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Can lessons from infants solve the problems of data-greedy AI?

Words and images experienced by an infant wearing sensors during their daily life have led to efficient machine learning, pointing to the power of multimodal training signals and to the potentially exploitable statistics of real-life experience.
  1. Linda B. Smith

    1. Linda B. Smith is in the Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana 47405, USA.

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Current advances in artificial intelligence (AI) seem to be transforming science into science fiction, as large-data machine-learning models approach and, in some ways, surpass human abilities. But such models are trained on vast amounts of data. Writing in Science, Vong et al.1 have thrown down a challenge on behalf of humans by using 61 hours of one infant’s real-life experiences to demonstrate the efficiency of a multimodal learning model.

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Nature 628, 45-46 (2024)

doi: https://doi.org/10.1038/d41586-024-00713-5

References

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Competing Interests

The author declares no competing interests.

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