Biological Black Box integrates biological neurons with artificial neural networks to develop a living computer. This is used to train AI models 1000x more efficiently than silicon.
BBB needed an ML leader who could own the full lifecycle from research to production. The role required deep computer vision expertise and proven experience shipping models under real-world constraints, including on-device and low-latency environments. They were looking for someone with strong judgment around trade-offs between speed, memory, accuracy, and cost, and a consistently high bar for production-ready ML.
Placed a Head of ML with deep computer vision expertise and a track record of shipping low-latency, compute-constrained models, capable of owning the full lifecycle from research through real-world deployment.
Tai-Peng combined computer vision expertise with experience in both large-scale and early-stage environments, giving him a unique sense of how to build production-ready systems. He led teams while staying close to the technical work, especially in compute-aware model optimization, thinking from an architectural and hardware perspective. The blend of practical engineering and leadership sets him apart.
