Abstract : Digital computing is approaching its fundamental limits just as compute-intensive workloads like machine learning are taking off. To address this, we are building a new kind of computer–an analog optical computer–to accelerate AI inference and hard optimization workloads. The computer has the potential to improve the efficiency and sustainability of these workloads by around 100x by stepping away from several fundamentally limiting aspects of general-purpose digital computing. It leverages chip-scale optical and electronic technologies from the consumer space that are low cost and scalable. In this talk, I will describe two generations of this computer that we have built, outline our roadmap for scaling, and discuss the importance of hardware-software co-design for such emerging computers and their potential for accelerating real-world problems in the post-Moore Law’s era. Speaker(s): Dr. Hitesh Ballani, Bldg: McConnell Engineering building, , Room MC603, 6th floor, 817 Sherbrooke St W, , Montreal, Quebec, Canada, H3A 0C3, Virtual: https://events.vtools.ieee.org/m/430520