Brain-like computing is the device

model or methodology which emulates

simulates or imitates the structure of the brain's neural system and its information processing mechanism

with the goal to produce the brain-like computer and brain-level intelligence. This report reviews the progress and challenges of brain-like computing in the last two decades

in the world and in China

including related research in the brain science

the neuromorphic devices

neural network chips

brain inspired computing models and applications. The future development trend is also prospected. Different from the classical artificial intelligence methodologies

including the symbolism

connectionism

behaviourism and statisticsism

brain-like computing follows the imitationism: imitate the brain at structure level (non von Neumann architecture)

approximate the brain at device level (neuromorphic devices emulating the biological neurons and synapses)

and surpass the brain at intelligent level (mainly by autonomous learning and training rather than manual programming). At present

there is still a big gap between the practical application of brain computing and the practical application of the industry

which provides an important research direction and opportunity for the researchers.