Speaker 1: Welcome to Bedtime Astronomy. Explore the wonders of the cosmos
Speaker 1: with our soothing Bedtime Astronomie podcast. Each episode offers a
Speaker 1: gentle journey through the stars, planets, and beyond, perfect for
Speaker 1: unwinding after a long day. Let's travel through the mysteries
Speaker 1: of the universe as you drift off into a peaceful
Speaker 1: slumber under the night sky.
Speaker 2: Okay, I want you to start by picturing something well,
Speaker 2: truly immense, the Sun. Our sources are telling us that
Speaker 2: the Sun, just doing its thing, pumps out more power
Speaker 2: than me. Get this, one hundred trillion times all the
Speaker 2: electricity humanity generates across the globe. I mean that number.
Speaker 2: It's not just big, it's almost impossible to really wrap
Speaker 2: your head around, right, Yeah, that scale of energy. And
Speaker 2: yet down here on Earth or a modern world, especially
Speaker 2: our push for bigger and bigger AI artificial intelligence, it's
Speaker 2: kind of hitting a ceiling, a real physical limit based
Speaker 2: on how much energy we can actually feed these things
Speaker 2: now we cool them. We're burning through massive amounts of
Speaker 2: power just to train and run the really big machine
Speaker 2: learning systems, and that demand is just going up and up.
Speaker 2: So what happens when a company like Google, I mean,
Speaker 2: a company that's all in on scaling AI, looks up
Speaker 2: and asks, well, what if the best place, maybe the
Speaker 2: only sustainable place to really scale this stuff isn't here.
Speaker 2: What if it's you know, up there in space, tap
Speaker 2: and right of that massive power source. Today we're doing
Speaker 2: a deep dive into a really bold idea, Google's project Suncatcher.
Speaker 2: We've got this fascinating, super detailed research paper that outlines
Speaker 2: their technical plan for actually moving entire data centers, huge
Speaker 2: stacks of computers running their own custom chips in the
Speaker 2: low Earth orbit. It sounds like something straight out of
Speaker 2: sci fi, honestly, but when you look at the engineering details,
Speaker 2: they're surprisingly well grounded in tech. It's either here now
Speaker 2: or very close.
Speaker 3: Yeah, And that grounding, that sort of technical seriousness, is
Speaker 3: what makes this more than just a cool thought experiment.
Speaker 3: It's real engineering because when we talk about AI right now,
Speaker 3: we're basically talking about an energy crisis that's just around
Speaker 3: the corner. Training the biggest models today, they already use
Speaker 3: more power than small cities. So projects on Ketcher it's
Speaker 3: a serious engineering first attempt to tackle what's fast becoming
Speaker 3: a huge bottleneck for the whole tech industry. It's an
Speaker 3: infrastructure problem fundamentally, So for you listening in, we're going
Speaker 3: to try and get past that initial wow factor and
Speaker 3: really unpack the nuts and bolts of how Google actually
Speaker 3: thinks they can make this work. We've got three main
Speaker 3: areas we're going to break down today. First, the really huge,
Speaker 3: undeniable energy advantage you get in orbit and the specific
Speaker 3: orbital mechanics they need. Second, the let's call it extreme
Speaker 3: engineering that's required for the communication and for keeping a
Speaker 3: whole data center flying together in a tight formation. And finally,
Speaker 3: something pretty surprising how well the hardware might actually hold up,
Speaker 3: and the razor thin economics that really decide if this
Speaker 3: whole thing makes sense in the next say decade or two.
Speaker 2: Okay, let's start right there with energy, because that's the
Speaker 2: whole point, isn't it. That's the core problem projects suncatchers
Speaker 2: aiming at. Like you said, the power demands for large
Speaker 2: scale machine learning are just enormous, So why mess around
Speaker 2: building ever bigger solar farms down here where you've got clouds, nighttime,
Speaker 2: the atmosphere blocking sunlight land issues. Yeah, when you could
Speaker 2: just put the computers right next door to the power
Speaker 2: source itself.
Speaker 3: It really boils down to efficiency, doesn't it. If energy
Speaker 3: is your biggest cost, you go where the energy is
Speaker 3: cheapest and most abundant, and the suncatch paper or their
Speaker 3: analysis it suggests that solar panels in orbit could be
Speaker 3: up to eight times more productive than the best ones
Speaker 3: we have down here on Earth. Wow, that eight x factor,
Speaker 3: that's the fundamental thing driving this whole project. It just
Speaker 3: completely changes the math before you even start talking about
Speaker 3: chips or rockets or anything else.
Speaker 2: Eight times more productive, that's a staggering difference. Why why
Speaker 2: such a huge gap? Is it just because there's no
Speaker 2: atmosphere up there?
