Numenta is creating a new type of computing technology modeled on the structure and operation of the neocortex. The technology is called Hierarchical Temporal Memory, or HTM, and is applicable to a broad class of problems from machine vision, to fraud detection, to semantic analysis of text. HTM is based on a theory of neocortex first described in the book On Intelligence by Numenta co-founder Jeff Hawkins, Numenta is a technology tools and platform provider rather than an application developer. We work with developers and partners to configure and adapt HTM systems to solve a wide range of problems. HTM technology has the potential to solve many difficult problems in machine learning, inference, and prediction. Some of the application areas we are exploring with our customers include recognizing objects in images, recognizing behaviours in videos, identifying the gender of a speaker, predicting traffic patterns, doing optical character recognition on messy text, evaluating medical images, and predicting click through patterns on the web. The world is becoming awash with data of all types, whether numeric, video, text, images or audio, making it challenging for humans to sort through it and find whats important. HTM technology offers the promise of making sense of all that data. An HTM system is not programmed in the traditional sense; instead it is trained. Sensory data is applied to the bottom of the hierarchy of an HTM system and the HTM automatically discovers the ...
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