Omnii-1 is a huge milestone for @RadicalNumerics. Building it required advancing architectures, pre-training, post-training and inference to make new biological applications possible. Pre-training meant tokenizing and blending continuous and discrete biological modalities. Post-training adapted that foundation to different applications. At inference, we’re exploring algorithms for reasoning across biological modalities and allocating test-time compute across selective generation and conditioning steps. Making these models train and run at scale meant pushing the underlying numerics and systems alongside the modeling. The frontier of biological AI runs all the way down the stack. We have a cracked team. Really proud of what we’ve built together.