Nature Communications (Mar 2023)
Catalyzing next-generation Artificial Intelligence through NeuroAI
- Anthony Zador,
- Sean Escola,
- Blake Richards,
- Bence Ölveczky,
- Yoshua Bengio,
- Kwabena Boahen,
- Matthew Botvinick,
- Dmitri Chklovskii,
- Anne Churchland,
- Claudia Clopath,
- James DiCarlo,
- Surya Ganguli,
- Jeff Hawkins,
- Konrad Körding,
- Alexei Koulakov,
- Yann LeCun,
- Timothy Lillicrap,
- Adam Marblestone,
- Bruno Olshausen,
- Alexandre Pouget,
- Cristina Savin,
- Terrence Sejnowski,
- Eero Simoncelli,
- Sara Solla,
- David Sussillo,
- Andreas S. Tolias,
- Doris Tsao
Affiliations
- Anthony Zador
- Cold Spring Harbor Laboratory
- Sean Escola
- Department of Psychiatry, Columbia University
- Blake Richards
- Mila
- Bence Ölveczky
- Department of Organismic and Evolutionary Biology, Harvard University
- Yoshua Bengio
- Mila
- Kwabena Boahen
- Department of Bioengineering, Stanford University
- Matthew Botvinick
- Google Deepmind
- Dmitri Chklovskii
- Flatiron Institute, Simons Foundation
- Anne Churchland
- Department of Neurobiology, University of California Los Angeles
- Claudia Clopath
- Department of Bioengineering, Imperial College London
- James DiCarlo
- Department of Brain and Cognitive Sciences, MIT
- Surya Ganguli
- Department of Applied Physics, Stanford University
- Jeff Hawkins
- Numenta
- Konrad Körding
- Department of Neuroscience, University of Pennsylvania
- Alexei Koulakov
- Cold Spring Harbor Laboratory
- Yann LeCun
- Meta
- Timothy Lillicrap
- Google Deepmind
- Adam Marblestone
- Media Lab, MIT
- Bruno Olshausen
- Helen Wills Neuroscience Institute, University of California Berkeley
- Alexandre Pouget
- Department of Basic Neurosciences, University of Geneva
- Cristina Savin
- Center for Neural Science, NYU
- Terrence Sejnowski
- Salk Institute for Biological Studies
- Eero Simoncelli
- Departments of Neural Science, Mathematics, and Psychology, NYU
- Sara Solla
- Department of Physiology, Northwestern University
- David Sussillo
- Meta
- Andreas S. Tolias
- Department of Neuroscience, Baylor College of Medicine
- Doris Tsao
- Helen Wills Neuroscience Institute, University of California Berkeley
- DOI
- https://doi.org/10.1038/s41467-023-37180-x
- Journal volume & issue
-
Vol. 14,
no. 1
pp. 1 – 7
Abstract
Abstract Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which challenges AI animal models to interact with the sensorimotor world at skill levels akin to their living counterparts. The embodied Turing test shifts the focus from those capabilities like game playing and language that are especially well-developed or uniquely human to those capabilities – inherited from over 500 million years of evolution – that are shared with all animals. Building models that can pass the embodied Turing test will provide a roadmap for the next generation of AI.