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Machine learning + neuroscience = biologically feasible computing | Benjamin Migliori | TEDxSanDiego

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Published on Jan 3, 2018

Whether you're a human, an animal, or a machine, decisions can't be made without perception, which is how we come to understand the world around us. Machine learning will allow us to create a future in which artificial systems extend and augment our abilities, to help us create and imagine. To do that, we need to create machines that make decisions based on instinct, context, and minimal training. Combining neuroscience and machine learning, we can enter the world of biologically feasible computing. Companies are building computers that can mimic and simulate neurons in biophysical detail. The goal is to create algorithms that compute in biologically feasible ways. Benjamin Migliori is an interdisciplinary physicist-slash-neuroscientist who focuses on biologically inspired systems – that is, using our understanding of computational neuroscience to help machines perceive the world, and using our understanding of machines to help us understand the brain. He is currently contributing this unique outlook to challenges of national defense at the Space and Naval Warfare Systems Center Pacific as a principal investigator in machine learning and computational neuroscience. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx

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