Brain-derived neuromorphic computing with 3D electronic-photonic integrated circuits
S. J. Ben Yoo · 2023
Reverse engineering the brain has been our dream and a grand challenge for many decades. The human brain has immense learning capabilities at extreme energy efficiencies and scale, which no artificial system has been able to match. We propose that utilization of a brain-derived—rather than a brain-inspired—architecture will lead to a paradigm shift, enabling the development of intelligent agents that can work in tandem with humans on complex tasks in noisy, unpredictable environments. Key to this paradigm shift will be the integration of hardware that emulates the processing characteristics of the brain with design principles based on fundamental aspects of neural plasticity and circuit design in the human brain. To achieve this grand challenge, we pursue a new neuromorphic computing paradigm enabled by modular integration of energy-efficient 3D-electronic-photonic-ICs (3D EPICs) with attojoule nanophotonic neurons in photonic neural networks.