Excited to announce that @Azaliamirh and I are launching @RicursiveAI, a frontier AI lab creating a recursive self-improving loop between AI and the hardware that fuels it. Today, chip design takes 2-3 years and requires thousands of human experts. We will reduce that to weeks. This will be incredibly hard. For context: Go has a search space of 10^360. A simplified version of chip placement—only one part of the design process—has a search space of 10^9000. But we are the right team to solve it. We co-founded the Machine Learning for Systems team at Google Brain. There, we built AlphaChip—an RL agent for chip placement. AlphaChip has been used to design four generations of TPUs, data center CPUs, autonomous vehicle chips, and mobile phone chips. These chips are running in data centers and devices all over the world. Our immediate goal is to dramatically accelerate chip design. Next, we plan to design chips end-to-end given an ML workload, unlocking a Cambrian explosion of custom silicon. Finally, we will close the recursive loop. We will build our own chips, train our own models, and co-evolve them on the path to superintelligence. AI designs better chips 🔄chips train better AI We sat down with @WSJ’s @Berber_Jin1 to discuss Ricursive: wsj.com/tech/this-ai-startup…