Conference explores the collision between neuroscience and machine learning

In a world inundated with data, we rely more and more on machines to help us understand it all. However, despite advances in machine learning, the pattern-recognition and learning abilities of artificial brains still pales in comparison to even the simplest mammalian brains. Today’s computer scientists are turning to neuroscientists and the human brain for inspiration to design computer systems that can interpret, analyze, and learn information as successfully as humans. But do artificial intelligence and neuroscience really need each other? Is there a better way to model machine intelligence? Is the relationship reciprocal? Are simple, artificial brains changing our understanding of complex, organic ones? This year’s Institute for Applied Computational Science (IACS) symposium on the Future of Computation in Science and Engineering will explore these issues and others that…


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