Speaker 3: That's a big slice of it. Yeah, our atmosphere, you know,
Speaker 3: great for breathing, but it absorbs or reflects something like
Speaker 3: thirty percent of the Sun's energy right off the bat
Speaker 3: and that's on a clear day, not counting clouds or
Speaker 3: dust or anything. Up in LEO low Earth orbit, you're
Speaker 3: getting the raw deal, full spectrum, no filtering, pure sunlight.
Speaker 3: But there's actually another factor that's maybe even more powerful,
Speaker 3: especially when you think about cost, and that's the idea
Speaker 3: of continuous collection. See down here, even in the sunniest
Speaker 3: desert on Earth, you lose half your operating time just
Speaker 3: because of night plus you've got seasons, bad weather. But
Speaker 3: in orbit, especially the orbit they're planning, these satellites are
Speaker 3: in almost constant sunlight.
Speaker 2: Almost constant sunlight. Okay, And if you get rid of
Speaker 2: the night cycle, what big engineering headache just.
Speaker 3: Vanishes storage batteries. It basically eliminates the biggest, heaviest, and
Speaker 3: frankly most expensive part of large scale solar power on Earth,
Speaker 3: which is storing enough energy to last through the night.
Speaker 3: If you're generating power pretty much twenty four to seven,
Speaker 3: you just don't need those massive, heavy, costly battery banks
Speaker 3: that are absolutely vital for any serious solar project down here.
Speaker 2: Ah right, that makes sense.
Speaker 3: Heavy, incredibly heavy. Think about the mass budget for launch.
Speaker 3: Lithium ion batteries add a lot of weight. To power
Speaker 3: a data center on Earth through the night, you'd need
Speaker 3: enormous battery arrays adds mass, adds volume, adds cost in space.
Speaker 3: If you need far less battery mass, your satellite is lighter,
Speaker 3: and that directly lowers the complexity and crucially the cost
Speaker 3: to launch the whole thing, So that AIGHTX efficiency isn't
Speaker 3: just about getting more power out. It's also about needing
Speaker 3: left heavy stuff like batteries sent up there in the
Speaker 3: first place. It's minimizing that dead weight.
Speaker 2: Okay, so Project Suncatcher isn't just about grabbing more sunlight.
Speaker 2: It's using a really specific orbital trick to get that
Speaker 2: continuous power. So let's talk about what this thing actually
Speaker 2: looks like. What's the architecture. Is it one giant space station?
Speaker 3: No, not monolithic at all. The concept is actually a
Speaker 3: distributed constellation. Think lots and lots of separate satellites. Each
Speaker 3: one would have its own solar panels, its own processors,
Speaker 3: specifically Google's own ships, their TPUs, and they'd all be
Speaker 3: connected together with super fast laser links, optical links. And
Speaker 3: the orbit they chose that's really the key piece of
Speaker 3: engineering here. They've zero in on a sun synchronous.
Speaker 2: Low Earth orbit l e O Sun synchronous ALIO.
Speaker 3: Yeah, sometimes called SSO, and choosing that specific orbit. It's
Speaker 3: not random at all. It's this really clever bit of
Speaker 3: orbital mechanics, a kind of geometric trick designed purely to
Speaker 3: keep the sunlight hitting those panels almost all the time.
Speaker 2: Okay, for those of us listening who hear Sun synchronous
Speaker 2: and maybe you just picture it following the Sun around.
Speaker 2: Can you break down the orbital magic there? What makes
Speaker 2: SSO so good for power?
Speaker 3: Sure? So, an SSO is an orbit that goes almost
Speaker 3: over the poles, a near polar orbit, and the magic,
Speaker 3: as you put it, is how the plane of that
Speaker 3: orbit rotates. The orbit itself actually precesses. It sort of
Speaker 3: turns around the Earth at the exact same speed that
Speaker 3: the Earth goes around the Sun, which is about one
Speaker 3: degree per day. Okay, So the geometry works out such
Speaker 3: that the satellite always crosses the equator at the same
Speaker 3: local solar time every day.
Speaker 2: Ah Okay, so the Sun is always hitting it from
Speaker 2: roughly the same direction relative to.
Speaker 3: Its pass exactly. The satellite keeps a near constant angle
Speaker 3: relative to the Sun, so the solar panels can be
Speaker 3: oriented to be almost perfectly perpendicular to the sunlight for
Speaker 3: most of the orbit, maximizing collection. And the big payoff
Speaker 3: is that the satellite hardly ever goes into Earth's shadow.
Speaker 3: If it does, the eclipse is super short, maybe just
Speaker 3: a few minutes. Compare that to a typical l EO satellite,
Speaker 3: which might spend thirty or forty minutes in darkness every
Speaker 3: single orbit difference, huge difference. This specific orbit choice guarantees
Speaker 3: that almost constant sunlight, which then lets them drastically minimize
Speaker 3: how many batteries they need onboard. It's really the sweet
Speaker 3: spot maximum sun exposure for power, but still in low orbit,
Speaker 3: which helps keep the communication latency back down to Earth
Speaker 3: somewhat reasonable.
