Catalyzing next-generation Artificial Intelligence through NeuroAI

Zador, Anthony, Escola, Sean, Richards, Blake, Ölveczky, Bence, Bengio, Yoshua, Boahen, Kwabena, Botvinick, Matthew, Chklovskii, Dmitri, Churchland, Anne, Clopath, Claudia, DiCarlo, James, Ganguli, Surya, Hawkins, Jeff, Körding, Konrad, Koulakov, Alexei, LeCun, Yann, Lillicrap, Timothy, Marblestone, Adam, Olshausen, Bruno, Pouget, Alexandre, Savin, Cristina, Sejnowski, Terrence, Simoncelli, Eero, Solla, Sara, Sussillo, David, Tolias, Andreas S, Tsao, Doris (March 2023) Catalyzing next-generation Artificial Intelligence through NeuroAI. Nature Communications, 14 (1). p. 1597. ISSN 2041-1723

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URL: https://www.ncbi.nlm.nih.gov/pubmed/36949048
DOI: 10.1038/s41467-023-37180-x

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.

Item Type: Paper
Subjects: neurobiology
neurobiology > neuroscience
CSHL Authors:
Communities: CSHL labs > Koulakov lab
CSHL labs > Zador lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 22 March 2023
Date Deposited: 29 Sep 2023 15:46
Last Modified: 11 Jan 2024 15:03
PMCID: PMC10033876
Related URLs:
URI: https://repository.cshl.edu/id/eprint/41061

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