What insights can the Kidd Lab provide for creators of neural networks?

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The discussion highlights insights from an interview with AI experts featured in VentureBeat, focusing on predictions for the future of AI in 2020. Celeste Kidd, a developmental psychologist at UC Berkeley, emphasizes the parallels between child learning and training neural networks. Her research at Kidd Lab aims to enhance understanding of learning processes in children, which can inform the development of AI models. The conversation underscores the importance of interdisciplinary approaches in advancing AI technology, particularly through insights gained from developmental psychology.
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AI is no longer poised to change the world someday; it’s changing the world now. As we begin a new year and decade, VentureBeat turned to some of the keenest minds in AI to revisit progress made in 2019 and look ahead to how machine learning will mature in 2020.

We spoke with PyTorch creator Soumith Chintala, University of California professor Celeste Kidd, Google AI chief Jeff Dean, Nvidia director of machine learning research Anima Anandkumar, and IBM Research director Dario Gil.
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Pretty appropriate how Dr. Kidd named the lab that she founded at UC Berkeley... :smile:

Celeste Kidd

Developmental psychologist at the University of California, BerkeleyCeleste Kidd is director of Kidd Lab at the University of California, Berkeley, where she and her team explore how kids learn. Their insights can help the creators of neural networks who are attempting to train models in ways not too dissimilar to raising a child.
 
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