Speaker 2: Okay, that perfect energy supply, that constant sunlight. It leads
Speaker 2: us straight into the second, really big challenge, maybe the
Speaker 2: hardest one. Taking a static building some data center on
Speaker 2: the ground and turning it into a swarm of individual
Speaker 2: satellites flying together information that demands coordination on a scale
Speaker 2: that just sounds well, incredibly difficult.
Speaker 3: Yeah, and the coordination isn't just a nice to have,
Speaker 3: It's an absolute requirement, and it's driven entirely by the
Speaker 3: need for fast data links between the satellites, getting that
Speaker 3: data center level of performance the kind you need for
Speaker 3: these giant AI models. It absolutely depends on the satellites
Speaker 3: flying and what the paper calls extremely tight formation.
Speaker 2: Extremely tight Why why so close as it just so
Speaker 2: the lasers don't miss each other.
Speaker 3: That's definitely part of it. The pointing accuracy but the
Speaker 3: main reason comes back to the data link speed and
Speaker 3: the latency. We'll get more into the links themselves in
Speaker 3: a bit, but think about how a huge AI model works.
Speaker 3: It's splitting up the job across potentially thousands of processors simultaneously.
Speaker 3: All those processors need to talk to each other, share results,
Speaker 3: coordinate almost instantly like.
Speaker 2: Components inside a single computer.
Speaker 3: Basically pretty much in a data center on Earth, those
Speaker 3: processors might be connected by a few feet of fiber
Speaker 3: optic cable, really short distances, giving you microsecond latency incredibly
Speaker 3: high bandwidth. To get anywhere close to that kind of
Speaker 3: low latency in space, you just can't have the satellites
Speaker 3: drifting far apart. The paper specifies they need to be
Speaker 3: separated by kilometers or less.
Speaker 2: A kilometer or less, okay, even a kilometer in space.
Speaker 2: When you're talking data links, that still sounds like a
Speaker 2: long way for data compared to inside a server rack.
Speaker 3: It is, it absolutely is, And you can't beat the
Speaker 3: speed of light.
Speaker 2: Right.
Speaker 3: Even though light travels faster in vacuum than in fiber,
Speaker 3: that kilometer distance still introduces a delay you don't have
Speaker 3: on Earth. So they have to design the whole system
Speaker 3: the network protocols, the way tasks are distributed. Specifically to
Speaker 3: handle these slightly longer latencies, The whole constellation has to
Speaker 3: function like one single massive coordinated computer cluster, even though
Speaker 3: it's physically spread out over potentially you know, several miles.
Speaker 2: And the altitude they're aiming for around six hundred fifty kilometers.
Speaker 2: That adds another complication, doesn't it. It's LAO, sure, but
Speaker 2: it's not that high. There's still some atmosphere, some drag.
Speaker 3: Precisely, this isn't way out in geo geostationary orbit, where
Speaker 3: drab is basically zero down at six hundred and fifty kilometers,
Speaker 3: Especially when you're trying to keep potentially hundreds of these
Speaker 3: things packed so closely together, maybe hundreds of meters apart
Speaker 3: or less. Even tiny forces become a.
Speaker 2: Huge problem, like what kind of forces.
Speaker 3: Well, the residual atmospheric molecules, for one, Even though the
Speaker 3: air is incredibly thin up there, it's not a perfect vacuum.
Speaker 3: Hit a slightly denser patch, and it creates drag. If
Speaker 3: that drag affects one satellite's big solar panel slightly differently
Speaker 3: than its neighbors.
Speaker 2: It could nudge them out of alignment almost immediately and
Speaker 2: break those laser.
Speaker 3: Lis exactly, break the links, and the whole cluster stops
Speaker 3: working as a single unit. Plus you've got subtle things
Speaker 3: like the fact that Earth's gravity isn't perfectly uniform. All
Speaker 3: these tiny perturbations add up when you need such precise
Speaker 3: relative positioning.
Speaker 2: So if the forces are tiny but complex and always changing,
Speaker 2: how did Google figure out if they could actually solve this,
Speaker 2: this problem of keeping a distributed data center flying in
Speaker 2: formation seems almost impossible.
Speaker 3: Well, they didn't just guess. This is where the serious
Speaker 3: engineering comes in again. They built some really sophisticated physics
Speaker 3: simulations to model it. They wanted to analyze the stability
Speaker 3: of these tight formations over the long haul, over the
Speaker 3: whole mission lifetime.
Speaker 2: What did the simulations look at?
