Speaker 1: Imagine a force, a force so so disruptive that if
a rival power got their hands on it first, it
could just completely rewrite the map, geopolitics, the economy, even
you know, the way we live. It can make everything unrecognizable.
Speaker 2: And for the better part of a century, almost eighty years,
that fear has really been all about one thing, the.
Speaker 1: Atom, exactly. But today that fear has a new name,
and it's not fueled by nuclear fission. It's fueled by
algorithms and just a terrifying amount of electricity. Welcome to
Thrilling Threads, the place where we pull on the most
crucial filaments of information to see exactly what the future
is being woven from today.
Speaker 2: We're doing a really, really deep dive into a concept
that's being called Manhattan Project two point zero. Our mission
here is to understand the stakes, which are they're existential,
and the technology and the history that's all wrapped up
in this new race for digital dominance.
Speaker 1: Right and our source material for this is taking us
deep into some reporting that comes from a very specific place, Oakridge, Tennessee,
a place that's basically synonymous with the original nuclear age.
We're looking at the arguments and the tech breakthroughs laid
out in the video transcript Manhattan Project two point zero,
which comes from.
Speaker 2: The Daily Wire, and that location Oakridge is just so
key to all of this. It's the whole story in
one place. It was the epicenter of uranium enrichment for
the original bomb.
Speaker 1: And now eighty years later it's ground zero for the
global AI arms race. It's home to the engine of
this this whole new project.
Speaker 2: It really is.
Speaker 1: So the stakes, as the source material lays them out,
are I mean, they're intentionally provocative. The core argument is this,
the United States is an existential tech race, an AI
arms race with China.
Speaker 2: And if you just look back at the original Manhattan Project,
the urgency, you know the reason for all the secrecy
and they basically unlimited budget. It was this terrifying idea
that Nazi Germany could get the bomb first, right, and
that was seen as a direct threat to democracy, to
the entire free world.
Speaker 1: And the source makes that parallel crystal clear. It says, look,
if Germany had won that race, our world today would
be unrecognizable. And it argues that the danger of losing
the AI race today is of that exact same magnitude.
This isn't about a business advantage. It's a fundamental shift
in global power.
Speaker 2: Precisely. The argument is that AI it's not some slow
academic thing anymore. It's hitting a critical mass like right
now and in the next few years, it's expected to
just change everything finance, science, and maybe most critically, national defense.
Speaker 1: And the threat is defined very clearly. China is going
after this technology aggressively, and if China were to get
what they call a meaningful lead in AI, they argue,
it would create a different world in the future, one
where the US is probably no longer the main global leader.
Speaker 2: So the goal then becomes really unambiguous. It echoes the
Cold War, it echoes the atomic age. America has to
lead and America has to win.
Speaker 1: And this whole story, this convergence of nuclear history and
digital future, it's literally happening in one place. Years ago.
Oakridge was enriching uranium. Today it's home to the supercomputer Frontier,
the engine for this Manhattan Project two point zero. It's
the nexus point where the most powerful energy of the
past meets the most powerful intelligence of the future.
Speaker 2: That's an incredible story.
Speaker 1: Okay, so let's really unpack this before we get into
the machine itself frontier, and you know the algorithms it's running.
The source material makes this incredibly strong case that the
foundation of this new arms race isn't software, it's not chips,
it's raw brute force energy.
Speaker 2: This is such a crucial point, and it completely shifts
how you think about AI. It takes it out of
the sort of digital cloud and puts it squarely on
the power grid. And we hear this from leaders in
the field, people like open AI's co founder Greg Brockman
and the former Energy Secretary Chris Wright. They see AI
as this intensely, almost frighteningly energy hungry business.
Speaker 1: Brockman's framing of it is so powerful because it just
strips away all the mystique. He basically defines AI as
manufacturing energy into intelligence.
Speaker 2: Yeah, and just think about that for a second. When
you're training a massive model, something like a GPT four,
it eats up the energy equivalent of heating thousands of
homes for a year maybe more.
Speaker 1: Wow.
