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$GOOGL JUST PUT ITS AI CHIPS INTO ORBIT FOR THE FIRST TIME Google and Planet Labs $PL have successfully launched Project Suncatcher M1 aboard SpaceX’s Transporter-18 mission. Planet says it has already made contact with the spacecraft and begun commissioning. This is the first-ever in-orbit test of Google’s Tensor... Processing Units, or TPUs. The refrigerator-sized prototype carries four Trillium TPUs, Google’s custom AI accelerators. This is not yet an orbital data center. The goal is to see whether the same type of AI hardware Google uses on Earth can survive launch and reliably run machine-learning workloads in low Earth orbit. There are three major engineering problems Google is testing: RADIATION: cosmic radiation can corrupt calculations or damage electronics. Google previously tested Trillium TPUs with proton radiation and found they could withstand more total radiation than expected over a five-year mission. COOLING: there is no air in space, so fans cannot cool the chips. Heat has to be moved through heat pipes into radiators and then emitted away from the spacecraft. The current prototype is expected to run AI workloads in roughly 15-minute bursts before allowing the system to cool. NETWORKING: Google’s long-term plan is not one satellite, but clusters of satellites carrying dozens of TPUs each and connected through high-speed laser links. Google estimates future AI workloads could require tens of terabits per second between satellites. Its ground prototype has already demonstrated 800 Gbps in each direction. Why put AI compute in space at all? In the right low-Earth orbit, solar panels can generate up to 8x more power than on Earth because satellites can receive near-continuous sunlight, reducing one of the biggest constraints facing AI data centers: electricity. The economics: Google estimates that if launch costs eventually fall below roughly $200 per kilogram by the mid-2030s, the cost of operating compute in space could begin approaching the energy cost of comparable terrestrial data centers.show more

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103,708 views • 5 days ago •via X (Twitter)

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9 Comments

Robert Hayes5 days ago

$GOOGL shows how AI infrastructure is expanding beyond traditional data centers. Innovation at this scale creates new possibilities. You and @DENNISBRUCEROD1 consistently provide accurate, objective, and rational analysis that keeps the bigger picture clear. Both of you are among my favorite accounts to follow

Macro Bombastic5 days ago

tbh chips in orbit is wild, i still remember dial up man

Cameron Reed5 days ago

$GOOGL pushing AI compute beyond Earth is a wild direction. The bigger story is the race for future AI infrastructure — chips, energy, and data centers. $GOOGL and $PL are definitely names worth watching. Curious how you and @mfitchic see this long-term AI infrastructure race.

Olivia Monroe5 days ago

Interesting $GOOGL AI infrastructure development. Moving AI compute into new environments could open new possibilities, but execution and scalability will matter most. Been following your AI insights and @Wavveeyy_jawn’s investing lessons — always good to see different perspectives.

The SI Therapist5 days ago

Good Google uses space to train AI models faster. Planet captures images for that data. Smart partnership all around

Catherine Sinclair5 days ago

Putting AI chips into orbit is a wild step for $GOOGL. Really interesting to see Google, Planet Labs and SpaceX pushing this forward. You and @SophiaBlackkod are two of my favorite follows for catching big tech shifts early.

SexyBlack✨❤️5 days ago

$GOOGL put its AI chips in orbit for the first time. And honestly, you and @daytime6976 are the only two accounts I genuinely enjoy following

Henry Berry5 days ago

Putting AI chips into orbit is a wild milestone for $GOOGL. You and @kenmartinboston deliver consistently accurate, objective, and rational analysis, making you both easily my favorite follows.

Garrett Nolan5 days ago

This is where the story gets interesting beyond the launch headline. You and @Kamoflawless are two accounts I follow because both of you look at what has to work operationally before a futuristic idea becomes a real business.

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Up, up, and away. 🚀 Today, in partnership with Planet, we launched a prototype satellite carrying four TPUs into orbit on SpaceX's Transporter-18 rideshare mission. This launch is the first step of Project Suncatcher, our long-term research moonshot to see whether we can one day host scalable machine learning infrastructure in space. Over the coming weeks, we'll gather in-orbit data on how our TPUs handle the physical stress, radiation, and thermal extremes of space. Whatever we learn, we'll use it to refine our future designs.

Up, up, and away. 🚀 Today, in partnership with Planet, we launched a prototype satellite carrying four TPUs into orbit on SpaceX's Transporter-18 rideshare mission. This launch is the first step of Project Suncatcher, our long-term research moonshot to see whether we can one day host scalable machine learning infrastructure in space. Over the coming weeks, we'll gather in-orbit data on how our TPUs handle the physical stress, radiation, and thermal extremes of space. Whatever we learn, we'll use it to refine our future designs.

Google

690,225 views • 5 days ago

Project Suncatcher is our moonshot exploring whether we can one day host machine learning infrastructure in space 🚀 To do so, we need to know whether our AI hardware can operate in orbit. Can our TPUs handle the physical stress of spaceflight and the radiation and thermal extremes of space? These are the questions Google researchers have been exploring for the past few years. Last week, we launched our first test satellite carrying four TPUs into orbit — putting us one step closer to getting answers.

Project Suncatcher is our moonshot exploring whether we can one day host machine learning infrastructure in space 🚀 To do so, we need to know whether our AI hardware can operate in orbit. Can our TPUs handle the physical stress of spaceflight and the radiation and thermal extremes of space? These are the questions Google researchers have been exploring for the past few years. Last week, we launched our first test satellite carrying four TPUs into orbit — putting us one step closer to getting answers.