Speaker 3: Specifically, they modeled two main threats. First, those tiny irregular
Speaker 3: gravitational tugs from Earth not being a perfect sphere, what
Speaker 3: they're called the non gravitational field effects. And second, maybe
Speaker 3: more importantly in Lo, that atmospheric drag, which, like we said,
Speaker 3: is small at six hundred and fifty kilometers, but it's
Speaker 3: there and it changes depending on things like solar activity,
Speaker 3: puffing up the atmosphere. Even tiny differences in drag between
Speaker 3: adjacent satellites over time could cause them to drift apart
Speaker 3: significantly if you don't correct for it.
Speaker 2: Okay, that makes sense. You'd think hitting a slightly denser
Speaker 2: bit of air would slow one satellite down relative to
Speaker 2: its neighbor. Wouldn't that mean you need constant, powerful thruster
Speaker 2: burns to keep nudging them back into place. That sounds
Speaker 2: as a lot of fuel.
Speaker 3: You'd think so, right, But the conclusion from their models
Speaker 3: was actually surprisingly positive, which is good news for the
Speaker 3: project's lifespan. The simulations indicated that they should only need
Speaker 3: modest station keeping maneuvers to keep the formation stable over time.
Speaker 2: Modest that's the keyword there.
Speaker 3: It really is, because if they needed constant high thrust
Speaker 3: chemical rockets firing, they'd burn through propellant incredibly fast. That
Speaker 3: would limit the mission life drastically, and the whole economic
Speaker 3: argument kind of falls apart.
Speaker 2: So modest maneuvers probably means they're thinking about using things
Speaker 2: like electric propulsion, ion drives, hall thrusters, stuff that SIPs
Speaker 2: fuel but provides tiny pushes over long periods.
Speaker 3: That's almost certainly the implication Yeah, low thrust, high efficiency
Speaker 3: propulsion is perfect for this kind of longeration fine adjustment job.
Speaker 3: They can provide continue uk US really small corrections for
Speaker 3: years without needing massive fuel tanks, which means the mass
Speaker 3: needed for station keeping stays manageable within the overall satellite budget,
Speaker 3: and that helps keep the launch cost down. It all connects.
Speaker 3: The source material actually mentions NASA's Stereo Observatory spacecraft as
Speaker 3: a kind of parallel. Those probes needed really precise orbital
Speaker 3: control at relatively low altitudes to maintain their view of
Speaker 3: the Sun. The fact that Google's modeling suggests only modest
Speaker 3: maneuvers are needed implies that while the formation is tight,
Speaker 3: the natural orbital dynamics aren't totally fighting them. They can
Speaker 3: use these efficient, low thrust systems to nudge things back
Speaker 3: into place. It means that huge energy advantage they get
Speaker 3: from the sun synchronous orbit isn't immediately canceled out by
Speaker 3: needing tons of fuel just to hold the constellation together.
Speaker 2: Okay, all right, So we've got the massive power source,
Speaker 2: sorted things of the orbit, and we've got a plausible,
Speaker 2: simulation backed path to keeping the satellites flying to gather
Speaker 2: in formation using efficient thrusters. Now the third huge piece
Speaker 2: communication because if you can't shift data between all those
Speaker 2: processes at blinding speed was really low latency, then you
Speaker 2: don't have a data center. You just have a bunch
Speaker 2: of well solar powered computers sloating near each other. Not
Speaker 2: useful for big AI.
Speaker 3: Yeah, this communication challenge, it's truly the make or break
Speaker 3: piece for Suncatcher. We talked about AI workloads needing high
Speaker 3: bandwidth and low latency because the tasks get split up
Speaker 3: across maybe thousands of processors. If these connections between the
Speaker 3: processors are slow, the whole calculation grinds to a halt.
Speaker 3: It doesn't matter how fast the individual chips are. The
Speaker 3: system runs at the speed of its slowest link.
Speaker 2: Right.
Speaker 3: So, to really perform like a data center on Earth
Speaker 3: where data zips around on fiber optic cables at tens,
Speaker 3: maybe hundreds of gigabits per second, these links in space
Speaker 3: have to hit similar numbers across that kilometer or so
Speaker 3: gap we talked about, and Google set the bar incredibly
Speaker 3: high here. The goal they state is links supporting tens
Speaker 3: of terabits per second between satellite.
Speaker 2: Tens of terribus per seconds that's astronomical way beyond current
Speaker 2: inner satellite links, isn't it.
Speaker 3: Oh yeah, orders of magnitude faster. So how do you
Speaker 3: possibly achieve that kind of speed across kilometers of empty space,
Speaker 3: and crucially without using huge power hungry radio antennas. The
Speaker 3: answer is lasers. They're relying entirely on laser based optical communication.
Speaker 3: That's the key technology here.
