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What needs to happen for space-based data centers to scale? Lower launch costs and reusable systems could enable AI compute in orbit, easing terrestrial constraints and expanding infrastructure. Watch the "Big Ideas 2026" webinar to learn more. ARK Invest Europe

ARK Invest

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71,466 次观看 • 3 个月前 •via X (Twitter)

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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

20,056 次观看 • 2 个月前

Is space the next investing frontier? BlackRock’s Reid Menge breaks down why terrestrial constraints, AI-driven demand and falling technology costs could mean portions of economic activity move into orbit. From powering AI with space-based solar to satellites serving multiple industries at once, the opportunity may be closer than many think. Learn more in this episode of the BlackRock Bottom Line:

Is space the next investing frontier? BlackRock’s Reid Menge breaks down why terrestrial constraints, AI-driven demand and falling technology costs could mean portions of economic activity move into orbit. From powering AI with space-based solar to satellites serving multiple industries at once, the opportunity may be closer than many think. Learn more in this episode of the BlackRock Bottom Line:

BlackRock

13,177 次观看 • 1 个月前

Coming soon: $AI gensyn, the network for machine intelligence, is an open infrastructure layer for AI. It provides infrastructure AI needs to operate at scale: compute, data, and information exchange. Get ready →

Coming soon: $AI gensyn, the network for machine intelligence, is an open infrastructure layer for AI. It provides infrastructure AI needs to operate at scale: compute, data, and information exchange. Get ready →

Kraken Listings

53,052 次观看 • 2 个月前

Jim Cramer says $CRWV could play a role in orbital data centers if AI compute eventually moves to space. He said CoreWeave has one of the best handles on building data centers quickly making it a name to watch if the space-compute thesis becomes real.

Jim Cramer says $CRWV could play a role in orbital data centers if AI compute eventually moves to space. He said CoreWeave has one of the best handles on building data centers quickly making it a name to watch if the space-compute thesis becomes real.

Shay Boloor

159,180 次观看 • 25 天前

Telecom infrastructure is becoming a distributed AI compute layer, unlocking smarter cities and more efficient operations. NVIDIA AI-RAN and NVIDIA Metropolis Blueprint for video search and summarization enable AI agents to run continuously at the edge. These agents analyze real-time data streams from connected sensors over 5G to power live monitoring and infrastructure inspection. ▶️ Watch the full video to learn more:

Telecom infrastructure is becoming a distributed AI compute layer, unlocking smarter cities and more efficient operations. NVIDIA AI-RAN and NVIDIA Metropolis Blueprint for video search and summarization enable AI agents to run continuously at the edge. These agents analyze real-time data streams from connected sensors over 5G to power live monitoring and infrastructure inspection. ▶️ Watch the full video to learn more:

NVIDIA AI

11,078 次观看 • 2 个月前

NVIDIA AI Aerial uses neural networks to learn from data, adapt in real time, and scale with complexity. This boosts spectral efficiency, lowers costs, and improves connectivity for telecom. To learn more, watch the full video ➡️

NVIDIA AI Aerial uses neural networks to learn from data, adapt in real time, and scale with complexity. This boosts spectral efficiency, lowers costs, and improves connectivity for telecom. To learn more, watch the full video ➡️

NVIDIA AI

11,236 次观看 • 1 年前

Aetherflux is taking AI compute to orbit with NVIDIA to launch the new era of space innovation. This includes bringing the NVIDIA Space-1 Vera Rubin Module, IGX Thor, and Jetson Orin to space, powering geospatial intelligence and autonomous space operations for next-generation space missions. We are deploying advanced satellite constellations designed to act as high-performance hubs for AI compute in orbit.

Aetherflux is taking AI compute to orbit with NVIDIA to launch the new era of space innovation. This includes bringing the NVIDIA Space-1 Vera Rubin Module, IGX Thor, and Jetson Orin to space, powering geospatial intelligence and autonomous space operations for next-generation space missions. We are deploying advanced satellite constellations designed to act as high-performance hubs for AI compute in orbit.

Cowboy Space Corp.