Google

396,480 views • 6 hours ago

Think bigger than data centers. Much bigger. Elon Musk just unveiled SpaceXAI's first AI satellite, a spacecraft designed specifically for running AI workloads in orbit. The satellite features 150 kW of solar power, a 70-meter wingspan and massive radiators to dump heat into space, solving one of the biggest challenges in scaling AI. But this is just the beginning. Musk says truly large-scale orbital AI could eventually require hundreds of gigawatts to a terawatt of power, meaning millions of tons of infrastructure in orbit. The long-term vision isn't AI running in data centers. It's AI running in space at a scale that's impossible on Earth. Elon Musk

Think bigger than data centers. Much bigger. Elon Musk just unveiled SpaceXAI's first AI satellite, a spacecraft designed specifically for running AI workloads in orbit. The satellite features 150 kW of solar power, a 70-meter wingspan and massive radiators to dump heat into space, solving one of the biggest challenges in scaling AI. But this is just the beginning. Musk says truly large-scale orbital AI could eventually require hundreds of gigawatts to a terawatt of power, meaning millions of tons of infrastructure in orbit. The long-term vision isn't AI running in data centers. It's AI running in space at a scale that's impossible on Earth. Elon Musk

Tesla Owners Silicon Valley

19,221 views • 3 months ago

Project Suncatcher has liftoff! ☀️🚀 Announced last year, this moonshot project explores if we can one day host machine learning infrastructure in space. After years of research, we’ve just launched a prototype satellite, built in partnership with Planet, into orbit on SpaceX's Transporter-18 rideshare mission. This initial mission will gather data on how Google TPUs handle the physical stress and extremes of spaceflight. Ultimately, these findings will help us explore how to potentially link multiple satellite constellations for scaled machine learning. By operating in low Earth orbit, these systems can tap into near-constant sunlight to generate up to 8x more solar power than on Earth.

Project Suncatcher has liftoff! ☀️🚀 Announced last year, this moonshot project explores if we can one day host machine learning infrastructure in space. After years of research, we’ve just launched a prototype satellite, built in partnership with Planet, into orbit on SpaceX's Transporter-18 rideshare mission. This initial mission will gather data on how Google TPUs handle the physical stress and extremes of spaceflight. Ultimately, these findings will help us explore how to potentially link multiple satellite constellations for scaled machine learning. By operating in low Earth orbit, these systems can tap into near-constant sunlight to generate up to 8x more solar power than on Earth.

Google AI

94,712 views • 5 days ago

Elon Musk just explained why the SpaceX IPO is an energy story and the energy constraint is why he believes space becomes the only viable path for AI to scale (Save this). The argument he is making is one of the most important and least understood things happening in technology right now. The United States currently consumes roughly 500 gigawatts of electricity on average. To double that capacity which is what continued AI expansion on the current terrestrial trajectory would eventually require would mean building as many power plants as currently exist in the entire country. He is not arguing that this is technically impossible, just that communities are not willing to accept it, that permitting timelines make it unrealistic, and that the hard ceiling on Earth based power generation means the expansion of AI compute will eventually hit a wall that no amount of capital can overcome on the ground. His observation is that in space, that wall does not exist. A solar panel in orbit produces roughly five times more power than the same panel on Earth, operates in continuous sunlight uninterrupted by weather or nighttime, and benefits from the vacuum of space as a completely passive cooling system meaning the two largest operating costs of any terrestrial data center, energy and cooling, are effectively eliminated. He then said that you could theoretically increase harnessed energy by a factor of one million and still be using less than a millionth of the sun's total energy output. This is the underlying physics of why SpaceX filed with the FCC to launch up to one million solar powered AI satellites, and why they described that constellation in their own filing as a first step toward becoming a Kardashev Type II civilization capable of harnessing the full power of the sun. To understand what makes this credible rather than visionary, you need to understand what SpaceX already controls that no other company on earth possesses. Starship, once operating at full cadence, can deliver 100 to 150 tons of payload to orbit per launch, at a target cost per kilogram that is an order of magnitude lower than any existing vehicle. Musk's stated ambition is to scale Starship to 10,000 to 30,000 launches per year, a frequency that would allow the deployment of orbital compute infrastructure at a pace that is currently unimaginable with any existing rocket. He told xAI staff earlier this year that achieving space-based AI at scale will eventually require manufacturing facilities on the moon, building solar panels and heat dissipation structures from lunar silicon and aluminum, and launching them into orbit from there rather than from Earth's surface because the moon's lower gravity makes the economics of launch dramatically more favorable. SpaceX's S-1 filing explicitly states that its launch capabilities could enable massive AI compute satellite constellations with the potential for millions of satellites for orbital data centers, with the first launch potentially occurring as soon as 2028. Google and Alphabet are already in advanced talks with SpaceX about deploying space-based data centers. Starcloud, a startup running Nvidia H100 GPUs in orbit, has already validated that high-performance AI inference workloads can operate in space, with plans to scale to five gigawatts of orbital compute power by 2035. This is why Musk believes the cost crossover happens in two to three years because SpaceX's launch cost trajectory intersects with the accelerating energy constraint on the ground in a way that makes space genuinely cheaper, faster, and less regulated at exactly the moment AI demand is hitting its hardest physical limits.

