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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...

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BlackRock

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13,467 просмотров • 3 месяцев назад •via X (Twitter)

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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.
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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.

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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.
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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.

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