Numenta Researchers Discover How the Brain Learns Sequences, a Key Ingredient of Intelligent Systems

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WIRE)--How do our brains learn and understand the world? That question is of paramount importance to both neuroscientists and technologists who want to build intelligent machines. It has been understood for over a hundred years that the inputs and outputs of the brain are constantly changing sequences of patterns and therefore learning and recalling sequences must be a fundamental operation of neurons. Numerous proposals have been made for how neural networks might learn sequences. However, these proposals did not match the anatomy and function observed in the brain.


Numenta Researchers Discover How The Brain Learns Sequences, A Key to Intelligent Systems

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Numenta's theory of how the brain learns and understands sequences of patterns may be an essential component for creating intelligent machines REDWOOD CITY, CA –April 12, 2016-- How do our brains learn and understand the world? That question is of paramount importance to both neuroscientists and technologists who want to build intelligent machines. It has been understood for over a hundred years that the inputs and outputs of the brain are constantly changing sequences of patterns and therefore learning and recalling sequences must be a fundamental operation of neurons. Numerous proposals have been made for how neural networks might learn sequences. However, these proposals did not match the anatomy and function observed in the brain.


Numenta brings brain theory to machine learning

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REDWOOD CITY, CA - November 14, 2016-- Numerous proposals have been offered for how intelligent machines might learn sequences of patterns, which is believed to be an essential component of any intelligent system. Researchers at Numenta Inc. have published a new study, "Continuous Online Sequence Learning with an Unsupervised Neural Network Model," which compares their biologically-derived HTM sequence memory to traditional machine learning algorithms. The paper has been published in MIT Press Journal's Neural Computation 28, 2474-2504 (2016). You can read and download the paper here. Authored by Numenta researchers Yuwei Cui, Subutai Ahmad, and Jeff Hawkins, the new paper serves as a companion piece to Numenta's breakthrough research offered in "Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex," which appeared in Frontiers in Neural Circuits, in March 2016.


Out in the Open: Palm Pilot Inventor Wants to Open Source the Human Brain

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Everyone wants to make computers work more like the human brain these days. There are more research projects than ever trying to unlock the mysteries of intelligence, ranging from government projects like the White House's brain mapping initiative to corporate projects like Google's ambitious artificial intelligence program to academic research like Stanford's attempts to help computers understand human languages. But computer scientist and entrepreneur Jeff Hawkins, who is best known as the inventor of the Palm Pilot, already has developed a unified theory of the brain's inner workings and created algorithms for applying the theory to computer science. What's more, he has open-sourced his work so anyone can use the algorithms and software to build their own machine learning systems -- for free. Hawkins was the co-founder of Palm and Handspring, which were behind several widely used mobile devices in the late 1990s, but artificial intelligence and neuroscience are his real passions.


Numenta brings brain theory to machine learning - Scienmag

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REDWOOD CITY, CA – November 14, 2016– Numerous proposals have been offered for how intelligent machines might learn sequences of patterns, which is believed to be an essential component of any intelligent system. Researchers at Numenta Inc. have published a new study, "Continuous Online Sequence Learning with an Unsupervised Neural Network Model," which compares their biologically-derived HTM sequence memory to traditional machine learning algorithms. The paper has been published in MIT Press Journal's Neural Computation 28, 2474-2504 (2016). You can read and download the paper here. Authored by Numenta researchers Yuwei Cui, Subutai Ahmad, and Jeff Hawkins, the new paper serves as a companion piece to Numenta's breakthrough research offered in "Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex," which appeared in Frontiers in Neural Circuits, in March 2016.