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arXiv:2210.08340 (cs)
[Submitted on 15 Oct 2022 (v1), last revised 22 Feb 2023 (this version, v3)]

Title:Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Authors: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 Koerding, 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
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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.
Comments: White paper, 10 pages + 8 pages of references, 1 figures
Subjects: Artificial Intelligence (cs.AI); Neurons and Cognition (q-bio.NC)
Cite as: arXiv:2210.08340 [cs.AI]
  (or arXiv:2210.08340v3 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2210.08340

Submission history

From: Sean Escola [view email]
[v1] Sat, 15 Oct 2022 17:18:37 UTC (274 KB)
[v2] Fri, 21 Oct 2022 03:11:55 UTC (265 KB)
[v3] Wed, 22 Feb 2023 20:05:10 UTC (375 KB)
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