Google just fired up its Project Suncatcher prototype satellite, generating the first-ever AI response from a data center-grade TPU in orbit. Passing over Norway, the satellite ran Google's Gemma 4 model to beam back a space-themed haiku. Why it matters: Google is testing whether AI chips can survive extreme radiation and thermal swings, setting the stage for orbital data centers.
Google just revealed its Project Suncatcher moonshot is launching a prototype satellite aboard a SpaceX rocket to test how Trillium TPUs handle space. Ground tests show the chips survive radiation exceeding a five-year mission, with laser-linked clusters planned for 2027. Why it matters: Low Earth orbit gets up to 8x more solar energy, making space data centers a wild but serious bet against earthbound power limits.
Google is reportedly developing a custom server chip called "Frozen v2" that physically etches Gemini model architecture into silicon to cut data movement. Slated for 2028, it could deliver 6 to 10 times more tokens per watt than current TPUs, targeting a cloud compute crunch that has forced Google to turn away customers.
Anthropic has committed to spending roughly $200 billion on Google Cloud and TPU chips over the next five years, according to The Information. The massive deal secures five gigawatts of server capacity and represents over 40% of Google's cloud backlog. Why it matters: The cloud boom is increasingly riding on whether cash-burning AI startups can fulfill their astronomical compute budgets.
Google is investing up to $40 billion in Anthropic, committing an immediate $10 billion at a $350 billion valuation with another $30 billion tied to performance targets. The deal also locks in 5 gigawatts of Google Cloud compute over the next five years to power Claude.
Anthropic just signed a major compute agreement with Google and Broadcom to secure multiple gigawatts of next-generation TPU capacity starting in 2027. The expansion comes alongside explosive customer growth: run-rate revenue has surged past $30 billion—up from roughly $9 billion at the end of 2025—while seven-figure enterprise clients doubled to over 1,000 in under two months. The vast majority of the new compute will be based in the U.S. to power frontier Claude models.
OpenAI just confirmed it is testing Google's TPUs, but shut down rumors of any large-scale rollout. While the company continues to rely heavily on Nvidia GPUs alongside AMD and CoreWeave, it is also pushing ahead with an in-house chip expected to tape out later this year.
OpenAI has reportedly started leasing Google's TPU chips to handle inference for ChatGPT and other services. The move marks its first major compute shift beyond Nvidia hardware, aiming to rein in spiraling inference costs and diversify a single-vendor supply chain.
Google just revealed Ironwood, its seventh-generation custom TPU and the first designed from scratch for AI inference. The chip doubles the energy efficiency of the previous Trillium generation and packs 192 GB of high-bandwidth memory. It will arrive on Google Cloud later this year.
Google just officially named and released pre-trained weights for AlphaChip, its reinforcement learning system that treats chip floorplanning like a board game. The AI generates superhuman circuit layouts in hours instead of months, and has already designed Google's last three TPU generations as well as MediaTek chips. Why it matters: AI is no longer just running on advanced silicon—it is actively redesigning the hardware that powers it.
Google Cloud just unveiled its fifth-generation custom TPU chips at Cloud Next, aiming squarely at high AI computing costs. The new processors deliver 2x the training performance per dollar and 2.5x for inferencing versus the previous gen, while letting massive workloads scale across physical clusters to tens of thousands of chips.
