If you’ve been following my analog posts you’ll know that one of my concerns has been that we don’t train enough engineers who are really comfortable working in this area.
Analog has two major problems: not only is it just generally more difficult to design (much harder maths!), but once you do you have to go and have a chip fabricated (i.e. spend time and money) to see how it works in practice. Digital designers have an easier job to begin with, better tools, and can reliably simulate using systems like field-programmable gate arrays (FPGAs) if they’d rather not work in software simulation alone. Plus there are a gazillion of them, which also helps them to make progress!
If you’re interested in building brains into machines, this matters because analog technology seems to be the most appropriate (in terms of both power and behavior) in which to implement artifical neurons that behave in biologically-plausible or -inspired ways. This is basis of neuromorphic engineering.
Although not a new idea, field programmable analog arrays (FPAAs) may be one way of making possible both the rapid prototyping of chips and rapid training of students. Paul Hasler and his colleagues at Georgia Tech have been working on both improving the FPAA technology itself and the interfaces that designers can use with them. If you’re interested in this, please check out my recent article in EE Times on the subject.
Picture: Paul Hasler and PhD student Csaba Petre demonstrate the interface to their FPAA chip. Photo by Gary Meek.
Originally posted on Brains and Machines.