This article, appeared on 7/19/2011 on AZoRobotics, discusses the main reasons why I believe that we are on the verge of a paradigm shift in the way robots are going to be programmed.
AZoRobotics.com is part of AZoNetwork, a leading online science, engineering and medical publisher serving over 2.5 million monthly visitor sessions across its suite of sites.... so it's a good venue to get some valuable feedback.
The Neuromorphics Lab is not new to hosting industrial visitors. Historically linked with HP Labs, and recently hosting iRobot in a CELEST Catalyst event, the Lab was visited by a large contingent of managers from Ericsson on 5/3/2011. Read the rest of this entry »
Neural modelers like many neurdon readers have many things to think about. Keeping up with a growing basic neuroscience and modeling literature, coming up with equations describing neural and synaptic dynamics, and designing large-scale brain circuitry is not quite enough. If you are designing large-scale brain circuits that you want to, one day, embed in mobile robotic platforms, you also need to devote a good chunk of time to thinking on what hardware platform you would need to compute. The answer to the hamletic dilemma of digital vs analog is key. Read the rest of this entry »
This article has just been published on the Neuromorphic Engineer, the publication of the Institute of Neuroinformatics. The article discusses converging advances in memory, parallel computers, and neural network models, and how these technologies will soon allow for systems that can support complicated activities in virtual and robotic agents. Read the rest of this entry »
For the memristors/neuromorphic computing aficionados, a new article featured on the cover page of the February edition of IEEE Computer describing the joint work done by Hewlett-Packard and the Neuromorphics Lab at Boston University summarizing the challenges and the accomplishments of the past year. And what a year! The abstract says it all: "In a synchronous digital platform for building large cognitive models, memristive nanodevices form dense, resistive memories that can be placed close to conventional processing circuitry. Through adaptive transformations, the devices can interact with the world in real time." Read the rest of this entry »
No, we have not invented the flying Humvee, and we are not about to. However, if you buy the February edition of Popular Science, you will find, on page 41, a nice overview of three projects, the Connectome, the Blue Brain, and SyNAPSE. These initiatives do not share the same goals, but can be all assimilated by the way they combine neuroscience and computer science to achieve their objectives. Read the rest of this entry »
A colleague of mine pointed me to this interesting article appeared on WIRED, The AI Revolution Is On. Despite the title, it does present a somehow specular approach to our recent IEEE Spectrum article "MoNETA: A Mind Made from Memristors". Since we advocate par condicio, here it is.
This is the second post in a series of responses to comments from our IEEE Spectrum article. You can read the announcement here or the first response here.
In response to "Who will win the artificial brain race?", fellow editor Jeff Markowitz raised a particularly challenging point:
We’ve all assumed that an artificial brain of sorts can be useful for industrial or military applications, e.g. things like spatial navigation and object recognition. Why do we think that? Because humans/rats/mammals are so incredibly good at these things? Must we take for granted that replicating biological intelligence is as good as we can do?
as well as this question:
The why is what concerns me the most. Is this somewhat akin to the international space station? That is, because the engineering problem is so hard and the solution is so cool, people assume that its utility is self-evident. I mean, it’s a freaking SPACE STATION!
Our mission is intelligent machines that are suitable for real-world applications. We want to build an airplane, not a highly accurate reproduction of a bird wing. In this context the utility of neuromorphic computing isn't at all self-evident, but a number of converging trends suggest that biology may have a whole lot to teach us about computation. Ultimately, the driving force is energy.
Who will be the first to build truly intelligent machines? Would it be a lonely investigator, a modern days Darwin that, in perfect isolation, would sail back from her/his neuroscientific Galapagos with the great truth, or... Read the rest of this entry »
No, I am not going to argue that that somebody has figured out the brain road map to building a human-intelligence level chip. Actually, me and many of the people deeply involved in the endeavor of building software and hardware to emulate biological intelligence are too busy with the immense hurdles of getting even the most elementary levels of intelligence to work, that there is no time to speculate on when we will be done. Nevertheless.... Read the rest of this entry »