Speaker 2: Lasers. Okay, why lasers instead of radio?
Speaker 3: Well, unlike radio waves which tend to spread out over
Speaker 3: distance and need a lot of power to keep the
Speaker 3: signal strong, lasers can focus light into an incredibly tight,
Speaker 3: narrow beam think laser pointer versus a floodlight. That tight
Speaker 3: focus means much less power gets wasted and you can
Speaker 3: pack way more information, much higher throughput into that beam.
Speaker 2: We've seen demos of this kind of thing before, right,
Speaker 2: leaser cons in space.
Speaker 1: Yeah.
Speaker 3: Absolutely. The sources mention the opal US experiment on the
Speaker 3: International Space Station, for example, optical payload for lasercom science
Speaker 3: that proved you could beam high bandwidth data using less
Speaker 3: pretty effectively. But the challenge here is taking that proof
Speaker 3: of concept and scaling it up massively, like by a
Speaker 3: factor of ten or twenty maybe more to get to
Speaker 3: those tens of terrabits.
Speaker 2: Okay, so the basic tech exists, but going from say
Speaker 2: gigabits or maybe single terabt up to tens of terrabits,
Speaker 2: that's a giant leap. How do they plan to squeeze
Speaker 2: so much more data down the same laser plate.
Speaker 3: They're planning to use some really advanced multiplexing techniques, basically
Speaker 3: finding clever ways to pack more separate data channels into
Speaker 3: the same physical path. The paper details two main methods working.
Speaker 2: Together multiplexing like splitting the beam sort of.
Speaker 3: The first is called dense wavelength division multiplexing or DWDM.
Speaker 3: This is already standard practice in long haul fiber optics
Speaker 3: on Earth. Imagine the laser beam is like a single highway.
Speaker 3: DWDM is like painting say thirty or forty different color
Speaker 3: lanes onto that same highway. Each color, each specific wavelength
Speaker 3: of light carries its own independent stream of data.
Speaker 2: Ah. Okay, so multiple data streams riding on different colors
Speaker 2: of light within the same beam. That multiplies the capacity
Speaker 2: right there exactly.
Speaker 3: It leverages the spectrum really efficiently. But then they add
Speaker 3: a second layer on top of that.
Speaker 2: Okay, what's the second layer.
Speaker 3: That's spatial multiplexing technology. So if d do UDM gives
Speaker 3: you multiple lanes on one highway, spatial multiplexing is like
Speaker 3: building several parallel highways right next to each other. It
Speaker 3: means sending multiple separate laser beams between the two satellites simultaneously,
Speaker 3: all aimed very precisely at an array of sensitive receivers
Speaker 3: on the other end.
Speaker 2: Wow, okay, so multiple beams and each beam is carrying
Speaker 2: multiple colors or wavelengths of data precisely.
Speaker 3: You combine DDM and spatial multiplexing multiple colors times multiple beams.
Speaker 3: That's how they aim to multiply the data rate so
Speaker 3: dramatically and hit that collective target of tens of terabits
Speaker 3: per second.
Speaker 2: That sounds incredibly complex keeping all those beams and colors
Speaker 2: aligned across a kilometer of space. Is this still just
Speaker 2: theory or have they actually tested any of.
Speaker 3: This is important. They have done some concrete validation, at
Speaker 3: least on a lab bench, which is crucial right to
Speaker 3: show the physics works. The research teams set up a
Speaker 3: demonstration combining these approaches, and they successfully transmitted data at
Speaker 3: a total rate of one point six terabits per second.
Speaker 2: Okay, one point six tvps. It's still a long way
Speaker 2: from tens, but it's well, it's not zero. It shows
Speaker 2: the combined technique actually functions exactly.
Speaker 3: It proves the principle. And what's really interesting here is
Speaker 3: how this lab success ties straight back to that need
Speaker 3: for tight formation flying we discussed earlier keeping the satellites
Speaker 3: separated by kilometers or less. That tight spacing it isn't
Speaker 3: just for orbital stability. It's absolutely essential for making sure
Speaker 3: these complex laser links can actually be scaled up and
Speaker 3: work reliably. The closer the satellites are, the easier it
Speaker 3: is to maintain that pinpoint accuracy needed for multiple laser
Speaker 3: beams carrying multiple wavelengths to hit tiny receivers without the
Speaker 3: signal degrading or getting lost.
Speaker 2: Ah I see. So maintaining that close distance is basically
Speaker 2: what allows the fancy multiplexing tricks to work at their
Speaker 2: full potential. It protects the signal quality for those super
Speaker 2: high data rates. The whole system is interconnected.
Speaker 3: Totally interconnected. The formation flying enables the high speed links,
Speaker 3: and the need for high speed links dictates the type formation.
