Mark Tilden changed my life. In about 1998 I started to become interested in analog computing for intelligence and came across a paper called Living Machines Mark wrote with Brosl Hasslacher a few years earlier. In it they talked about analog electronic creatures that were were very different to any other robots I had seen before. The ‘nervous networks’ that drove them were made of very few transistors, capacitors, and resistors—dozens rather than hundreds—and yet they, together, performed a rich, natural, and robust set of behaviors. The sun-seeking robots were even being used for interesting applications like satellite guidance and mine-clearing. It was a great story and it helped me understand what was important about intelligence in a way I hadn’t before.
What was more important, however, was that researching this piece made me more sensitive to other analog stories and introduced me to the community of neuromorphic engineers: people who try to build in silicon circuits that emulate biological neurons. A case in point was Reid Harrison’s work on fly vision at Caltech. Reid, I discovered, was part of a movement started by Carver Mead, who showed in his groudbreaking book that analog circuits could do the same kind of functions that biological neurons did, and at the same time would consume many orders of magnitude less power than digital circuits. I started to get sucked into the field.
About two years later, in 2001, I got the opportunity to attend the Telluride Neuromorphic Engineering Workshop in Colorado: a critical experience in my life. There I learned about floating gates and address-event representation (which I’ll get to in later posts), that I could climb from 8000 to 12000 feet in a couple of hours without dying, and that scientists and engineers are not the same. I also got to see the construction of the very first prototype of Mark Tilden’s Robosapiens (pictured). I was so inspired that I offered to start a newsletter covering the field, which is produced on behalf of the Institute of Neuromorphic Engineering.
Although I, of course, have written about the movement (and will be writing a lot more about it in this blog), I’m amazed at how few people who claim to be interested in artificial intelligence are aware of it. This community has built robots that respond to the calls of the opposite sex, can see using tiny vision chips and optical flow, that have bat-like hearing, that walk using the same kind of internal oscillations that keep a chicken running after it’s head’s been chopped off.
My theory is that neuromorphic engineering is still such a minority pursuit because it requires people to actually build things (rather than just program them). You have to solder and send chips off to be fabricated and all sorts of expensive and time-consuming things that really make getting your PhD finished difficult: you don’t just type and run. Plus you have to do the maths related to analog electronics, which is not for the faint hearted. The ‘basic’ analog VLSI course I had to do as part of my time at the workshop was well beyond me and my physics degree. In fact, companies are having difficulty recruiting analog engineers because so few bother to train.
Anyway, though small in numbers they’re doing some very interesting work. To show some of it off without rambling on for much longer here, below is a little video of the last Telluride event I attended (2005), and the test of some of their robots at the end of the three-week workshop You’ll see robots navigating around a maze. Some are very intelligent, some are not (just dumb toys designed to show that the maze can’t be navigated by accident). They use vision, sonar, feelers, and even smell as triggers to move around. And then there’s Audio Sapiana (I think that’s her name), irresistably drawn to the voice of her mate…
Photo, top: This robot is driven by a circuit based on the nervous system of a lobster.
Photo, middle: The first prototype for Robosapiens, built at the Telluride Neuromorphic Engineering Workshop in 2001.
Photo, bottom: Telluride 2005 video by Stuart Arnott of Red Planet.
Originally posted on Brains and Machines.