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Learning over a lifetime

Artificial-intelligence researchers turn to lifelong learning in the hopes of making machine intelligence more adaptable.
  1. Neil Savage

    1. Neil Savage is a freelance writer in Lowell, Massachusetts.

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An animated illustration showing a walking robot facing unknown obstacles and learning how to overcome them.

Illustration by David Parkins

Bing Liu was road testing a self-driving car, when suddenly something went wrong. The vehicle had been operating smoothly until it reached a T-junction and refused to move. Liu and the car’s other occupants were baffled. The road they were on was deserted, with no pedestrians or other cars in sight. “We looked around, we noticed nothing in the front, or in the back. I mean, there was nothing,” says Liu, a computer scientist at the University of Illinois Chicago.

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doi: https://doi.org/10.1038/d41586-022-01962-y

This article is part of Nature Outlook: Robotics and artificial intelligence, an editorially independent supplement produced with the financial support of third parties. About this content.

Updates & Corrections

  • Correction 01 September 2022: An earlier version of this article incorrectly described Bing Liu's field of expertise.

References

  1. Patterson, D. et al. Preprint at https://arxiv.org/abs/2104.10350 (2021).

  2. Mandivarapu, J. K., Camp, B. & Estrada, R. Front. Artif. Intell. 3, 19 (2020).

    Article  PubMed  Google Scholar 

  3. Camp, B., Mandivarapu, J. K. & Estrada, R. Preprint at https://arxiv.org/abs/2011.07035 (2020).

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