14,221 次观看 • 3 个月前

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

19,152 次观看 • 1 个月前

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

338,729 次观看 • 8 个月前

Elon just created the most valuable private company in history. And the VISION behind this move is going to win him the AI race. Yesterday, SpaceX and xAI combined in a $1.25 TRILLION deal, But this isn’t just a merger. Elon is literally solving AI’s biggest bottleneck: AI needs INSANE amounts of electricity. Every major AI company is hitting the same wall: Power constraints. OpenAI, Google, Anthropic are all racing to build bigger data centers. But they're all stuck on Earth fighting for the same limited power grid. Elon's solution: Move the data centers to SPACE. Last Friday, SpaceX filed with the FCC to launch up to 1 MILLION satellites. Not for internet. For compute. Solar-powered AI data centers in orbit that run 24/7 with zero cooling costs and unlimited energy from the sun. Look: On Earth, you need massive power plants, cooling systems, and infrastructure that costs billions and takes years to build. But in space? You have direct solar power. No cooling needed. Near-constant sunlight. According to Elon: "Within 2-3 years, space will be the lowest-cost way to generate AI compute." The numbers behind this are crazy: SpaceX made $8 billion profit on $15 billion revenue in 2025. xAI was valued at $230 billion standalone. Combined entity: $1.25 trillion heading into what could be the biggest IPO in history. And here's why this actually makes sense: SpaceX already dominates launches. 80% of their revenue comes from launching Starlink satellites. They've perfected reusable rockets. Launch costs keep dropping. Now instead of just launching communication satellites, they're launching compute infrastructure. xAI gets unlimited scalable compute without fighting for power grid access. SpaceX gets a customer that will need constant satellite refreshes and launches for decades. The vertical integration is incredible: SpaceX builds and launches the satellites. xAI runs the AI models on them. Grok gets trained on infrastructure no competitor can access. Starlink provides the communication backbone. Nobody else can replicate this. OpenAI can't launch rockets. Google can't either. What you have to understand about the upcoming IPO: This isn't just "rocket company goes public." It's "AI infrastructure company that happens to own the launch capability" goes public. Investors get exposure to both the AI race AND space commercialization in one ticker. That's why the $1.25 trillion valuation makes sense to Wall Street. Now here's the rational take: This is extremely ambitious. Maybe too ambitious. xAI is burning $1 billion per month right now competing with OpenAI. Space-based data centers have never been done at scale. The satellite constellation would be the largest in history by 100X. Technical challenges are massive. Regulatory approval isn't guaranteed. But if it works? Elon isn't just winning the AI race. He's changing WHERE the race happens. Imagine training AI models with 10X the compute power at 1/10th the cost because you're not constrained by Earth's power grid. That's game over for competition. The timeline to watch: Mid-2026: SpaceX/xAI IPO (largest in history) Late 2026: First orbital compute satellites launch 2027-2028: Proof of concept for space-based AI training If this actually delivers, we're looking at: The first trillion-dollar private company IPO. A new category of infrastructure (orbital compute). AI development unconstrained by terrestrial power limits. If it doesn't deliver? Well, it's still SpaceX with $8B in annual profit and dominance in launch services. Plus xAI with a $230B valuation and Grok. The risk-reward here is asymmetric. Downside: You own the world's most valuable rocket company. Upside: You own the infrastructure layer for all future AI development. Do you think datacenters in space could work?

Elon just created the most valuable private company in history. And the VISION behind this move is going to win him the AI race. Yesterday, SpaceX and xAI combined in a $1.25 TRILLION deal, But this isn’t just a merger. Elon is literally solving AI’s biggest bottleneck: AI needs INSANE amounts of electricity. Every major AI company is hitting the same wall: Power constraints. OpenAI, Google, Anthropic are all racing to build bigger data centers. But they're all stuck on Earth fighting for the same limited power grid. Elon's solution: Move the data centers to SPACE. Last Friday, SpaceX filed with the FCC to launch up to 1 MILLION satellites. Not for internet. For compute. Solar-powered AI data centers in orbit that run 24/7 with zero cooling costs and unlimited energy from the sun. Look: On Earth, you need massive power plants, cooling systems, and infrastructure that costs billions and takes years to build. But in space? You have direct solar power. No cooling needed. Near-constant sunlight. According to Elon: "Within 2-3 years, space will be the lowest-cost way to generate AI compute." The numbers behind this are crazy: SpaceX made $8 billion profit on $15 billion revenue in 2025. xAI was valued at $230 billion standalone. Combined entity: $1.25 trillion heading into what could be the biggest IPO in history. And here's why this actually makes sense: SpaceX already dominates launches. 80% of their revenue comes from launching Starlink satellites. They've perfected reusable rockets. Launch costs keep dropping. Now instead of just launching communication satellites, they're launching compute infrastructure. xAI gets unlimited scalable compute without fighting for power grid access. SpaceX gets a customer that will need constant satellite refreshes and launches for decades. The vertical integration is incredible: SpaceX builds and launches the satellites. xAI runs the AI models on them. Grok gets trained on infrastructure no competitor can access. Starlink provides the communication backbone. Nobody else can replicate this. OpenAI can't launch rockets. Google can't either. What you have to understand about the upcoming IPO: This isn't just "rocket company goes public." It's "AI infrastructure company that happens to own the launch capability" goes public. Investors get exposure to both the AI race AND space commercialization in one ticker. That's why the $1.25 trillion valuation makes sense to Wall Street. Now here's the rational take: This is extremely ambitious. Maybe too ambitious. xAI is burning $1 billion per month right now competing with OpenAI. Space-based data centers have never been done at scale. The satellite constellation would be the largest in history by 100X. Technical challenges are massive. Regulatory approval isn't guaranteed. But if it works? Elon isn't just winning the AI race. He's changing WHERE the race happens. Imagine training AI models with 10X the compute power at 1/10th the cost because you're not constrained by Earth's power grid. That's game over for competition. The timeline to watch: Mid-2026: SpaceX/xAI IPO (largest in history) Late 2026: First orbital compute satellites launch 2027-2028: Proof of concept for space-based AI training If this actually delivers, we're looking at: The first trillion-dollar private company IPO. A new category of infrastructure (orbital compute). AI development unconstrained by terrestrial power limits. If it doesn't deliver? Well, it's still SpaceX with $8B in annual profit and dominance in launch services. Plus xAI with a $230B valuation and Grok. The risk-reward here is asymmetric. Downside: You own the world's most valuable rocket company. Upside: You own the infrastructure layer for all future AI development. Do you think datacenters in space could work?

