This week sees the launch of the first major ‘biological foundation model’ based on an exciting new type of AI architecture, the state space model. The Arc Institute in collaboration with TogetherAI released Evo, a notable step forward step in the new field of ‘life engineering’. Evo is trained on DNA, RNA and protein data, the building blocks of life, can process long inputs (like Google’s Gemini 1.5) and can generate genome scale outputs. The human genome is >3bn nucleotides long, so there is some way to go before we print out modified humans 🙂 but if we use the analogy of software development, this breakthrough enables engineers to operate on full ‘apps’ instead of just snippets of code and could dramatically reduce the time needed to design, test and fabricate new biological components. From cell factories, to drugs or vaccines, foods and fuels, biology is the latest AI ‘modality’.
Takeaway: Look out for AI progress crossing over from the digital to the physical both through robotics advancements from companies like Figure AI (see roundup) and in the field of synthetic biology through Evo, Bioptimus and others. Time to start considering AI’s digital-physical opportunities (and also threats… companies will need an integrated strategy for cyber-physical-bio security). Also keep an eye on for state space models. Gemini, GPTs and Claude are all ‘transformers’, but the state space architecture offers greater efficiency, longer inputs and crucially has long-term memory. Whilst they’re not comparable with transformers on language yet, their time may be imminent.