The DARPA Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program, started in 2008, has the goal to develop electronic neuromorphic machine technology that scales to biological levels. This section covers initiatives in SyNAPSE and in related projects that use new technologies to implement artificial neural systems at biological scale and power.

  • Robots that can think

    By Massimiliano Versace | February 22, 2016

    AI_that_thinks(From BU Today) “That is a ball.” “I do believe that is a cone.” “Seems like a wonderful book.” The voice is mechanical and flat, and anyone offering such banal commentary and sounding so bored would surely bomb in a job interview. But in this case, the observations are impressive. They’re made by what looks like a two-foot-tall stack of hors d’oeuvre trays on wheels, careening around the floor and proclaiming its discoveries as its “eye,” an attached camera, falls on them.
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  • How Deep in the past go Deep Networks?

    By Massimiliano Versace | November 17, 2015

    One of the pillars of the recent success (almost viral) of Deep Networks, a subspecies of the bigger class called Neural Networks, is that their execution and training methods are highly conducive to parallelism. The term GPGPU is often use to refer to the backbone of the revolution: General-Purpose computation on Graphics Processing Units. GPUs, chips whose main technological push comes from huge revenues from the gaming market, and more recently are finding their ways into mobile devices, are in reality high-performance many-core processors that can be used to accelerate a wide range of applications, going from physics, to chemistry, to computer vision, to neuroscience. And, of course, Deep Networks.
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  • The Future of Robotics Summit – Feeding the Body, Brain and Mind

    By Massimiliano Versace | December 16, 2013

    What will it take to get robots out of YouTube and into our day to day lives? Max Versace, Director of the Boston University Neuromorphics Lab, talks about the state of the art in robotic bodies, brains and minds.  He says that in just a few years, it will be robotic intelligence that will make the next leap forward.

    In just a little more than 10 minutes, Dr. Versace presented the trends in a compelling presentation at the MassTLC Future of Robotics Summit on December 13, 2013. Watch the video and go on a journey to Mars and the brain of a mouse.

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  • Qualcomm Neural Processing Unit, Zeroth

    By Massimiliano Versace | October 24, 2013

    One talk stood out this year from MIT Technology Review’s EmTech conference on October 8th. This was Matt Grob, Qualcom CTO. Matt announced the company’s development of a new class of standardized, biologically inspired “neuromorphic” hardware, the Zeroth processors. Read the rest of this entry »

  • ETH Zurich advancing artificial brain programming

    By Massimiliano Versace | September 8, 2013

    A new article from the producting group leading by Giacomo Indiveri, a professor at the Institute of Neuroinformatics (INI), of the University of Zurich and ETH Zurich, explains how cognitive abilities can be incorporated into electronic systems made with so-called neuromorphic chips. In the article, they show how to assemble and configure these electronic systems to function in a way similar to an actual brain. Read the rest of this entry »

  • The Spikey chip

    By Massimiliano Versace | November 24, 2012

    A new article on New scientist features Spikey, the new chip coming out of Karlheinz Meier's group. The University of Heidelberg, Germany, chip contains contains 400 "neurons". The original article (see link) describes the various networks the group was able to implement in the chip, which includes a variety of different circuits. Read the rest of this entry »

  • Advances in Neuromorphic Memristor Science and Applications

    By Massimiliano Versace | August 13, 2012

    This recent book, part of the Springer Series in Cognitive and Neural Systems (Editors Robert Kozma, Robinson E. Pino, and Giovanni E. Pazienza), is one that may become part of Neurdons bookshelves. In "Advances in Neuromorphic Memristor Science and Applications", the main researchers behind the pioneering work on memristors and their applications to bio-inspired machine intelligence review the state of the art and predict trends. The Abstract: Physical implementation of the memristor at industrial scale sparked the interest from various disciplines, ranging from physics, nanotechnology, electrical engineering, neuroscience, to intelligent robotics. As any promising new technology, it has raised hopes and questions; it is an extremely challenging task to live up to the high expectations and to devise revolutionary and feasible future applications for memristive devices. The possibility of gathering prominent scientists in the heart of the Silicon Valley given by the 2011 International Joint Conference on Neural Networks held in San Jose, CA, has offered us the unique opportunity of organizing a series of special events on the present status and future. Read the rest of this entry »

  • Better late than never: Intel neural chips & memristors, but with a spin…

    By Massimiliano Versace | June 18, 2012

    Charles Augustine at Intel's Circuit Research Laboratory in Hillsboro, Oregon, and a few of his colleagues unveil their design for a neuromorphic chip based on memristors and spin valves. Neurdons have heard this before... Once upon a time, in a galaxy far, far away.... Read the rest of this entry »

  • Object recognition in mobile robots

    By Massimiliano Versace | June 15, 2012

    If you want to design robots able to interact to the real world in a useful way, you will eventually bump into the problem of implementing robust object recognition, when by robust I mean able to recognize objects irrespective of (or at least able to tolerate variation in..) distance from the object, its orientation, illumination conditions, etc.

    This post describes work done the Neuromorphics Lab, using the Cog Ex Machina software platform to recognize objects in an iRobot Create platform. Read the rest of this entry »

  • Study Computational Neuroscience at Boston University

    By Frank Guenther | September 21, 2011

    Computational BrainThe Computational Neuroscience PhD specialization of Boston University’s Graduate Program for Neuroscience provides students with a uniquely specialized curriculum that supplements core neuroscience coursework with advanced training in a wide array of computational methods for studying the nervous system and developing neuroscience-related technologies. Topics of study include: neural network modeling, neural dynamics, sensory, motor, and cognitive modeling, statistical modeling, sensory and motor prosthesis, brain-machine interfaces, neuroinformatics, neuromorphic engineering, and robotics. Coursework is chosen from the wide array of computational and neuroscience courses offered by the many departments and programs of the main Boston University campus and the BU School of Medicine. Students pursue their research interests in laboratories across the University and have the opportunity to combine hands on experimental research with highly sophisticated computational analysis.