Today I’m joining @Natl_Compute I’ve spent the last four years working on GPU access, first as a founding engineer at Brev and then at NVIDIA after they acquired us in 2024. When I started, on-demand GPU capacity at the hyperscalers was effectively gone. If you were an independent researcher, a two-person startup, or a grad student with a grant and a deadline, you refreshed console pages and got nothing, or hammered the API only to get “insufficient capacity” errors back. I vividly remember hard-coding a filter at Brev to hide certain GCP instances because they almost never provisioned. Around 2023, a wave of new public clouds were coming online, and many of them had on-demand capacity. That gap is a big part of why Brev worked: we gave researchers a simple way to find GPUs across dozens of providers and start building. For a while, aggregation was enough. Then in 2025, I watched that capacity dry up too. Access to compute has never been worse. Existing supply is already under contract, and new capacity is reserved before it ever comes online. I won’t rehash why. There are a hundred good explanations out there covering debt financing, anchor tenants, backstops, lead times and so on. What matters more are the downstream effects. Long-term, single-tenant leases hold back scaling for everyone who couldn’t secure funding in time, and the industry’s momentum shouldn’t hinge on the handful of players who locked up access early. Today small startups, labs, and university researchers don’t even get a chance to compete. National Compute is solving this with a foundational layer we call “the Grid”. It’s an interconnected network of multi-silicon capacity composed of multiple providers and spans multiple sites that will be pooled for our members. The speed at which this team has been able to scale in such a small fraction of time is remarkable, and I’m excited to push that scale even higher for the public benefit.