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Google and SpaceX are in talks to launch orbital data centers in space as part of an initiative to support the growing demand for AI infrastructure. This move aims to leverage the advantages of space-based computing, including access to uninterrupted solar energy.

5/5 🧵 The catch: today, ground-based data centers are still cheaper once you factor in satellite construction and launch costs. So the orbital thesis is more future bet than present advantage. If launch costs keep falling and AI hunger keeps exploding, this stops sounding ridiculous faster than people think. For now, it’s bold, expensive, and very on-brand for 2026 tech. 📎 Source

#threadstorm

4/5 🧵 The timing matters. SpaceX recently tied itself more tightly to AI infrastructure through xAI, and Anthropic reportedly struck a deal last week to use compute from xAI’s Memphis data center, with future collaboration on orbital data centers also in the mix. Add Google’s earlier $900 million investment in SpaceX back in 2015, and the relationship already has real financial history behind it.

3/5 🧵 Google isn’t just flirting with one partner either. It’s reportedly talking with other launch companies too, and plans to launch prototype satellites by 2027 under Project Suncatcher, an initiative announced last year. So this isn’t random sci-fi chatter — there’s at least an early roadmap forming around space-based compute experiments.

2/5 🧵 The pitch is simple: launch compute into orbit and sidestep some of the headaches choking terrestrial buildouts — land, power bottlenecks, and public backlash from communities that don’t want giant data centers dropped next door. SpaceX is reportedly using that vision as part of the story ahead of its planned $1.75 trillion IPO later this year.

1/5 🧵 Google and SpaceX are reportedly discussing orbital data centers for AI compute. That’s either visionary infrastructure or the most expensive way possible to avoid local zoning fights. The real story: AI demand is now so absurdly large that “put the servers in space” is being pitched with a straight face.

So the real advancement is this: AI is shifting drug discovery from a slow, expensive guessing game toward a more predictive, iterative, and efficient system. It reduces the number of wasted experiments, shortens discovery cycles, improves candidate quality, and helps teams allocate resources where they matter most. That does not make medicine easy. It makes the path to new medicine less wasteful. And in this industry, shaving off waste is basically gold.

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