Speaker 3: One can't work without the other. If the formation drifts
Speaker 3: too far apart, the beams misalign, the data rate crashes,
Speaker 3: and your space data center just isn't a data center anymore.
Speaker 3: It's just separate computers again.
Speaker 2: Okay, let's switch gears then to the computers themselves, the processors.
Speaker 2: You can have all the power in the universe, perfect formation,
Speaker 2: amazing laser links. But if the actual chips doing the work,
Speaker 2: the TPUs, get fried by space radiation on day one,
Speaker 2: then the whole project is obviously useless. And the usual thinking,
Speaker 2: right is that regular commercial computer chifts just can't handle
Speaker 2: the radiation environment in space. You normally need special rad
Speaker 2: hardened components, which are expensive and usually slower.
Speaker 3: That has definitely been the big hurdle for using standard
Speaker 3: off the shelf hardware in space for a long time.
Speaker 3: But what's really striking in the Sunketcher page is what
Speaker 3: they found when they tested Googles on chips. It suggests
Speaker 3: maybe that old constraint isn't quite as rigid as we thought,
Speaker 3: at least for their specific architecture. They took their Trillium
Speaker 3: V six E Cloud TPU, that's their custom chip designed
Speaker 3: specifically for AI and machine learning, and they blasted it
Speaker 3: with radiation to see how it held up, and the
Speaker 3: results they're actually much better than even the researchers themselves
Speaker 3: seemed to expect better.
Speaker 2: In what way, how do you measure holding up against radiation?
Speaker 2: We're talking about accumulated damage over time, right, Yeah, and
Speaker 2: also maybe sudden failures from like a direct hit bioparticle.
Speaker 3: Yeah, both are concerns. The study focused heavily on the
Speaker 3: cumulative dose tolerance, which is measured in a unit called rads.
Speaker 3: It's basically how much radiation energy gets absorbed over time.
Speaker 3: So for the planned five year mission in that specific
Speaker 3: sun synchronous l EO, they calculated the expected total radiation
Speaker 3: dose that chips would receive even with some shielding. The
Speaker 3: number they planned for their baseline was seven hundred and
Speaker 3: fifty rads.
Speaker 2: Seven hundred and fifty rads over five years.
Speaker 3: Now here's the key finding. The TPU chips themselves, the
Speaker 3: core processors could actually withstand a cumulative dose almost three
Speaker 3: times higher than that. They kept working properly well past
Speaker 3: seven hundred and fifty rads, significantly past it before they
Speaker 3: started showing any major problem.
Speaker 2: Wow, three times the expected dose. That's a huge margin.
Speaker 2: Does that mean that maybe the way modern chips are
Speaker 2: built really small and dense, actually helps protect them somehow
Speaker 2: more than older chips.
Speaker 3: That seems to be exactly the implication. Yeah, modern ship
Speaker 3: manufacturing with incredibly tiny transistors packed cluickally together smaller nodes,
Speaker 3: it seems they might be inherently less likely to be
Speaker 3: damaged by certain kinds of radiation, just less physical target
Speaker 3: area for the radiation to hit.
Speaker 2: Perhaps.
Speaker 3: If this holds true, it's a massive deal Economically. It
Speaker 3: means they might be able to use largely commercial grade processors,
Speaker 3: which are produced in huge volumes and are relatively cheap,
Speaker 3: instead of relying solely on expensive, low volume, specially hardened
Speaker 3: space components that could drastically lower the cost per satellite.
Speaker 2: Really, not every part of the system is equally tough
Speaker 2: in a complex chip, Aren't things like the memory usually
Speaker 2: more delicate.
Speaker 3: That's a very good point, and yes, the testing showed
Speaker 3: exactly that. While the main processing units were surprisingly robust
Speaker 3: against the total dose, the high bandwidth memory or HBM
Speaker 3: systems turned out to be the most sensitive part HBM.
Speaker 2: That's the really fast memory right next to the process,
Speaker 2: or crucial for feeding it data quickly for AI tasks.
Speaker 3: Yeah, exactly. It's absolutely vital. If the HBM fails or
Speaker 3: gets corrupted too often, the whole AI calculation grinds to
Speaker 3: a halt, no matter how tough the processor is.
Speaker 2: So, how did the HBM fare in the tests? What
Speaker 2: was its breaking point?
Speaker 3: Well, even the weak link, the HBM did surprisingly well.
Speaker 3: It only started showing significant issues related to the cumulative
Speaker 3: radiation dose after it had absorbed about two killer ads.
Speaker 2: Two killer ads. That's two thousand rats.
Speaker 3: Yep, two thousand rads. And remember the expected dose for
Speaker 3: the entire five year emission with shielding was only seven
Speaker 3: hundred and fifty rads.
Speaker 2: So the most sensitive part lasted well over double the
Speaker 2: expected mission dose before failing.
