight. But Peter, I just want to thank you for bringing
this incredible group together. All of you in this room. I just I think it's very clear. I'm
sure you've now been spending two and a half days with Peter and the ideas. Every time that Peter
and I collaborate, I come away come away inspired energized and i'm sure
i can speak for everyone here that you have that same um let's guys let's give it up for jack
hittery