Recent, dramatic advances in machine learning and AI, such as large language models and deep and recurrent neural networks, have opened the door to powerful new interdisciplinary collaborations between neuroscience and computer science, aimed at unlocking the basis of biological and artificial intelligence. Despite the power of current AI models, we are finding they are not as powerful as the brain in terms of efficiency and learning; neuroscience can inform and inspire better AI architecture. Researchers at PNI are currently working at the intersection of neuroscience and AI to gain new insights into neural data, generate new hypotheses for understanding the brain and behavior, and develop the next-generation AI architectures inspired by the brain.


Upcoming Event

Princeton Symposium on Biological & Artificial Intelligence

The Symposium will bring together researchers at Princeton and the broader New York area, who work on problems cutting across the boundaries of biological and artificial intelligent systems.

PNI, Washington Road, Princeton, NJ

Associated Programs at Princeton

Princeton Language and Intelligence (PLI)

Princeton University has launched a new multidisciplinary initiative, Princeton Language and Intelligence (PLI), that seeks to develop fundamental understanding of large AI models; investigate their application to research and education across academic disciplines (including science, humanities, social sciences, and engineering); and study societal and ethical issues arising from AI as well as development of methods to avert any of its harms. The exponential growth of language and intelligence in machines may revolutionize our research and teaching, as well as launch new disciplines. PLI looks forward to engaging with all of you as we enter this new frontier.

Computer Science at Princeton

Princeton has been at the forefront of computing since Alan Turing, Alonzo Church and John von Neumann were among its residents. The CS department is home to about 60 faculty members, with strong groups in theory, networks/systems, vision/graphics, architecture/compilers, programming languages, security/policy, machine learning, natural language processing, human-computer interaction, robotics, and computational biology.