Speaker 2: And the next generation of these models, the ones pushing
into the trillion parameter range, I mean, the energy they'll
need is completely unprecedented. So if you start thinking of
AI as a factory, you know, an industrial process for
making knowledge.
Speaker 1: Then the energy infrastructure it needs becomes very physical, very industrial,
not just digital exactly.
Speaker 2: And that demand is only going to grow and it
could very well outstrip what our current grid can even handle.
Speaker 1: But here's the really interesting irony that the sources point out.
While AI is consuming all this massive energy, it's also
expected to help unlock more energy.
Speaker 2: It's a fascinating loop, right, consumption and production loop. The
idea is that AI is so good at optimizing these
incredibly complex systems like power grids, energy transmission, even predicting
when a power plant needs maintenance, that it could create
huge efficiencies, so.
Speaker 1: It actually helps us produce more usable power overall. It's
a feedback mechanism. The intelligence helps solve the very energy
crisis it's creating.
Speaker 2: So if having limitless reliable power is the foundation for
winning this race, the next question is obvious what energy
source can actually sustain that pace? And the source Materials
is very direct about this.
Speaker 1: It points to nuclear absolutely. The US today we rely
mostly on oil and natural gas, and they're huge dominant sources.
But to scale up to the level you need for
this kind of two hundred and forty seven expansion of
AI and EXAs scale computing. Nuclear is presented as really
the only viable solution that can scale that quickly and
that reliably, and they.
Speaker 2: Really stress its unique factor, the thing that a supercomputer
like Frontier absolutely needs, which is that nuclear is the
only technology that works whether the sun is shining or
the wind is blowing. It's not intermittent. You get that solid,
reliable base load power.
Speaker 1: And you can't run a system with eighteen thousand blits
on power that dips or has brown outs. You need absolute,
unwavering energy, surety.
Speaker 2: But the source goes even further than just electricity for computers.
It talks about a not distant future and maybe a
lot closer than we think, where nuclear also provides high
temperature process heat. And this is where the strategic argument
for nuclear gets even deeper.
Speaker 1: Okay, explain that for us, because electricity is obvious, but
process heat that's an industrial idea that might not immediately
click for everyone.
Speaker 2: Right, So high temperature process heat is basically the thermal
energy you need for heavy industry. The source calls it
the single most important energy source in the world. If
you want to make core manufacturing materials.
Speaker 1: Things like steel, plastics, alumina.
Speaker 2: Exactly, steel plastics, ammonia for fertilizer, aluminum. All those processes
need incredibly high temperatures, and right now we get that
by burning massive amounts of natural gas or coal. But
if you can replace that fossil fuel with nuclear heat,
often from these new small modular reactors or s, you
get two huge advantages.
Speaker 1: Okay, So first, I'm guessing you cut emissions in a
really tough sector drastically. Yeah.
Speaker 2: And second, you decouple your entire industrial base from volatile
fossil fuel.
Speaker 1: Markets, which is a massive strategic.
Speaker 2: Advantage, a huge one. The source argues that if you
control the cleanest, cheapest, most reliable source of this high
temperature heat, you control the production of everything that builds
a modern economy and a modern military.
Speaker 1: And this leads us right into the political framing in
the sources which connects this whole tech challenge to a
sense of policy urgency. The former Energy Secretary's view is
pretty forceful. He argues that America will lose the AI
arms race if we strangle innovation.
Speaker 2: Yeah, that phrase strangle innovation is very loaded. The source
expresses this clear frustration, suggesting that the previous four years
were and this is a quote consumed with theology regarding
the environment.
Speaker 1: Implying that environmental regulations were holding back essential energy sources
like nuclear and gas.
Speaker 2: Right They see that focus as a kind of self
sabotage when we're in this critical global race.
Speaker 1: It's a strong claim and one we have to look
at impartially for someone listening who might not follow energy
policy that closely. The source is really pushing for an
innovation first approach. But what's the counter argument there? What
about balancing that expansion with climate goals?
Speaker 2: Well, the standard counter argument is all about long term
risk and global leadership on climate. Proponents of regulation would
say that, sure, we need to expand, but if we
do it unchecked, especially with carbon intensive sources, you create
these massive costs down the line.