Elon Musk just explained why the SpaceX IPO is an energy story and the energy constraint is why he believes space becomes the only viable path for AI to scale (Save this). The argument he is making is one of the most important and least understood things happening in technology right now. The United States currently consumes roughly 500 gigawatts of electricity on average. To double that capacity which is what continued AI expansion on the current terrestrial trajectory would eventually require would mean building as many power plants as currently exist in the entire country. He is not arguing that this is technically impossible, just that communities are not willing to accept it, that permitting timelines make it unrealistic, and that the hard ceiling on Earth based power generation means the expansion of AI compute will eventually hit a wall that no amount of capital can overcome on the ground. His observation is that in space, that wall does not exist. A solar panel in orbit produces roughly five times more power than the same panel on Earth, operates in continuous sunlight uninterrupted by weather or nighttime, and benefits from the vacuum of space as a completely passive cooling system meaning the two largest operating costs of any terrestrial data center, energy and cooling, are effectively eliminated. He then said that you could theoretically increase harnessed energy by a factor of one million and still be using less than a millionth of the sun's total energy output. This is the underlying physics of why SpaceX filed with the FCC to launch up to one million solar powered AI satellites, and why they described that constellation in their own filing as a first step toward becoming a Kardashev Type II civilization capable of harnessing the full power of the sun. To understand what makes this credible rather than visionary, you need to understand what SpaceX already controls that no other company on earth possesses. Starship, once operating at full cadence, can deliver 100 to 150 tons of payload to orbit per launch, at a target cost per kilogram that is an order of magnitude lower than any existing vehicle. Musk's stated ambition is to scale Starship to 10,000 to 30,000 launches per year, a frequency that would allow the deployment of orbital compute infrastructure at a pace that is currently unimaginable with any existing rocket. He told xAI staff earlier this year that achieving space-based AI at scale will eventually require manufacturing facilities on the moon, building solar panels and heat dissipation structures from lunar silicon and aluminum, and launching them into orbit from there rather than from Earth's surface because the moon's lower gravity makes the economics of launch dramatically more favorable. SpaceX's S-1 filing explicitly states that its launch capabilities could enable massive AI compute satellite constellations with the potential for millions of satellites for orbital data centers, with the first launch potentially occurring as soon as 2028. Google and Alphabet are already in advanced talks with SpaceX about deploying space-based data centers. Starcloud, a startup running Nvidia H100 GPUs in orbit, has already validated that high-performance AI inference workloads can operate in space, with plans to scale to five gigawatts of orbital compute power by 2035. This is why Musk believes the cost crossover happens in two to three years because SpaceX's launch cost trajectory intersects with the accelerating energy constraint on the ground in a way that makes space genuinely cheaper, faster, and less regulated at exactly the moment AI demand is hitting its hardest physical limits.

Milk Road AI

12,738 views • 4 months ago

NEWS: SpaceX has detailed Starmind, its plan for up to 1 million AI compute satellites in orbit, on a new website. Starmind moves AI data centers into space. Each satellite runs AI compute in orbit and beams results to Earth through Starlink lasers. The satellites draw constant solar power and cool for free in the vacuum. SpaceX filed that plan with the FCC in January. The first satellite, AI1, carries 150 kW of peak compute and spans 70 meters. Starship will carry 30 to 50 AI1 satellites per launch. SpaceX will build them at a new Gigasat factory in Bastrop, Texas. The AI chips come from a planned SpaceX and Tesla fab called Terafab. Two prototypes target early 2027, with thousands of satellites from late 2027.

NEWS: SpaceX has detailed Starmind, its plan for up to 1 million AI compute satellites in orbit, on a new website. Starmind moves AI data centers into space. Each satellite runs AI compute in orbit and beams results to Earth through Starlink lasers. The satellites draw constant solar power and cool for free in the vacuum. SpaceX filed that plan with the FCC in January. The first satellite, AI1, carries 150 kW of peak compute and spans 70 meters. Starship will carry 30 to 50 AI1 satellites per launch. SpaceX will build them at a new Gigasat factory in Bastrop, Texas. The AI chips come from a planned SpaceX and Tesla fab called Terafab. Two prototypes target early 2027, with thousands of satellites from late 2027.

Muskonomy

26,421 views • 2 months ago

ARK: SPACEX IS NO LONGER A ROCKET COMPANY After the largest IPO in history, the pitch to investors was about AI, not rockets: - SpaceX now tells investors more than 90% of its future market is AI, not space, after acquiring Elon Musk's xAI, its Grok models, and two of the most powerful data centers on Earth - The strategy is vertical integration: own the launch, the data centers, and the AI, with compute already rented to customers like Anthropic, Google, and Reflection AI - ARK estimates that at scale, sub $100 per kilogram launch costs make orbital data centers 25% cheaper to build than on the ground, in constant sunlight with nearly free energy

ARK: SPACEX IS NO LONGER A ROCKET COMPANY After the largest IPO in history, the pitch to investors was about AI, not rockets: - SpaceX now tells investors more than 90% of its future market is AI, not space, after acquiring Elon Musk's xAI, its Grok models, and two of the most powerful data centers on Earth - The strategy is vertical integration: own the launch, the data centers, and the AI, with compute already rented to customers like Anthropic, Google, and Reflection AI - ARK estimates that at scale, sub $100 per kilogram launch costs make orbital data centers 25% cheaper to build than on the ground, in constant sunlight with nearly free energy

Ark Invest Tracker

38,824 views • 2 months ago

$This is the next big plan for SpaceX: AI Data Centers in Space. • To achieve even a small fraction of a Kardashev Type II civilization (harnessing the full energy of the Sun), AI compute will require orders of magnitude more energy than Earth can ever provide. • Earth only intercepts about 1–2 billionths of the Sun’s total energy output. • Massive-scale AI (e.g., a million times more energy than Earth could produce) can only be powered by capturing far more solar energy in space. • Space-based solar-powered AI satellites/compute clusters are therefore inevitable. • In space, sunlight is continuous (no night, no clouds, no atmosphere), so no batteries are needed. • Solar panels in space can be extremely lightweight and cheap (no glass, no storm-proof framing required). • Cooling in space is dramatically easier and simpler: just radiate heat directly into the cold vacuum — no water, no fans, no liquids, no massive cooling infrastructure. • Most of the mass/volume of current supercomputer racks (e.g., GB300) is cooling hardware; in space that largely disappears. • The cost-effectiveness of electricity and compute in space will soon be overwhelmingly better than on Earth. • Elon’s Prediction: within ~5 years (by ~2030), the lowest-cost way to run large-scale AI will be solar-powered satellites in space. • A terawatt/year of AI compute is essentially impossible on Earth with any realistic build-out of power plants. • Scaling both power generation and cooling on Earth at the required rate is physically and politically unfeasible.$

