Can a New Theory of the Neocortex Lead to Truly Intelligent Mach. Hierarchical temporal memory. Hierarchical temporal memory (HTM) is an online machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex. HTM is a biomimetic model based on the memory-prediction theory of brain function described by Jeff Hawkins in his book On Intelligence.
HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world. Jeff Hawkins states that HTM does not present any new idea or theory, but combines existing ideas to mimic the neocortex with a simple design that provides a large range of capabilities. HTM combines and extends approaches used in Bayesian networks, spatial and temporal clustering algorithms, while using a tree-shaped hierarchy of nodes that is common in neural networks.
HTM structure and algorithms[edit] An example of HTM hierarchy used for image recognition Bayesian networks[edit] Numenta - numenta.com. Jeff Hawkins. Hawkins also serves on the Advisory Board of the Secular Coalition for America and offers advice to the coalition on the acceptance and inclusion of nontheism in American life.[3] Early life and career[edit] Hawkins grew up with an inventive family on the north shore of Long Island. They developed a floating air cushion platform that was used for waterfront concerts. He attended Cornell University, where he received a bachelor's degree in electrical engineering in 1979. Grok[edit] They have been using biological information about the structure of the neocortex to guide the development of their theory on how the brain works. Numenta, Inc., was founded in 2005 to be a catalyst in the emerging field of machine intelligence.
Neuroscience[edit] In 2002, after two decades of finding little interest from neuroscience institutions, Hawkins founded the Redwood Neuroscience Institute in Menlo Park, California. References[edit] Books[edit] Jeff Hawkins on how brain science will change computing. Jeff Hawkins on Artificial Intelligence - Part 1/5. Redwood Center for Theoretical Neuroscience. On Intelligence: Jeff Hawkins, Sandra Blakeslee. Hierarchical Temporal Memory. We've completed a functional (and much better) version of our .NET-based Hierarchical Temporal Memory (HTM) engines (great job Rob). We're also still working on an HTM based robotic behavioral framework (and our 1st quarter goal -- yikes - we're late). Also, we are NOT using Numenta's recently released run-time and/or code... since we're professional .NET consultants/developers, we decided to author our own implementation from initial prototypes authored over the summer of 2006 during an infamous sabbatical -- please don't ask about the "Hammer" stories.
I've been feeling that the team has not been in synch in terms of HTM concepts, theory and implementation. We decided to spend the last couple of meetings purely focused on discussions concerning HTMs. This has resulted in a new HTM based initiative (in line with our charter) that utilizes HTMs as the basis of chess playing game engine and in the team rededicating itself to gain deeper insights into HTM-based networks and AIs.