Teaching computers to learn the way we do is widely considered an important step toward better artificial intelligence, but it's hard to achieve without a good understanding of how we think. With that premise in mind, a new $12 million effort launched Wednesday with aims to "reverse-engineer" the human brain. Led by Tai Sing Lee, a professor in Carnegie Mellon University's Computer Science Department and the Center for the Neural Basis of Cognition (CNBC), the five-year project seeks to unlock the secrets of neural circuitry and the brain's learning methods. Ultimately, the goal is to improve neural networks, the computational models often used for AI in applications including self-driving cars, automated trading, and facial and speech recognition. "Today's neural nets use algorithms that were essentially developed in the early 1980s," Lee said.
Jan-18-2017, 11:49:26 GMT