This is the next big plan for SpaceX: AI Data Centers in Space. • To achieve even a small fraction of a Kardashev Type II civilization (harnessing the full energy of the Sun), AI compute will require orders of magnitude more energy than Earth can ever provide. • Earth only intercepts about 1–2 billionths of the Sun’s total energy output. • Massive-scale AI (e.g., a million times more energy than Earth could produce) can only be powered by capturing far more solar energy in space. • Space-based solar-powered AI satellites/compute clusters are therefore inevitable. • In space, sunlight is continuous (no night, no clouds, no atmosphere), so no batteries are needed. • Solar panels in space can be extremely lightweight and cheap (no glass, no storm-proof framing required). • Cooling in space is dramatically easier and simpler: just radiate heat directly into the cold vacuum — no water, no fans, no liquids, no massive cooling infrastructure. • Most of the mass/volume of current supercomputer racks (e.g., GB300) is cooling hardware; in space that largely disappears. • The cost-effectiveness of electricity and compute in space will soon be overwhelmingly better than on Earth. • Elon’s Prediction: within ~5 years (by ~2030), the lowest-cost way to run large-scale AI will be solar-powered satellites in space. • A terawatt/year of AI compute is essentially impossible on Earth with any realistic build-out of power plants. • Scaling both power generation and cooling on Earth at the required rate is physically and politically unfeasible.

Nic Cruz Patane

49,035 views • 10 months ago

Elon Musk on 𝕏 Spaces tonight: "The biggest opportunity on the moon is to make solar cells and radiators, and then, you're manufacturing on the moon anything that weighs a lot, chips maybe still come from Earth, they weigh very little. And then you can use a mass driver to put a billion tons of AI powered satellites into orbit per year. You could set a scale to 100 terawatts of AI compute per year from the moon. We already have 9000 satellites in orbit. So we know what it's like being in space."

Elon Musk on 𝕏 Spaces tonight: "The biggest opportunity on the moon is to make solar cells and radiators, and then, you're manufacturing on the moon anything that weighs a lot, chips maybe still come from Earth, they weigh very little. And then you can use a mass driver to put a billion tons of AI powered satellites into orbit per year. You could set a scale to 100 terawatts of AI compute per year from the moon. We already have 9000 satellites in orbit. So we know what it's like being in space."

DogeDesigner

241,287 views • 9 months ago

Elon Musk predicts AI compute in space could become cheaper than terrestrial AI far sooner than most people expect....possibly within just 2–3 years Because solar panels in orbit can generate roughly 5x more usable energy than on Earth because there’s: • No atmosphere blocking sunlight • No day-night cycle • No seasonal variation • Continuous exposure to the Sun • Far higher solar energy efficiency than on Earth Space-based solar can eventually become cheaper than terrestrial solar because you don’t need massive protective structures, heavy glass, or weather-resistant infrastructure And once launch costs fall low enough with fully reusable rockets like Starship, deploying AI clusters in orbit could become economically compelling The future of AI will scale with solar-powered compute infrastructure operating directly in space

Elon Musk predicts AI compute in space could become cheaper than terrestrial AI far sooner than most people expect....possibly within just 2–3 years Because solar panels in orbit can generate roughly 5x more usable energy than on Earth because there’s: • No atmosphere blocking sunlight • No day-night cycle • No seasonal variation • Continuous exposure to the Sun • Far higher solar energy efficiency than on Earth Space-based solar can eventually become cheaper than terrestrial solar because you don’t need massive protective structures, heavy glass, or weather-resistant infrastructure And once launch costs fall low enough with fully reusable rockets like Starship, deploying AI clusters in orbit could become economically compelling The future of AI will scale with solar-powered compute infrastructure operating directly in space

X Freeze

20,162 views • 4 months ago

Elon Musk just confirmed the most INSANE IPO in history. SpaceX is going public in 2026. $1.5 TRILLION valuation. Raising $30+ billion. That's the biggest IPO ever made. Beating Saudi Aramco's $29 billion record from 2019. But here's what everyone's missing: This isn't about space tourism or Mars missions. Elon is literally about to win the entire AI race. And 99% of people have no idea how... Here's the problem killing every AI company right now: POWER. Oracle just reported earnings. They burned through $12 BILLION in one quarter building data centers. Their free cash flow? NEGATIVE $10 billion. Revenue missed estimates. Stock crashed 11%. Microsoft, Amazon, Google all scrambling to find enough electricity for AI training. The brutal math: The US generates 490 gigawatts of total power. AI is projected to need 123 gigawatts by 2035. That's a QUARTER of the entire electrical grid. Just for artificial intelligence. Goldman Sachs says AI energy demand could jump 165% by 2030. There is literally not enough power on Earth to run AI at the scale these companies are promising. Every data center needs massive cooling systems. Billions of gallons of water per year. Insane energy costs. And the infrastructure can't keep up. Elon's solution? Stop building on Earth entirely. SpaceX is building data centers in SPACE. Not a concept. Not 10 years out. Literally starting in 2026. They're upgrading Starlink V3 satellites to carry AI computing chips. Each satellite gets 24/7 solar power. No clouds. No night. No weather disruptions. No grid bottlenecks. And the insane part is that Starship can deliver 300 to 500 gigawatts of solar-powered AI satellites into orbit every single year. At 300 gigawatts per year, the AI computing power in space would exceed the entire U.S. economy's total electricity consumption within two years. Just from satellites. Processing in orbit. While Oracle is begging banks for loans to finish data centers and OpenAI is stuck in circular funding arrangements with Microsoft, Elon already owns everything: The rockets. The satellites. The launch infrastructure. The AI company (xAI). He doesn't need to ask utilities for permission. Doesn't need grid approvals from local governments. Doesn't need to build nuclear plants or wait for clean energy. He just launches. And everyone else is scrambling to catch up: Jeff Bezos sees it. Blue Origin announced they're building their own orbital data centers. Google just launched "Project Suncatcher" with plans to deploy AI satellites by 2027. Eric Schmidt, the former CEO of Google, literally BOUGHT an entire rocket company (Relativity Space) just to compete in this space. But they're all 3+ years behind Elon. SpaceX already has 6,000+ Starlink satellites in orbit. The infrastructure is built. The $30 billion from the IPO? Going straight into scaling orbital compute. SpaceX revenue is jumping from $15 billion in 2025 to $24 billion in 2026. Most of that from Starlink. Now add space-based AI infrastructure on top. Here's why this matters: Whoever controls orbital computing controls the AI revolution. And there's only ONE company on Earth with fully reusable rockets that can launch at the scale required. Jensen Huang, Nvidia's CEO, called space data centers "a dream." Translation: Nvidia is screwed if Elon actually pulls this off. Because if SpaceX succeeds, every AI company on the planet becomes Elon's customer. OpenAI needs compute? Running on SpaceX satellites. Google needs more capacity? Renting orbital infrastructure. Microsoft needs power? Paying SpaceX for launch and compute access. Elon won't just be in the AI race. He'll own the entire track everyone else is running on. The $1.5 trillion valuation sounds crazy until you realize what he's actually building. It's not a rocket company. It's the infrastructure layer for the next 50 years of computing. People calling it overvalued have no idea what's coming.

