The Human Brain and Computing Machines of the Future

In June 2015, the White House Office of Science and Technology Policy issued a “grand challenge” to the scientific community that addressed three national priorities: the National Nanotechnology Initiative, the National Strategic Computing Initiative, and the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative: “create a new type of computer that can proactively interpret and learn from data, solve unfamiliar problems using what it has learned, and operate with the energy efficiency of the human brain.” While conventional digital computing has been the engine of the global information technology revolution, it falls far short of both the brain's sensing and problem-solving abilities, not to mention its low-power consumption. While the human brain consumes less power than an electric light bulb, its capacity for recognition, decision-making, and complex problem-solving often far exceeds that of vast arrays of computing machines that are consuming many megawatts of power. However, recent progress in developing novel, low-power methods of sensing and computation, including neuromorphic, magneto-electronic, and analog systems, combined with dramatic advances in neuroscience and cognitive sciences, makes it seem that this ambitious challenge may be within reach. The session assembles thought leaders in computing from government, academia, and industry to critically examine these opportunities.