Speaker 1: Through things like extreme weather damage or even trade penalties exactly.
Speaker 2: But the viewpoint in our source material is really prioritizing
national security and tech dominance above all else.
Speaker 1: Right now, which brings them to their solution unleash American energy,
make nuclear a huge part of an all of the
above energy portfolio, and the competitive angle is key. They
see two camps in the world, one that favors collaboration
and one that's all about national competition.
Speaker 2: And the source is firmly in that second camp. The
assumption is that if countries like China or Russia make
a breakthrough, they're not going to share.
Speaker 1: It, So relying on collaboration is just too risky for
the US.
Speaker 2: That's the argument. The imperative is clear. America has to
out innovate everybody on the planet on energy because energy
is the bottleneck for the entire AI engine.
Speaker 1: Okay, so this is where it gets really interesting. We've
talked about the fuel, this idea of limitless reliable nuclear power.
Now let's look inside the engine itself. Let's talk about Frontier.
Speaker 2: Frontier is just it's not just a big room full
of servers. It is the world's fastest supercomputer for open science.
When it was unveiled, it was the first machine ever
confirmed to break the Exascal barrier.
Speaker 1: Okay, we need to go beyond the simple comparison of
you know, fifty times your laptop. What does xaskel actually
mean in real terms?
Speaker 2: Well, the jump from petaflop, which is a quadrillion calculations
per second flop is just massive. Exascal means Frontier can
do a quintillion calculators per second. That's a one with
eighteen zeros after it.
Speaker 1: That's I can't even picture that.
Speaker 2: To try and visualize it. If every single person on
Earth did one calculation every second, it would take them
four years to do what Frontier can do in one second.
Speaker 1: Wow.
Speaker 2: Okay, and you need that speed because the algorithms these
scientists are writing have you know, billions of parameters.
Speaker 1: And they're tackling problems that are just genuinely unfathomable for
a human mind. The example they give is working with
a company like ge to design new aircraft gifts. I
mean that's calculating fluid dynamics, material stress, combustion, just an
insane number of variables.
Speaker 2: All at once, precisely. And if a simulation takes weeks
to run, it's basically useless for a company that needs
to make quick design choices. Frontier shrinks that time from
weeks down to hours, so engineers can test just exponentially
more designs. That's what accelerated innovation really means.
Speaker 1: A key point, and this is a parallel to the
original Manhattan Project, is that the technology for a machine
this complex often doesn't even exist when the project.
Speaker 2: Starts exactly when Oakridge decides to procure a system like Frontier,
the tech needed to actually hit that exast scale goal.
It hasn't been manufactured yet. They commit to building it
knowing they'll have to innovate it into existence through these
really intense partnerships.
Speaker 1: So in this case, that meant working hand in hand
with Hewlett Packard Enterprise and AMD.
Speaker 2: Right, and it wasn't just about assembling parts. It was
about pushing the fundamentals of chip design and maybe even
more importantly cooling.
Speaker 1: Okay, so what were the big engineering hurdles they had
to clear.
Speaker 2: Well, the biggest one in modern supercomputing is usually the
interconnect and memory bandwidth, basically how fast all the different
processors can talk to each other and get to the
data they need. Frontier was designed with this really integrated
CPU and GPU architecture, which required a completely bespoke design
from AMD to cut down latency.
Speaker 1: But the innovation that oak really pushed for, and this
ties right back to our energy discussion, was the cooling system.
Speaker 2: Yes, this was a massive crucial push the implementation of
warm water cooling. It's something people overlook but it's a
revolutionary piece of engineering. You have eighteen thousand blades producing
that much heat. Cooling is normally your biggest energy cost.
Speaker 1: And the result was pretty staggering, right as savings of
at least forty percent in our energy cost.
Speaker 2: A forty percent savings on the cooling for the world's
fastest computer is an enormous advantage strategically and financially. They're
not using these giant chilled air conditioned rooms. They're flowing
warmer water directly over the components, which is way more efficient, and.
Speaker 1: They can reuse that captured heat.
Speaker 2: I assume often. Yes, it creates a much more sustainable system.