Ricardo

78,777 次观看 • 5 个月前

🚨 Sam Altman Throws Shade at Elon’s Vision of Putting Data Centers in Space “Putting data centers in space is ridiculous … Do the very rough math of launch costs relative to the cost of power we can do on Earth … Orbital data centers are not something that's going to matter at scale this decade.”

🚨 Sam Altman Throws Shade at Elon’s Vision of Putting Data Centers in Space “Putting data centers in space is ridiculous … Do the very rough math of launch costs relative to the cost of power we can do on Earth … Orbital data centers are not something that's going to matter at scale this decade.”

Chief Nerd

261,617 次观看 • 4 个月前

Sam Altman just called Elon Musk’s plan for AI data centers in space “ridiculous” in the current landscape—citing brutal launch costs and the hassle of orbital repairs. But history has a clear rule: never bet against Elon. Reusable rockets? Pipe dream—until they weren’t. Electric cars dominating? Laughable—until they did. Space-based compute? Watch this space. Altman might learn the hard way that what sounds absurd today becomes inevitable tomorrow. “I honestly think the idea, with the current landscape, of putting data centers in space is ridiculous.” — Sam Altman (via recent interview) Altman’s point on today’s math is fair—orbital setups aren’t scaling this decade. But Musk’s roadmap (Starship slashing costs, Starlink-scale networks, xAI + SpaceX integration) is built to rewrite that math entirely. History favors the bold dreamer over the cautious calculator. 🚀

Sam Altman just called Elon Musk’s plan for AI data centers in space “ridiculous” in the current landscape—citing brutal launch costs and the hassle of orbital repairs. But history has a clear rule: never bet against Elon. Reusable rockets? Pipe dream—until they weren’t. Electric cars dominating? Laughable—until they did. Space-based compute? Watch this space. Altman might learn the hard way that what sounds absurd today becomes inevitable tomorrow. “I honestly think the idea, with the current landscape, of putting data centers in space is ridiculous.” — Sam Altman (via recent interview) Altman’s point on today’s math is fair—orbital setups aren’t scaling this decade. But Musk’s roadmap (Starship slashing costs, Starlink-scale networks, xAI + SpaceX integration) is built to rewrite that math entirely. History favors the bold dreamer over the cautious calculator. 🚀

Tesla Owners Silicon Valley

15,661 次观看 • 4 个月前

With a remarkable year of innovation behind us, Cathie Wood looks back on the advances that defined 2025 and shares her optimism for what lies ahead. Happy New Year from ARK Invest and ARK Invest Europe! Stay tuned for Big Ideas 2026, coming soon.

With a remarkable year of innovation behind us, Cathie Wood looks back on the advances that defined 2025 and shares her optimism for what lies ahead. Happy New Year from ARK Invest and ARK Invest Europe! Stay tuned for Big Ideas 2026, coming soon.

