Читать книгу The Innovation Ultimatum - Steve Brown - Страница 49

Neuromorphic computers are inspired by the way brains work. Today's neural network designs are based on an understanding of neuroscience from the 1960s. Half a century later, we finally have the computing horsepower needed to implement these archaic machine models. The next time you ask Google Assistant or Alexa to play some Beatles music, remember that the foundation of the AI you're using was designed at the time when the Stones and The Beatles were first vying to be top of the charts. Neuromorphic computers, also referred to as cognitive computers, are based on a much more recent understanding of how the brain operates. Nodes are hyperconnected, their connections can change over time (in the same way that the human brain exhibits plasticity), and there is no separation between memory and processing functions.

Major research projects—the Human Brain Project in the European Union and the BRAIN (Brain Research through Advanced Innovative Neurotechnologies) initiative in the United States—seek to advance our understanding of the human brain, mapping and understanding brain function. These efforts, and others like them, push the boundaries of our understanding and offer new frameworks for the design of future neuromorphic computers. New computer chips, inspired by neuromorphic insights, may accelerate AI functions, reduced power consumption for AI tasks, and enable exciting new capabilities.

Whether it's capsule networks, neuromorphic computing, or common sense and causal AI, there are plenty of avenues of research that should fuel future advances in AI in the coming decades.