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What have we learned about artificial intelligence from studying the brain?

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Abstract

Neuroscience and artificial intelligence (AI) share a long, intertwined history. It has been argued that discoveries in neuroscience were (and continue to be) instrumental in driving the development of new AI technology. Scrutinizing these historical claims yields a more nuanced story, where AI researchers were loosely inspired by the brain, but ideas flowed mostly in the other direction.

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Data Availability

No datasets were generated or analysed during the current study.

Notes

  1. In Gershman (2021), it is also argued that there is no “innocent algorithm” for analyzing data without making certain assumptions.

  2. Some recent work in computer vision has begun to incorporate eccentricity dependence into convnets (Chen et al. 2017; Deza and Konkle 2020).

  3. When the Kempner Institute was created at Harvard, I suggested to the directors that if they really wanted to advance biologically inspired AI, they should restrict the compute budget to the wattage of a light bulb, which is all the brain needs. My suggestion was not followed.

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Acknowledgements

I’m grateful to Andy Barto, Terry Sejnowski, Tony Zador, Ken Miller, Brad Aimone, Momchil Tomov, Venki Murthy, Chris Summerfield, Gabriel Kreiman, Chris Bates, and Jay Hennig for comments on an earlier draft. This work was supported by the Center for Brains, Minds, and Machines (CBMM), funded by NSF STC award CCF1231216.

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Authors and Affiliations

  1. Department of Psychology and Center for Brain Science, Harvard University, Cambridge, USA, Cambridge, USA

    Samuel J. Gershman

  2. Center for Brains, Minds, and Machines,MIT, Cambridge, USA

    Samuel J. Gershman

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  1. Samuel J. Gershman
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S.G. wrote the manuscript.

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Correspondence to Samuel J. Gershman.

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Communicated by Benjamin Lindner.

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Gershman, S.J. What have we learned about artificial intelligence from studying the brain?. Biol Cybern (2024). https://doi.org/10.1007/s00422-024-00983-2

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