Speaker 3: Correct more than double, which strongly suggests that fundamentally, the
Speaker 3: high performance hardware Google is using is basically tough enough
Speaker 3: for that ILIO environment, assuming they designed the shielding correctly.
Speaker 3: This finding really tackles what many space engineers would probably
Speaker 3: point to as the biggest technical show stopper and cost
Speaker 3: driver for putting commercial style data centers in orbit. It
Speaker 3: suggests the hardware might actually survive.
Speaker 2: Okay, this whole thing, Project Suncatcher, it's just an amazing
Speaker 2: combination of well energy physics, clever orbits, laser engineering, surprisingly
Speaker 2: tough hardware. But like we said at the start, Google's
Speaker 2: a business. This is a gigantic infrastructure play. It only
Speaker 2: actually happens if it makes financial sense. Right, When does
Speaker 2: putting computers in space actually become cheaper than just building
Speaker 2: another data center down here? What's the bottom line?
Speaker 3: Yeah, that's the multi billion dollar question, isn't it? And
Speaker 3: the paper is refreshingly honest about it. The entire financial
Speaker 3: viable ability, the whole economic case for Suncatcher, it depends
Speaker 3: heavily on launch costs continuing their decline. If the cost
Speaker 3: per kilogram to get stuff out of Earth gravity well
Speaker 3: doesn't drop dramatically, then this whole project, no matter how
Speaker 3: cool the tech is, just stays on the drawing board.
Speaker 3: It's completely unaffordable. Right.
Speaker 2: Launch cost is everything in space.
Speaker 3: It's the biggest upfront cost by far. You have to
Speaker 3: lift all that hardware, the satellites, the solar panels, the lasers,
Speaker 3: the processors, the fuel for station keeping all the way
Speaker 3: into orbit.
Speaker 2: Just to give people a sense of scale, what does
Speaker 2: it roughly cost today to launch a kilogram to l
Speaker 2: EO using current.
Speaker 3: Rockets ballpark figures. Even with modern reasonable rockets coming online,
Speaker 3: you're probably still looking somewhere between say, fifteen hundred dollars
Speaker 3: and maybe three thousand dollars per kilogram on the commercial market,
Speaker 3: maybe a bit less for very large customers. Now that's
Speaker 3: way way cheaper than the Space Shuttle air obviously, but
Speaker 3: launching the tens, maybe hundreds of tons of hardware needed
Speaker 3: for a constellation like Suncatcher at those prices, the upfront
Speaker 3: cost is just astronomical, completely non viable.
Speaker 2: So what's the magic number? Then? What did Google's analysis
Speaker 2: say launch costs need to fall to for this whole
Speaker 2: thing to start looking economical compared to the energy.
Speaker 3: Savings Their analysis pinpoints are really critical target price launch
Speaker 3: costs need to get below two hundred dollars per.
Speaker 2: Kilogram two hundred dollars akilo.
Speaker 3: Wow, yeah, two hundred dollars per kilogram. That's the threshold where,
Speaker 3: according to their map, the enormous cost of building, launching,
Speaker 3: and operating this space infrastructure starts to become economically justifiable
Speaker 3: when weighed against the huge continuous savings from getting free
Speaker 3: constant eight x more efficient solar power.
Speaker 2: Two hundred dollars akilo is that's incredibly ambitious. That's not
Speaker 2: just incrementally cheaper rockets. That basically requires the full dream
Speaker 2: of super heavy, rapidly reusable launch vehicles to become reality,
Speaker 2: right like SpaceX's Starship working at full cadence or similar systems.
Speaker 3: Absolutely, they are essentially making a long term strategic bet
Speaker 3: on that specific future for the launch industry, a future
Speaker 3: defined by full and rapid reusability and a very high
Speaker 3: flight rate. Their timeline reflects this. They project that this
Speaker 3: kind of price point sub two hundred kilograms might become
Speaker 3: achievable sometime in the mid twenty thirties, assuming you know,
Speaker 3: continued progress and success in developing these next generation launch system.
Speaker 2: The mid twenty thirties. Okay, so this isn't something they
Speaker 2: expect to build next year. It's a decade plus strategic vision.
Speaker 3: Definitely, it requires the whole commercial space ecosystem, especially launch,
Speaker 3: to mature significantly. And that two hundred dollar kilogram target
Speaker 3: probably also implicitly relies on the fact that because of
Speaker 3: the ad X energy efficiency and constant sunlight, the satellites
Speaker 3: themselves can be lighter, smaller solar arrays, way fewer batteries
Speaker 3: than if they had to launch the equivalent power generation
Speaker 3: and storage capacity needed on Earth. So the total mass
Speaker 3: they need to launch is less to begin with.
