TheSequence
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2 weeks ago
Space is becoming a competitive frontier for AI companies because orbital locations offer unmetered energy and avoid terrestrial regulatory constraints, with trillion-dollar companies and startups racing to deploy compute infrastructure there. As of December 2025, nanoGPT was trained in orbit on an H100 processor aboard a 130-pound satellite, demonstrating that practical AI workloads now run in space. This shift reframes low Earth orbit from a scientific domain into contested economic territory where energy scarcity, rather than other computational bottlenecks, determines the next phase of AI capability development.
Rest of World
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2 weeks ago
India launched a government-backed hackathon partnering Bhashini, Current AI, and Kalpa Impact to develop affordable, multilingual AI tools that run offline using open-source models for use in schools, farms, and villages with limited connectivity. Organizers will select 20 teams to receive hardware kits and mentorship, with winning solutions to be deployed in government departments. The initiative reflects a shift toward viewing AI as public infrastructure rather than proprietary products, though experts question whether hackathon prototypes can scale without sustained funding, engineering talent, and clear business models.
The Neuron
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2 weeks ago
Meta is building a cloud business to sell excess AI compute capacity, with the company's stock rising 9% after investors viewed this as a way to justify its massive infrastructure spending. The company is exploring selling AI compute and possibly hosted model access through this new venture. This shift positions Meta to generate revenue from its infrastructure investments and compete with cloud providers like AWS in the AI services market.
NVIDIA
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2 weeks ago
NVIDIA introduced a new business model that enables AI cloud providers to access NVIDIA infrastructure through revenue-sharing and credit-support arrangements, allowing startups and enterprises faster access to accelerated computing for AI inference and training. Sharon AI is deploying up to 40,000 NVIDIA Grace Blackwell GB300 GPUs, while Firmus is building an AI factory campus in Indonesia expected to scale to 360 megawatts with up to 170,000 NVIDIA GPUs. The model accelerates adoption of NVIDIA platforms among AI-native companies by removing barriers to large-scale compute access without delays from site selection and infrastructure construction.