It just shows how oak Ridge is pushing the boundaries
of both the hardware and the efficiency.
Speaker 1: At the same time, and that innovation trickles down. You
mentioned the chips they helped design became commercially available just
a year later.
Speaker 2: That rapid spin off is a huge part of the mission.
Bridge acts as this forcing function for the whole industry.
They demand technology a year or two before the market
is even ready for it, and in doing so they
basically fund and test the absolute bleeding edge, which then
cascades down into commercial products for everyone, which.
Speaker 1: Brings us to the core philosophy of how Frontier is used.
And this is what really separates Manhattan Project two point
zero from the original. It's the mandate of open science.
Speaker 2: That is the defining line. The machine is available to
scientists with really big problems, the kinds of problems no
single university or private company could ever tackle alone. But
there's a catch, a quid pro quo.
Speaker 1: You have to agree to publish part of your work.
Speaker 2: You have to publish it in the scientific domain. This
ensures what they call true open science where everyone benefits.
It's a very deliberate rejection of the extreme secrecy of
eighty years ago.
Speaker 1: Yeah, the leadership at the facility is really clear about it.
They say, we don't do the secret stuff because we
want it to be available to the public.
Speaker 2: So, even though the whole thing is set against this
backdrop of intense national competition, the actual engine of research
is in a way democratized for global science, and that
creates this profound duality. It's just fascinating to think about.
Speaker 1: So we've got the energy, we've got the exasma machine.
What are they actually doing with it? How do these
eighteen thousand blades translate into real scientific breakthroughs?
Speaker 2: Right? Now this is where it all comes to life.
The collaboration is so big, with researchers from all the
national labs and tons of universities that they're calling it
the one thousand Scientists aijim I love that the goal
is to integrate these sophisticated AI models with what human
scientists are already doing and just exponentially accelerate their work.
Speaker 1: Well, let's start with one of the biggest examples they
give the search for nuclear fusion.
Speaker 2: Fusion is famously notoriously difficult because plasma, the superheated stuff
you need, is just so chaotic and volatile. So scientists
are using AI on frontier to come up with new
designs for experimental reactors modeling these incredibly complex magnetic fields.
Speaker 1: And a human team might spend weeks just simulating one
design to see if it's even.
Speaker 2: Viable, right, But the AI can run thousands of different versions,
instantly tweaking parameters, spotting flaws, and even proposing new designs
that a human might never think of. And that acceleration
is everything, because every month we save infusion research gets
that much closer to potentially limitless clean energy. The AIA
just speeds up that whole cycle of trial and error.
Speaker 1: So another area you mentioned is manufacturing and material science,
especially at the neutrons scattering division at oak Ridge. This
is a bit technical, so let's slow down and really
explain how studying atoms applies to this arms race.
Speaker 2: It connects directly to industrial strength, which is fundamental. They're
using neutrons to literally map the atomic structure of materials.
You take a material, say a new metal alloy, you
put in a beam line, you hit it with neutrons,
and the way those neutrons scatter gives you data with
atomic resolution.
Speaker 1: So you're basically getting a map of where every single
atom is in that material exactly.
Speaker 2: The raw data these diffraction peaks are just massive streams
of information that tell you exactly where the atoms are
and whether the material is under stress. And this huge,
complex data stream is then immediately quote shoved into a
machine learning or AI, and the.
Speaker 1: AI isn't just storing the data, it's actively interpreting it
in real time, seeing patterns that would take a person
days to figure out, and then making suggestions.
Speaker 2: That's the critical difference. The AI takes that instantaneous data
and actively steers the experiment. It gives predictive feedback to
the scientist, telling them how to optimize the material or
adjust the manufacturing process.
Speaker 1: Wait, if the AI is steering the experiment, how do
the humans stay in control? I mean, how do they
even understand the physics behind what the AI is suggesting?
Speaker 2: That's a great question. The AI isn't replacing the scientist,
it's just making the experiment faster and more efficient. So
the AI is typically optimizing the parameters of the neutron beam,
the angle, the intensity, based on the atomic stress it's seeing.
