Hierarchical Temporal Memory (HTM) is a learning theory proposed by Jeff Hawkins and developed by Numenta. It aims to reflect the functioning of the human neocortex, reminiscent of the enthusiasm of early AI, and this time may succeed due to the advances in neuroscience research. Every day, the human neocortex learns the structure of the world from temporal data flowing in through our sensory organs and makes numerous predictions every second, directly influencing our behaviour — whether its to catch a ball thrown at us or to plan what time to leave in the morning to reach work on time…

Srishti Mishra

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