Elon Musk just confirmed the most INSANE IPO in history. SpaceX is going public in 2026. $1.5 TRILLION valuation. Raising $30+ billion. That's the biggest IPO ever made. Beating Saudi Aramco's $29 billion record from 2019. But here's what everyone's missing: This isn't about space tourism or Mars missions. Elon is literally about to win the entire AI race. And 99% of people have no idea how... Here's the problem killing every AI company right now: POWER. Oracle just reported earnings. They burned through $12 BILLION in one quarter building data centers. Their free cash flow? NEGATIVE $10 billion. Revenue missed estimates. Stock crashed 11%. Microsoft, Amazon, Google all scrambling to find enough electricity for AI training. The brutal math: The US generates 490 gigawatts of total power. AI is projected to need 123 gigawatts by 2035. That's a QUARTER of the entire electrical grid. Just for artificial intelligence. Goldman Sachs says AI energy demand could jump 165% by 2030. There is literally not enough power on Earth to run AI at the scale these companies are promising. Every data center needs massive cooling systems. Billions of gallons of water per year. Insane energy costs. And the infrastructure can't keep up. Elon's solution? Stop building on Earth entirely. SpaceX is building data centers in SPACE. Not a concept. Not 10 years out. Literally starting in 2026. They're upgrading Starlink V3 satellites to carry AI computing chips. Each satellite gets 24/7 solar power. No clouds. No night. No weather disruptions. No grid bottlenecks. And the insane part is that Starship can deliver 300 to 500 gigawatts of solar-powered AI satellites into orbit every single year. At 300 gigawatts per year, the AI computing power in space would exceed the entire U.S. economy's total electricity consumption within two years. Just from satellites. Processing in orbit. While Oracle is begging banks for loans to finish data centers and OpenAI is stuck in circular funding arrangements with Microsoft, Elon already owns everything: The rockets. The satellites. The launch infrastructure. The AI company (xAI). He doesn't need to ask utilities for permission. Doesn't need grid approvals from local governments. Doesn't need to build nuclear plants or wait for clean energy. He just launches. And everyone else is scrambling to catch up: Jeff Bezos sees it. Blue Origin announced they're building their own orbital data centers. Google just launched "Project Suncatcher" with plans to deploy AI satellites by 2027. Eric Schmidt, the former CEO of Google, literally BOUGHT an entire rocket company (Relativity Space) just to compete in this space. But they're all 3+ years behind Elon. SpaceX already has 6,000+ Starlink satellites in orbit. The infrastructure is built. The $30 billion from the IPO? Going straight into scaling orbital compute. SpaceX revenue is jumping from $15 billion in 2025 to $24 billion in 2026. Most of that from Starlink. Now add space-based AI infrastructure on top. Here's why this matters: Whoever controls orbital computing controls the AI revolution. And there's only ONE company on Earth with fully reusable rockets that can launch at the scale required. Jensen Huang, Nvidia's CEO, called space data centers "a dream." Translation: Nvidia is screwed if Elon actually pulls this off. Because if SpaceX succeeds, every AI company on the planet becomes Elon's customer. OpenAI needs compute? Running on SpaceX satellites. Google needs more capacity? Renting orbital infrastructure. Microsoft needs power? Paying SpaceX for launch and compute access. Elon won't just be in the AI race. He'll own the entire track everyone else is running on. The $1.5 trillion valuation sounds crazy until you realize what he's actually building. It's not a rocket company. It's the infrastructure layer for the next 50 years of computing. People calling it overvalued have no idea what's coming.

