So for the next steps, I mean we only have a 20-minute talk here. One of the things that we are doing is we're taking these as really benchmarks to see where the frontier models stop, and then we're building reinforcement learning environments to help get models past that. The way that we go about this is we've done a a fairly curated approach where we take open-source software and we built a very extensive vulnerability mining machine based upon our work with DARPA over the last decade for novel vulnerability discovery. We find unique proofs of vulnerability. These are zero days no one else use and we use these to then build reinforcement learning environments. Why are we finding zero days? Well, we want to make sure that the models aren't simply memorizing and we know if it's a vulnerability they've never seen before that it can't at least be just memorizing that. We're able to do this at scale where some of our the companies that we work with we're providing up to 10,000 reinforcement learning environments per month to really accelerate their uh learning. We of course can't take credit for how