The human scientist still sets the overall scientific goal. The
AI just becomes this hyper fast, tireless optimizer, so the
human can focus on the big picture physics instead of
the tiny details.
Speaker 1: And the source gives this just stunning real world example
of this inaction, measuring the structure of an actual gas
engine cylinder head while the engine is running.
Speaker 2: I mean, that's just phenomenal. They can sync the pulse
of the engine with the pulse of the neutron beam
and capture what's happening inside the combustion chamber in real time.
And the goal is totally applied science. Develop materials for
cars and planes that are stronger lighter and cheaper by
understanding and manipulating their atomic structure with AI guidance.
Speaker 1: The computational power of Frontier just lets them train these
AI models so quickly on so much data that the
predictions become incredibly accurate.
Speaker 2: Exactly. It shortens the entire materials development cycle from years
down to months or even weeks. It's a speed that
was just unthinkable a decade ago.
Speaker 1: And finally, beyond physics and materials, they're also using Frontier
for health data.
Speaker 2: A huge area for public good. They have users who
come in with these vast protected health data sets and
they're looking for complex cancer related trends across huge populations.
By speeding up that analysis, the AI can spot subtle
correlations in treatment success in genomic markers that would be
impossible for a human team to ever find.
Speaker 1: The goal being to help clinicians make better decisions.
Speaker 2: Way faster and ultimately save lives.
Speaker 1: Yeah, so we have to connect this back to the
bigger picture. Oakridge is special not just for what it's
doing today, but for what it did eighty years ago,
that secretive, profound and dangerous leap it engineered.
Speaker 2: The history really gives the Manhattan Project two point zero
analogy its weight and the sources take us right back
to the birthplace of it all, the X ten Graphite Reactor.
Speaker 1: Which is a National Historic Site now it is.
Speaker 2: It started operating on November fourth, nineteen forty three, and
it was the birthplace of operational nuclear power. Its whole
job was just to prove that a controlled chain reaction
was possible. Workers loaded thirty one tons of uranium slugs
into this huge twenty four foot cube of graphite.
Speaker 1: And the graphite acts as a moderator, right, It slows
the neutrons down so they can sustain the reaction exactly.
Speaker 2: And once that uranium was irradiated, it was incredibly radioactive
and it contained these tiny amounts of a brand new element, plutonium.
So that material was taken next door to a chemical
separation plant where they had to work behind heavy shielding
to isolate that tiny bit of plutonium. Yeah, they were
literally inventing nuclear engineering as they went, figuring out the
safest materials, the best shielding all of it.
Speaker 1: And what's so fascinating is the extreme secrecy and compartmentalization
they needed to pull it off. I mean, how do
you keep seventy five thousand people from knowing what they're building.
Speaker 2: It was incredibly strict. The sources say most of those
seventy five thousand people had no idea what the final
goal was. They only knew their one tiny job. A
worker in one building might be told their separate nickel
while someone next door is purifying a liquid. Neither one
knew they were contributing to a weapon.
Speaker 1: They would just do their job and pass the component
to the next room, completely in the dark until the
bombs were dropped, and then the government was very open
immediately that they were made at Oak Ridge. The psychology
of that is just staggering, It truly is.
Speaker 2: I mean, can you imagine working under that kind of security,
knowing your work is vital, but having no idea you're
building the thing that will change the world forever. And
that's such a stark contract with frontiers mandate today of
open science.
Speaker 1: But the story of the X ten reactor didn't end
with the war. It actually became the foundation for the
entire post war nuclear.
Speaker 2: Age, right. It transitioned very quickly from a weapon site
to a science and engineering center. The scientists there realized
they had this unprecedented scientific tool, so it immediately became
the training ground for the very first nuclear engineers. Because
they were the only ones who had the expertise and
a working reactor. They were inventing the field.
Speaker 1: And that expertise gave the US a map massive strategic
advantage for decades.
Speaker 2: The most famous example they cite is Admiral Hyman Rickover.
He came to the X ten reactor specifically to train
and figure out how to put a safe, working nuclear
reactor onto a submarine, which was a game changer, a
huge one. The ability for a nuclear sub to stay
under water almost indefinitely silently gave the US Davy this
huge strategic advantage over its rivals.
