Higher usage limits for Claude and a compute deal with SpaceX
… We train and run Claude on a range of AI hardware—AWS Trainium, Google TPUs, and NVIDIA GPUs—and continue to explore opportunities to bring additional capacity online. …
… We train and run Claude on a range of AI hardware—AWS Trainium, Google TPUs, and NVIDIA GPUs—and continue to explore opportunities to bring additional capacity online. …
… Team Claude’s members largely worked in partnership with the AI. This experiment demonstrated substantial AI uplift in robotics—bridging digital and physical worlds. As models improve, their ability to affect the physical world by interacting with previously-unknown hardware could advance rapidly. …
… We train and run Claude on a range of AI hardware—AWS Trainium, Google TPUs, and NVIDIA GPUs—which means we can match workloads to the chips best suited for them. This diversity of platforms translates to better performance and greater resilience for customers who depend on Claude for critical work. …
… Managed Agents can accommodate any of these, matching Claude’s intelligence over time. Meta-harness design means being opinionated about the interfaces around Claude: we expect that Claude will need the ability to manipulate state the session and perform computation the sandbox . …
… Combined with additional capacity expansions and our diversified hardware strategy, with workloads spread across a range of chips, we are building the infrastructure needed to keep Claude at the frontier and reliably serve our growing customer base. …
… Footnotes Related content Natural Language Autoencoders: Turning Claude’s thoughts into text AI models like Claude talk in words but think in numbers. In this study we train Claude to translate its thoughts into human-readable text. …