The brain and how it learns may be among the most complicated puzzles in the quickly advancing field of neuroscience. But Harvard is trying to unravel its mystery.
The Ariadne Project, led by David Cox, an assistant professor of molecular and cellular biology and computer science at Harvard, mobilized a multi-university team of experts in neuroscience, physics, machine learning, and high-performance computing to explore the possibility of creating an artificial brain by reverse-engineering the brain of a rat while it learns. The aim is to build computer algorithms that replicate the way human brains perceive information and learn.
“This is where the field of computer science and neuroscience are not only exploding, but are merging on a collision course that is allowing us to explore the way we conventionally think of understanding,” Cox told 80 attendees at the Harvard Ed Portal’s Faculty Speaker Series lecture “Toward an Artificial Brain” in Allston.
“Walking across a room and not falling over is hard for a computer [robot], but easy for us. Systems don’t quite understand the way we understand,” he said. “Let’s go back to the brain and find out what we’re missing.”
“Let’s go back to the brain and find out what we’re missing.”
Kenneth Blum, executive director of the Center for Brain Science (CBS) said in opening remarks that recent advances in artificial intelligence may indicate that intelligent machines are just around the corner. But how that might happen remains a question.
“You have probably read about artificial intelligence in the news, seen it in movies, used Siri or Alexa or one of the other voice assistants … or know that soon in most cars to be sold there will be a little chip that will gather data to assist with self-driving cars,” he said.