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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...

359,597 views • 10 months ago •via X (Twitter)

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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🛰️

24,839 views • 9 months 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.

Milk Road AI

12,738 views • 3 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.

Nic Cruz Patane

49,035 views • 9 months ago

We sat down with Philip Johnston, co-founder and CEO of Starcloud, at MIT to discuss why the future of data centers might be in space. After graduating Y Combinator less than 2 years ago, Starcloud just raised an impressive $170M Series A at a $1.1B valuation led by Benchmark and EQT Ventures & Growth. The conversation covers everything from solar physics and cooling systems to GPU economics, radiation hardening, launch costs, and satellite design. Philip also shares what it takes to build a unicorn deeptech startup. We discuss his experience with YC, the skepticism around their demoday launch, and the crazy last minute race to get Starcloud’s first satellite onboard their scheduled Falcon flight. Full episode is here on X and at any of the links below (see comment). Timestamps: 00:00 - Intro 01:12 - What is Starcloud? 02:44 - Why do data centers need to go to space? 06:15 - Can’t we just build more solar panels on earth? 11:10 - Economic analysis of Starcloud 19:56 - How does Starcloud’s cooling work? 28:26 - Training an LLM in space 32:07 - Addressing critics on space Twitter 34:23 - Is Starcloud overfunded? 35:59 - Will demand for data centers keep going up? 38:11 - GPU lifespan and disposal in space 39:47 - Bus structures 41:43 - Starcloud’s origin and founders 49:29 - Fundraising, Competition, and Meeting Expectations 53:29 - Satellite size and collisions 56:29 - Manufacturing Bottlenecks 1:00:20 - Starcloud 1 tests 1:01:57 - Acceleration after YC 1:03:43 - Testing on Earth 1:05:06 - Motivations for Starcloud 1:06:45 - Data centers on the Moon 1:08:12 - Interacting with AI companies 1:08:18 - What’s next for Starcloud? 1:14:01 - Other uses for Starcloud satellites 1:17:56 - Lunar hotels and space elevators 1:24:28 - Complementary business ideas to Starcloud 1:29:51 - Philip’s competitive twin 1:32:18 - Philip and Mike’s thoughts on YC 1:36:04 - Advice for young entrepreneurs Elon Musk Scott Manley Kyle Hill Hank Green

632nm

46,599 views • 5 months ago