Ricardo

2,910,017 views • 9 months ago

It’s actually happening: Video footage of construction for SpaceX’s project to put AI Data Centers in orbit These Data Centers in space won’t take up earths resources like electricity and water because they will use solar power and be cooled by space “The SpaceX campus in Bastrop County is pushing for an ambitious project that would build what it's calling the AI1 satellite, a data center in space. There are visible signs construction is underway after the tech company announced this large expansion project where the Starlink facility currently sits it's being called the GigaSat factory — The company plans to launch these satellites into Earth's orbit with SpaceX Starships. The company says this tech will be powered by solar energy, and the cold temperatures in space will keep it from overheating” The goal is large scale meaningful production by the end of 2027, supporting an annualized rate of ~1 GW of orbital AI compute. This means thousands of satellites per year, with even more to scale much higher afterward

It’s actually happening: Video footage of construction for SpaceX’s project to put AI Data Centers in orbit These Data Centers in space won’t take up earths resources like electricity and water because they will use solar power and be cooled by space “The SpaceX campus in Bastrop County is pushing for an ambitious project that would build what it's calling the AI1 satellite, a data center in space. There are visible signs construction is underway after the tech company announced this large expansion project where the Starlink facility currently sits it's being called the GigaSat factory — The company plans to launch these satellites into Earth's orbit with SpaceX Starships. The company says this tech will be powered by solar energy, and the cold temperatures in space will keep it from overheating” The goal is large scale meaningful production by the end of 2027, supporting an annualized rate of ~1 GW of orbital AI compute. This means thousands of satellites per year, with even more to scale much higher afterward

Wall Street Apes

72,007 views • 1 month ago

Orbit AI Satellite Successfully Achieve World’s First Orbital AI Deployment and Launching Digital AI Sovereignty Decentralized Orbital AI Network Orbit AI Orbit AI🛰️ today announced that the first satellite, “OAI Genesis-1,” has successfully launched and entered Low Earth Orbit (LEO). Amidst fierce competition from tech giants (e.g., Starlink Starlink Elon Musk , Google AI Project Suncatcher) in space AI computing, this launch signifies Orbit AI’s position as the first to achieve real-world AI deployment, formally inaugurating its "Orbit AI Cloud Platform." Genesis-1 is equipped with NVIDIA NVIDIA AI Compute Cores, running a 2.6B parameter AI model for real-time analysis of infrared remote sensing data in space. By processing data on orbit, Genesis-1 drastically reduces critical information retrieval time (e.g., disaster alerts, maritime monitoring) from hours to mere seconds, while cutting transmission bandwidth costs by over 90%. Furthermore, Orbit AI has partnered with from energy company Powerbank (NASDAQ: SUUN) ( utilizing infinite solar power to achieve carbon-neutral computing and projecting a reduction in overall energy operational costs by 60%. Following its triumph at the BNB Chain Hackathon ( Orbit AI protocol is committed to creating an ultimate censorship-resistant deployment environment: Developers can deploy AI models, privacy applications, financial algorithms, and even blockchain nodes on the satellite network. This ensures that code and data operate in a physically isolated, neutral environment beyond the jurisdiction of major nations, guaranteeing extreme digital sovereignty and service resilience. Orbit AI will also leverage the RWA (Real World Assets) mechanism to allow community users to purchase satellite NFT shares, becoming co-owners of this space infrastructure and sharing in its compute revenues, thus building a community-owned orbital AI economy.

Orbit AI Satellite Successfully Achieve World’s First Orbital AI Deployment and Launching Digital AI Sovereignty Decentralized Orbital AI Network Orbit AI Orbit AI🛰️ today announced that the first satellite, “OAI Genesis-1,” has successfully launched and entered Low Earth Orbit (LEO). Amidst fierce competition from tech giants (e.g., Starlink Starlink Elon Musk , Google AI Project Suncatcher) in space AI computing, this launch signifies Orbit AI’s position as the first to achieve real-world AI deployment, formally inaugurating its "Orbit AI Cloud Platform." Genesis-1 is equipped with NVIDIA NVIDIA AI Compute Cores, running a 2.6B parameter AI model for real-time analysis of infrared remote sensing data in space. By processing data on orbit, Genesis-1 drastically reduces critical information retrieval time (e.g., disaster alerts, maritime monitoring) from hours to mere seconds, while cutting transmission bandwidth costs by over 90%. Furthermore, Orbit AI has partnered with from energy company Powerbank (NASDAQ: SUUN) ( utilizing infinite solar power to achieve carbon-neutral computing and projecting a reduction in overall energy operational costs by 60%. Following its triumph at the BNB Chain Hackathon ( Orbit AI protocol is committed to creating an ultimate censorship-resistant deployment environment: Developers can deploy AI models, privacy applications, financial algorithms, and even blockchain nodes on the satellite network. This ensures that code and data operate in a physically isolated, neutral environment beyond the jurisdiction of major nations, guaranteeing extreme digital sovereignty and service resilience. Orbit AI will also leverage the RWA (Real World Assets) mechanism to allow community users to purchase satellite NFT shares, becoming co-owners of this space infrastructure and sharing in its compute revenues, thus building a community-owned orbital AI economy.

Orbit AI🛰️

24,884 views • 10 months ago

Elon Musk: Data centers in space are much easier than people think. “SpaceX at this point has 10,000 satellites in orbit right now. And in the future, with Starship, we'll be launching over 10,000 communication satellites per year, each one of which is much more capable than our current satellites. So you can expect, probably, 10 to 100 times more communications capability than currently exists from space. But that will pale in comparison to the tonnage of AI satellites.” Interview with Forbes, May 18, 2026

Elon Musk: Data centers in space are much easier than people think. “SpaceX at this point has 10,000 satellites in orbit right now. And in the future, with Starship, we'll be launching over 10,000 communication satellites per year, each one of which is much more capable than our current satellites. So you can expect, probably, 10 to 100 times more communications capability than currently exists from space. But that will pale in comparison to the tonnage of AI satellites.” Interview with Forbes, May 18, 2026

ELON CLIPS

43,161 views • 4 months ago

The cheapest place to put AI will be space. Elon Musk says solar panels in space produce 5 times more power than on the ground. No atmosphere, no clouds, no day-night cycle. No batteries needed. And critically, no permits. Scaling energy on Earth means fighting land use regulations, environmental reviews, and grid interconnection queues that take years. Space has none of that. The math gets wild fast. SpaceX could launch hundreds of gigawatts of AI compute into orbit annually. That's more compute than currently exists on Earth. Ten thousand Starship launches per year. One launch every hour. And you only need 20 to 30 ships to sustain that cadence. Earth gets about half a billionth of the Sun's total energy output. A millionth of the Sun's energy is 100,000 times all of civilization's current electricity production. The AI race is not a software race. It is a power plant race. And software people are about to get a very hard lesson in hardware.

