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Tuesday, July 16, 2019

Intel's Neuromorphic Chips

Meaning chips that are closer in structure to neural networks, which themselves are just considerable simplifications of networks of biological neurons.   The result is being able to do such neural computation, key to deep learning, much faster.   No quantum computing here.   Below what Intel Corp writes about this, and then a piece by Technology Review.

Intel's Neuromorphic Computing

The emergent capabilities in artificial intelligence being driven by Intel Labs have more in common with human cognition than with conventional computer logic.

Neuromorphic computing research emulates the neural structure of the human brain.

The Loihi research chip includes 130,000 neurons optimized for spiking neural networks.

Intel Labs is making Loihi-based systems available to the global research community.

Probabilistic computing addresses the fundamental uncertainty and noise of natural data.

Collaborations on next-generation AI extend to worldwide industry and academic researchers.

What Is Neuromorphic Computing
The first generation of AI was rules-based and emulated classical logic to draw reasoned conclusions within a specific, narrowly defined problem domain. It was well suited to monitoring processes and improving efficiency, for example. The second, current generation is largely concerned with sensing and perception, such as using deep-learning networks to analyze the contents of a video frame.

A coming next generation will extend AI into areas that correspond to human cognition, such as interpretation and autonomous adaptation. This is critical to overcoming the so-called “brittleness” of AI solutions based on neural network training and inference, which depend on literal, deterministic views of events that lack context and commonsense understanding. Next-generation AI must be able to address novel situations and abstraction to automate ordinary human activities.

Intel Labs is driving computer-science research that contributes to this third generation of AI. Key focus areas include neuromorphic computing, which is concerned with emulating the neural structure and operation of the human brain, as well as probabilistic computing, which creates algorithmic approaches to dealing with the uncertainty, ambiguity, and contradiction in the natural world.  .... " 

Also from Technology Review:
Intel’s new AI chips can crunch data 1,000 times faster than normal ones  ......  "

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