Joint Future of Neuroscience and Artificial Intelligence

Over three days this week, NYU Shanghai hosted a stream of high profile speaking events featuring prominent intellectuals from neuroscience and artificial intelligence (AI), offering hundreds of science enthusiasts an opportunity to embrace advancing future technologies.

On Wednesday, Richard W. Tsien, NYU Druckenmiller Professor of Neuroscience, kicked off the discussion by presenting his lifelong research on Synapses, Circuits and Behavior at ECNU, as part of the neuroscience lecture series organized by The NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai.

“Huge academic interest now lies in understanding how the brain performs computations and decision,” said Prof. Tsien. “The brain is a highly evolved structure that has some powerful and efficient tricks for computation--such insights might be valuable to further development of AI.”

However, he affirmed that AI surpasses the brain in many aspects as it is not bound by the physical properties of neurons, which are in some ways inferior to that of silicon in microprocessors.

On Thursday, Prof. Tsien further elaborated on the future integration of  the two realms at the conference on The Joint Future of Neuroscience & AI, together with fellow leading scientists including Prof. J. Anthony Movshon from NYU, Prof. Larry Abbott from Columbia University, as well as NYU Prof. Yann LeCun who is also the Director of AI Research at Facebook, as well as NYU Shanghai’s Associate Vice Chancellor for Research, NYU Prof. Xiao-Jing Wang. 

Co-sponsored by NYU Shanghai and ECNU, the conference underscored multiple issues at the intersection of fields such as computational neuroscience and machine learning to a full auditorium of faculty and students.

“This forum provides an excellent opportunity for leaders in neuroscience and AI to communicate and explore cross-disciplinary approaches in developing new technologies. Research and education in this field represent a strength and priority of NYU Shanghai,” Prof. Wang said.

On Friday, Prof. LeCun concluded the week with a public talk on Predictive Learning and the Future of AI, organized by NYU Shanghai’s Center for Data Science and Analytics. He argued that the ability of machines to learn predictive models of the world is a key component to enabling significant progress in AI.

“The challenge of the next several years is to let machines learn from raw, unlabeled data, such as video or text. This is known as predictive learning. However, the main technical difficulty is that the world is only partially predictable,” he said. 

Hosting the talk, Prof. Keith Ross, Dean of Engineering and Computer Science at NYU Shanghai and co-director of the Center, said AI has made spectacular progress in object recognition, face recognition, speech recognition, and natural language translation over the past four years, primarily due to new advances in machine learning.

“Over the next four years, the trend will continue with advances in autonomous cars, healthcare, and digital personal assistants,” he said. 

Capping the Friday morning session, Prof. Zhang Zheng moderated a panel discussion in which Prof. Fan Jianqing from Fudan University & Princeton University, Prof. Ma Yi, from ShanghaiTech University, Shen Xiaowei, CTO of IBM Greater China Group, Director of IBM Research-China, as well as Prof. Xiao-Jing Wang joined LeCun, and fielded questions from the audience.