ARK Invest

47,075 次观看 • 6 个月前

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

12,140 次观看 • 1 个月前

AI INFRASTRUCTURE/ENERGY DEMAND STOCKS TO KEEP ON WATCH FOR 2026 Ex-CEO $GOOGL Eric Schmidt on energy demand driven by AI: "We need energy and the numbers are profound. What we need from you is energy in all forms. People are planning 10 gigawatt data centers" $IREN: owns and develops vertically integrated data centers for hyperscalers $CIFR: large power footprint, 3.4 GW pipeline for AI workloads + HPC $WULF: high capacity, low cost data center expansion across Texas and New York $NBIS: AI compute and cloud services translating energy into revenue $CLSK: America’s Bitcoin Miner transitioning to AI infrastructure with a massive power footprint across 30+ data center sites $BITF: owns and operates power sites positioned for AI workloads, yet to sign with a hyperscaler but could come this year $GLXY: multi-gigawatt data center infrastructure at scale

AI INFRASTRUCTURE/ENERGY DEMAND STOCKS TO KEEP ON WATCH FOR 2026 Ex-CEO $GOOGL Eric Schmidt on energy demand driven by AI: "We need energy and the numbers are profound. What we need from you is energy in all forms. People are planning 10 gigawatt data centers" $IREN: owns and develops vertically integrated data centers for hyperscalers $CIFR: large power footprint, 3.4 GW pipeline for AI workloads + HPC $WULF: high capacity, low cost data center expansion across Texas and New York $NBIS: AI compute and cloud services translating energy into revenue $CLSK: America’s Bitcoin Miner transitioning to AI infrastructure with a massive power footprint across 30+ data center sites $BITF: owns and operates power sites positioned for AI workloads, yet to sign with a hyperscaler but could come this year $GLXY: multi-gigawatt data center infrastructure at scale

Small Cap Snipa

116,034 次观看 • 6 个月前

🇺🇸 Elon’s plan: Put 1 terawatt of AI compute in orbit using Terafab + Starship. Build the world’s largest AI chip factory on Earth, then use Starship to launch that compute power into space. Claim: 80% of Terafab’s entire output will go to orbital applications. This could become the backbone of space-based AI. Writer: Val

🇺🇸 Elon’s plan: Put 1 terawatt of AI compute in orbit using Terafab + Starship. Build the world’s largest AI chip factory on Earth, then use Starship to launch that compute power into space. Claim: 80% of Terafab’s entire output will go to orbital applications. This could become the backbone of space-based AI. Writer: Val

Mario Nawfal

49,380 次观看 • 19 天前

AI data centers are projected to use more energy than the country of Japan. Trump’s solution is beautiful: Force AI companies to build their own power. Meanwhile, Elon applies to launch one *million* satellites to put AI data centers in space.

AI data centers are projected to use more energy than the country of Japan. Trump’s solution is beautiful: Force AI companies to build their own power. Meanwhile, Elon applies to launch one million satellites to put AI data centers in space.

Peter St Onge, Ph.D.

120,212 次观看 • 5 个月前

Starship is what gives $SPCX a credible path into the ~$26.5T AI infrastructure TAM. If AI compute moves to orbit then SpaceX is the only vertically integrated player across the full stack, launch, manufacturing, power and now compute.

Starship is what gives $SPCX a credible path into the ~$26.5T AI infrastructure TAM. If AI compute moves to orbit then SpaceX is the only vertically integrated player across the full stack, launch, manufacturing, power and now compute.

Shay Boloor

151,845 次观看 • 27 天前

$RKLB partner Starcloud is building data centers in orbit & about to launch $NVDA H100s into space for the first time in a few weeks 👀

$RKLB partner Starcloud is building data centers in orbit & about to launch $NVDA H100s into space for the first time in a few weeks 👀

Shay Boloor

138,220 次观看 • 9 个月前

Elon on why the Moon is the key bridge to becoming multi-planetary: “We can build a self-growing city on the Moon faster than Mars. No atmosphere + 1/6th gravity = perfect for railguns/mass drivers to launch AI data centers into deep space using Moon materials. Could scale to 1,000+ terawatts of space-based AI compute. Plus… Moon vacations would be epic.” Visionary stuff from Elon🔥 Source: J.P. Morgan

Elon on why the Moon is the key bridge to becoming multi-planetary: “We can build a self-growing city on the Moon faster than Mars. No atmosphere + 1/6th gravity = perfect for railguns/mass drivers to launch AI data centers into deep space using Moon materials. Could scale to 1,000+ terawatts of space-based AI compute. Plus… Moon vacations would be epic.” Visionary stuff from Elon🔥 Source: J.P. Morgan

Mario Nawfal

174,675 次观看 • 1 个月前