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What Does “Neuromorphic” Mean Today?

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What does the word “neuromorphic” mean today? The term is broadly used to mean technologies that are inspired by biology, specifically brains, but with the rise of artificial intelligence, technologies claiming to be “brain–inspired” are abundant.

In this EE Times Special Project, we consider exactly what neuromorphic means today, both explicitly and by exploring trends and new ideas in state–of–the–art neuromorphic systems, including sensors and computing.

To start, EE Times’ Nitin Dahad interviewed Caltech professor Carver Mead, the originator of neuromorphic technologies as we know them, about exactly how closely we should be copying the neuron in silicon, the potential of event–based sensing, and whether analog computing can help us achieve the power efficiency of biological brains. Read more in “An Interview with Carver Mead“.

Our next article, “Inspiration or Imitation: How Closely Should We Copy Biological Systems?”, recounts a recent expert panel discussion on neuromorphic technologies from the Embedded Vision Summit, moderated by EE Times’ Sally Ward–Foxton. The experts discussed how closely we could and should be copying biology, whether that’s human or animal brains or the retina.

Computer vision is one of the first applications to adopt neuromorphic technology in the form of event–based cameras. In “A Shift in Computer Vision is Coming“, EE Times’ Sally Ward–Foxton interviewed one of the technology’s founding fathers Ryad Benosman, professor at the University of Pittsburgh and adjunct professor at the CMU Robotics Institute, about what this shift in technology will mean for vision.

CEO of event–based camera company Prophesee, Luca Verre, tells EE Times the meaning of “neuromorphic” is not fixed.

“Ask 10 different people, and you’ll get 10 different answers,” he said, adding that as technologies have developed under different constraints, companies have taken the ideas in different directions.

Verre also tells EE Times about the company’s drive to commercialize event–based cameras and exactly how the company plans to accelerate commercial adoption. Which sectors will be first to adopt and why? Find out in “Neuromorphic Sensors: Coming Soon to Consumer Electronics“.

In “Reverse–Engineering Insect Brains to Make Robots“, we take a look at British startup Opteran. The company is studying insect brains to reverse–engineer the algorithms these tiny creatures use to fly and navigate. Opteran runs its brain–inspired algorithms on standard hardware and has demonstrated a working robot and a drone using its collision avoidance algorithms.

We also take a peek at how the automotive sector is planning to use neuromorphic computing for ultra–low–power intelligence in future electric vehicles. In “Cars That Think Like You“, we explore two neuromorphic computing companies’ partnerships with BMW and Mercedes.

Articles in this Special Project:

Carver Mead Lab_squareExclusive: An Interview with Carver Mead

By: Nitin Dahad

EE Times’ exclusive interview with Carver Mead delves into his achievements in the early days of semiconductors, and his legacy.


Inspiration or Imitation: How Closely Should We Copy Biological Systems?

By: Sally Ward–Foxton

A panel of experts agrees and disagrees on exactly which parts of biology we should be taking inspiration from.


A Shift in Computer Vision is Coming

By: Sally Ward–Foxton

Neuromorphic sensing and computing will revolutionize computer vision, says one of the technology’s founding fathers.


Prophesee Sony IMX 636Neuromorphic Sensing: Coming Soon to Consumer Products

By Sally Ward–Foxton

In this interview with Prophesee CEO Luca Verre, we discuss Prophesee’s approach to commercializing its retina-inspired sensors and where the technology will go from here.


Reverse–Engineering Insect Brains to Make Robots

By Sally Ward–Foxton

British startup Opteran is working on navigation and movement algorithms inspired by honeybee brains.


NeuromorCars That Think Like You

By: Sally Ward–Foxton

Carmakers are testing neuromorphic technologies based on spiking neural networks. What will cars do with their newly found brain power?

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