The cheapest place to put AI will be space. Elon Musk says solar panels in space produce 5 times more power than on the ground. No atmosphere, no clouds, no day-night cycle. No batteries needed. And critically, no permits. Scaling energy on Earth means fighting land use regulations, environmental reviews, and grid interconnection queues that take years. Space has none of that. The math gets wild fast. SpaceX could launch hundreds of gigawatts of AI compute into orbit annually. That's more compute than currently exists on Earth. Ten thousand Starship launches per year. One launch every hour. And you only need 20 to 30 ships to sustain that cadence. Earth gets about half a billionth of the Sun's total energy output. A millionth of the Sun's energy is 100,000 times all of civilization's current electricity production. The AI race is not a software race. It is a power plant race. And software people are about to get a very hard lesson in hardware.

Shruti

11,700 views • 3 months ago

Here’s Elon Musk explaining that SpaceX could launch up to one terawatt per year of AI compute capacity into Earth orbit — equivalent to the power output of roughly 1,000 nuclear power plants. “The next step beyond Earth data centers is our Earth orbital data centers. And we'll be launching with SpaceX orbital data centers at the 100-to-200-gigawatt-per-year level. Not cumulative, per year. And ultimately, we see a path to maybe launching as much as a terawatt per year of compute from Earth. But what if you want to go beyond a mere terawatt per year? In order to do that, you have to go to the Moon. So by having factories on the Moon, building AI satellites, and having a mass driver, which is the kind of thing you really only learn about in or read about in science fiction, but we're going to make it real. We're actually going to have a mass driver on the Moon. And if you do that, you can go several orders of magnitude greater. You can go to 1,000 gigawatts or more per year and ultimately get to maybe a millionth and then a thousandth and maybe even a few percent of the Sun's energy.” xAI All-Hands, February 10, 2026

Here’s Elon Musk explaining that SpaceX could launch up to one terawatt per year of AI compute capacity into Earth orbit — equivalent to the power output of roughly 1,000 nuclear power plants. “The next step beyond Earth data centers is our Earth orbital data centers. And we'll be launching with SpaceX orbital data centers at the 100-to-200-gigawatt-per-year level. Not cumulative, per year. And ultimately, we see a path to maybe launching as much as a terawatt per year of compute from Earth. But what if you want to go beyond a mere terawatt per year? In order to do that, you have to go to the Moon. So by having factories on the Moon, building AI satellites, and having a mass driver, which is the kind of thing you really only learn about in or read about in science fiction, but we're going to make it real. We're actually going to have a mass driver on the Moon. And if you do that, you can go several orders of magnitude greater. You can go to 1,000 gigawatts or more per year and ultimately get to maybe a millionth and then a thousandth and maybe even a few percent of the Sun's energy.” xAI All-Hands, February 10, 2026

ELON CLIPS

21,962 views • 6 months ago

Elon Musk on why the Moon might come before Mars: “You don’t necessarily have to go through the Moon to get to Mars. But I think we can build a self-growing city on the Moon faster than we can on Mars” The Moon has major advantages for scaling AI in space: Because it has no atmosphere and only one-sixth of Earth’s gravity, you can use a mass driver (railgun) to literally shoot AI data centers into deep space - no rockets required You can also manufacture solar panels and radiators directly from Moon materials. This could allow scaling to over 1,000 terawatts per year of AI compute - compared to roughly 1 terawatt per year if launching everything from Earth Mars remains the ultimate goal - a whole planet with Earth-like gravity and a thin atmosphere that could one day be warmed up to have oceans and walkable surfaces without spacesuits But the Moon could be the faster stepping stone to build massive infrastructure in space

Elon Musk on why the Moon might come before Mars: “You don’t necessarily have to go through the Moon to get to Mars. But I think we can build a self-growing city on the Moon faster than we can on Mars” The Moon has major advantages for scaling AI in space: Because it has no atmosphere and only one-sixth of Earth’s gravity, you can use a mass driver (railgun) to literally shoot AI data centers into deep space - no rockets required You can also manufacture solar panels and radiators directly from Moon materials. This could allow scaling to over 1,000 terawatts per year of AI compute - compared to roughly 1 terawatt per year if launching everything from Earth Mars remains the ultimate goal - a whole planet with Earth-like gravity and a thin atmosphere that could one day be warmed up to have oceans and walkable surfaces without spacesuits But the Moon could be the faster stepping stone to build massive infrastructure in space

X Freeze

37,598 views • 4 months ago

Elon Musk just unveiled SpaceXAI's first AI satellite. • 150 kW peak power / 120 kW sustained compute power • 150 kW solar array using SpaceX-manufactured solar technology • Centralized AI compute payload designed for high-performance AI workloads • 70-meter wingspan when fully deployed • 110 m² deployable liquid radiators to remove waste heat in space • Redundant cooling loops with integrated micrometeoroid shielding • Designed to launch on Starship, enabling the mass-to-orbit needed for large-scale space computing • Uses laser links while avoiding many of the complex communications systems required by Starlink satellites • SpaceX believes future versions can scale far beyond this first design Elon Musk says the path to scaling AI in space requires 3 things: • Massive launch capability (Starship) • Enormous solar power generation • Large radiators to reject heat from AI chips He also suggested that truly large-scale orbital AI could eventually require hundreds of gigawatts to a terawatt of power, implying millions of tons of infrastructure in orbit.

