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

doi:10.1038/s41467-023-37180-x

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 PougetCristina Savin, Terrence Sejnowski, Eero Simoncelli, Sara Solla, David Sussillo, Andreas S. Tolias, Doris Tsao

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Article number	1597
Journal	Nature communications
Volume	14
Issue number	1
DOIs	https://doi.org/10.1038/s41467-023-37180-x
State	Published - Dec 2023

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

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10.1038/s41467-023-37180-x

Cite this

Zador, A., Escola, S., Richards, B., Ölveczky, B., Bengio, Y., Boahen, K., Botvinick, M., Chklovskii, D., Churchland, A., Clopath, C., DiCarlo, J., Ganguli, S., Hawkins, J., Körding, K., Koulakov, A., LeCun, Y., Lillicrap, T., Marblestone, A., Olshausen, B., ... Tsao, D. (2023). Catalyzing next-generation Artificial Intelligence through NeuroAI. Nature communications, 14(1), Article 1597. https://doi.org/10.1038/s41467-023-37180-x

Zador, A, Escola, S, Richards, B, Ölveczky, B, Bengio, Y, Boahen, K, Botvinick, M, Chklovskii, D, Churchland, A, Clopath, C, DiCarlo, J, Ganguli, S, Hawkins, J, Körding, K, Koulakov, A, LeCun, Y, Lillicrap, T, Marblestone, A, Olshausen, B, Pouget, A, Savin, C, Sejnowski, T, Simoncelli, E, Solla, S, Sussillo, D, Tolias, AS & Tsao, D 2023, 'Catalyzing next-generation Artificial Intelligence through NeuroAI', Nature communications, vol. 14, no. 1, 1597. https://doi.org/10.1038/s41467-023-37180-x

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Catalyzing next-generation Artificial Intelligence through NeuroAI

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