Speaker 1: Now, if we connect that historical risk to today's AI race,
the source highlights this deep fundamental tension between AI optimism
and that historic atomic fear.
Speaker 2: This tension really defines the whole conversation. On one side,
you have AI innovators like Brockman, who sees AI not
as a crisis, but is this opportunity for extraordinary growth
for the human race. He's focused on all the powerful,
benevolent things we can do with it.
Speaker 1: But the parallel to the atomic age immediately brings up
all the moral and ethical conflicts that the original scientists face.
Speaker 2: Right. It's the explicit parallel to J. Robert Oppenheimer, who
later saw atomic energy as a grave crisis because of
the immense, unpredictable power it unleashed on humanity.
Speaker 1: And that tension, that risk of the unknown. It was
there from the very beginning, even in the design phase
of the X ten back in nineteen forty three.
Speaker 2: It was DuPont, the contractor. They realized the dangers, the
risk that the reactor could run out of control, kill workers,
or send nuclear particles into the air. They were stepping
into completely new, terrifying territory. And the source captures this perfectly.
It says the project's leaders recognized the power of unleashing
the atom, but we also realize the great responsibility that comes.
Speaker 1: With it that duality. Great power demands great responsibility, and.
Speaker 2: That defines both the original Manhattan project and this new
AI endeavor with Frontier Today.
Speaker 1: What a monumental, just thrilling story of technological continuity. From
the X ten reactor, which taught the world how to
harness the atom, to the Frontier supercomputer, which is teaching
AI how to optimize our future.
Speaker 2: We've really seen these three core threads all in twined.
First this massive essential link between national dominance and scalable
nuclear power. That's the physical fuel for this new race right.
Speaker 1: And second the incredible speed of innovation needed, which is
personified by Frontier and its contradictory mandate for open science,
which is the total opposite of the original project secrecy.
Speaker 2: And Third that inescapable historical and ethical tension that comes
back every single time humanity takes one of these enormous leaps,
the tension between the promise of extraordinary growth and the
threat of an unrecognizable world.
Speaker 1: The focus today at Oakridge, at least on the surface,
is on solving these really big problems fusion reactors, cancer treatments,
new materials, and it's all under this banner of true
open science for the greater good.
Speaker 2: And yet the political framing that's driving all the funding
and the urgency is completely geopolitical. It is framed as
a competitive nationalistic arms race against rivals like China and Russia.
It's a zero sum game that America has to win.
Speaker 1: This dichotomy benevolent science versus nationalist competition. It brings us
to the profound meaning of scientific freedom itself, which is
where the sources leave us.
Speaker 2: It's a really powerful quote that argues the value of
sciences more than just material.
Speaker 1: Yes, the concluding thought is that science has profoundly altered
man's life, not just materially, but in the ways of
the spirit. It's extended the range of questions we can
even choose to answer, and it's extended our freedom to
make significant decisions about our own future.
Speaker 2: And the source ends with this powerful defense of free inquiry.
It says no one can predict what vast new continents
of knowledge the future of science will discover. But we
know that as long as men are free to ask
what they will, free to say what they think, free
to think what they must, science will never regress, and
freedom itself will never be wholly lost.
Speaker 1: Which brings us to our final question for you, the listener,
And it's based entirely on these competing narratives we've talked about.
On one hand, the scientific community at Oakridge believes this
AI push is for the greater good and open science.
But on the other the political framing is entirely about
an arms race.
Speaker 2: So what's your stand on that duality? Do you think
transformative technologies like AI are best developed in a fiercely
competitive nationalistic race where the US has to out innovate
everybody on the planet. Or does the core requirement of
open science, which Frontier is literally built on, does that
inherently demand global collaboration, even with strategic rivals, to ensure
the safest and fastest progress for all of humanity.
Speaker 1: Just think about the difference between the secrecy of the
X ten reactor and the openness of Frontier. Which path
do you think truly secures our future? Let us know
what you think in the comments. We'll catch you next
time on thrilling Threads.