Elon Musk just unveiled SpaceXAI's first AI satellite. • 150 kW peak power / 120 kW sustained compute power • 150 kW solar array using SpaceX-manufactured solar technology • Centralized AI compute payload designed for high-performance AI workloads • 70-meter wingspan when fully deployed • 110 m² deployable liquid radiators to remove waste heat in space • Redundant cooling loops with integrated micrometeoroid shielding • Designed to launch on Starship, enabling the mass-to-orbit needed for large-scale space computing • Uses laser links while avoiding many of the complex communications systems required by Starlink satellites • SpaceX believes future versions can scale far beyond this first design Elon Musk says the path to scaling AI in space requires 3 things: • Massive launch capability (Starship) • Enormous solar power generation • Large radiators to reject heat from AI chips He also suggested that truly large-scale orbital AI could eventually require hundreds of gigawatts to a terawatt of power, implying millions of tons of infrastructure in orbit.

DogeDesigner

138,388 views • 4 months ago

Starcloud (starcloud_inc1) recently made history by launching a satellite with an NVIDIA H100 into orbit — the first time a GPU that powerful has ever operated in space. It's the first step toward building AI data centers in orbit, powered by continuous sunlight and cooled by radiating heat into deep space. Their approach could one day rival the world's biggest data centers while using less energy, zero fresh water, and far lower emissions. YC's Aaron Epstein visited Starcloud's HQ, where co-founders , Ezra Feilden, and Adrian Andrei Oltean explained how they built a working prototype in just 15 months — and why big tech is racing to space for AI compute.

Starcloud (starcloud_inc1) recently made history by launching a satellite with an NVIDIA H100 into orbit — the first time a GPU that powerful has ever operated in space. It's the first step toward building AI data centers in orbit, powered by continuous sunlight and cooled by radiating heat into deep space. Their approach could one day rival the world's biggest data centers while using less energy, zero fresh water, and far lower emissions. YC's Aaron Epstein visited Starcloud's HQ, where co-founders , Ezra Feilden, and Adrian Andrei Oltean explained how they built a working prototype in just 15 months — and why big tech is racing to space for AI compute.

Y Combinator

369,276 views • 10 months ago

Elon Musk just put a five-year timeline on moving the majority of AI compute off the surface of the Earth. Musk: “5 years from now my prediction is we will launch and be operating every year more AI in space than the cumulative total on Earth.” Not decades from now. Five years. Dwarkesh Patel broke down the math live. 100 gigawatts of AI in orbit requires roughly 10,000 Starship launches per year. One launch every single hour. Musk confirmed it without flinching. The entire operation could run on as few as 20 or 30 physical Starships, each one cycling back to the pad every 30 hours. A fleet smaller than most regional airlines. Deploying more intelligence per year than the entire planet currently runs. Musk: “SpaceX is gearing up to do 10,000 launches a year. And maybe even 20 or 30,000 launches a year.” Every data center under construction right now. Every GPU cluster. Every billion-dollar AI facility going up across three continents. All of it combined would still fall short of what one company plans to put above the atmosphere every year. The reason no one else can follow him here is physics. AI scaling on the ground is already hitting hard ceilings. Grid capacity. Permitting. Cooling. The surface of the planet has a finite budget for how much power you can feed into compute. Space does not. Unobstructed solar at a scale Earth physically cannot provide. Musk: “On Earth you can get to around a terawatt a year of AI in space before you start having fuel supply challenges for the rocket.” A terawatt. That single number exceeds the entire electrical generation capacity of the United States. And the only constraint Musk names is not engineering. Not physics. Not capital. Fuel supply for the rockets. This is why SpaceX and xAI were never two separate visions. The rockets exist to move intelligence off the surface. The AI exists to justify building the rockets. One architecture split across two companies. Every other AI lab on the planet is fighting over the same finite pool of terrestrial power and real estate. Musk is not trying to win that fight. He is leaving the board entirely. Five years from now, the majority of functioning intelligence in the solar system may not be on this planet. It will be above it, running on sunlight, bound by no grid, governed by no jurisdiction. Earth becomes the secondary compute environment in its own solar system.

Elon Musk just put a five-year timeline on moving the majority of AI compute off the surface of the Earth. Musk: “5 years from now my prediction is we will launch and be operating every year more AI in space than the cumulative total on Earth.” Not decades from now. Five years. Dwarkesh Patel broke down the math live. 100 gigawatts of AI in orbit requires roughly 10,000 Starship launches per year. One launch every single hour. Musk confirmed it without flinching. The entire operation could run on as few as 20 or 30 physical Starships, each one cycling back to the pad every 30 hours. A fleet smaller than most regional airlines. Deploying more intelligence per year than the entire planet currently runs. Musk: “SpaceX is gearing up to do 10,000 launches a year. And maybe even 20 or 30,000 launches a year.” Every data center under construction right now. Every GPU cluster. Every billion-dollar AI facility going up across three continents. All of it combined would still fall short of what one company plans to put above the atmosphere every year. The reason no one else can follow him here is physics. AI scaling on the ground is already hitting hard ceilings. Grid capacity. Permitting. Cooling. The surface of the planet has a finite budget for how much power you can feed into compute. Space does not. Unobstructed solar at a scale Earth physically cannot provide. Musk: “On Earth you can get to around a terawatt a year of AI in space before you start having fuel supply challenges for the rocket.” A terawatt. That single number exceeds the entire electrical generation capacity of the United States. And the only constraint Musk names is not engineering. Not physics. Not capital. Fuel supply for the rockets. This is why SpaceX and xAI were never two separate visions. The rockets exist to move intelligence off the surface. The AI exists to justify building the rockets. One architecture split across two companies. Every other AI lab on the planet is fighting over the same finite pool of terrestrial power and real estate. Musk is not trying to win that fight. He is leaving the board entirely. Five years from now, the majority of functioning intelligence in the solar system may not be on this planet. It will be above it, running on sunlight, bound by no grid, governed by no jurisdiction. Earth becomes the secondary compute environment in its own solar system.

Dustin

13,474 views • 5 months ago