Speaker 2: Okay, so let's assume they hit that target. Let's say
Speaker 2: launch costs do get down to two hundred dollars per
Speaker 2: kilogram by the mid twenty thirties. What's the final economic verdict? Then?
Speaker 2: How does space compare to Earth?
Speaker 3: This This is really the punchline that ties the whole
Speaker 3: vision together. At that target price point, the analysis concludes
Speaker 3: that launching and operating a space based data center becomes
Speaker 3: roughly comparable in cost to just the energy expenses of
Speaker 3: running an equivalent AI facility on Earth.
Speaker 2: We say that again, the total cost of building and
Speaker 2: launching the space system equals just the electricity bill for
Speaker 2: the Earth based one.
Speaker 3: Roughly comparable. Yeah, think about how huge that is. The
Speaker 3: massive capital cost of designing, building, launching, and maintaining this
Speaker 3: incredibly complex space constellation becomes similar in magnitude to just
Speaker 3: paying the ongoing power bill for a state of the
Speaker 3: art AI data center down here.
Speaker 2: So basically the biggest operational cost on Earth, that relentless
Speaker 2: massive electricity drogic gets.
Speaker 3: Utralized, pretty much neutralized yeah, it completely flips the usual
Speaker 3: cost calculation down here. Energy is the huge ongoing operational
Speaker 3: expense that kills you some Catcher frames. The big upfront
Speaker 3: launch cost is the main hurdle. But once you clear
Speaker 3: that hurdle, assuming cost drop enough, the free can continuous
Speaker 3: energy from the Sun provides this massive long term economic advantage.
Speaker 3: It offsets what would have been your biggest terrestrial operating cost. Okay,
Speaker 3: let's try and quickly recap the main pillars of what
Speaker 3: we've dug into here with projects on Catcher, we're looking
Speaker 3: at this really radical but technically detailed plan to essentially
Speaker 3: cut the cord between future AI growth and the limits
Speaker 3: of Earth's energy grid. The technical plan is super specific.
Speaker 3: We've got that huge energy advantage, solar panels maybe eight
Speaker 3: times more effective, and that carefully chosen sun synchronous LAO.
Speaker 3: We've talked about how they think they can get data
Speaker 3: center speeds between satellites using lasers with fancy techniques like
Speaker 3: DWDM and spatial multiplexing, but that relies heavily on keeping
Speaker 3: the satellites in that really tight formation less than a
Speaker 3: kilometer apart, using those modest efficient station keeping thrusters and
Speaker 3: then there was the surprising finding about the hardware. Google's
Speaker 3: own TPUs seemed tough enough to handle the elo radiation environment,
Speaker 3: potentially lasting almost three times the expected dose for a
Speaker 3: five year mission. Even the more sensitive memory lasted twice
Speaker 3: aid as long as needed.
Speaker 2: Right underpinning absolutely everything is the economics. It all hinges
Speaker 2: on launch costs dropping dramatically below that two hundred dollars
Speaker 2: per kilogram mark. Google thinks that's possible by the mid
Speaker 2: twenty thirties, and if they hit that number, the whole
Speaker 2: system starts to look financially competitive, purely based on saving
Speaker 2: the massive energy costs heeding cur on Earth. So, stepping back,
Speaker 2: what does this all really mean in the bigger picture
Speaker 2: of technology of infrastructure? This isn't just putting servers somewhere
Speaker 2: else slightly inconvenient. It feels like a fundamental shift. If
Speaker 2: you can actually decouple massive computing power from the physical
Speaker 2: limits of our terrestrial power grids, which right now is
Speaker 2: maybe the single biggest thing holding back AI scaling, then
Speaker 2: you're not just getting a bit more processing power. You're
Speaker 2: potentially unlocking a whole new scale of AI development, aren't you.
Speaker 2: It's about creating a tech base that isn't tied down
Speaker 2: by how many power plants we can build or where
Speaker 2: we can build them, or the politics around energy.
Speaker 3: That really leads to the final big question. Doesn't it
Speaker 3: something for you, the listener, to really chew on after
Speaker 3: hearing all this, If the AI models we have today,
Speaker 3: which are still relatively limited in the grand scheme of things,
Speaker 3: if they are already straining power grids and consuming frankly
Speaker 3: enormous amounts of energy, what scale of machine learning? What
Speaker 3: kinds of problems could we tackle? What level of intelligence
Speaker 3: could we potentially build if the energy source was effectively unlimited,
Speaker 3: tapping into something that's literally one hundred trillion times greater
Speaker 3: than our current global capacity, and the only real bottleneck
Speaker 3: left becomes the cost of getting the hardware up there.
Speaker 3: It's the kind of future scale project Suncatcher is aiming for.
Speaker 3: That's the potential transformation they're trying to engineers
Speaker 2: Us