Friday, September 17, 2010

NeuFlow: Close, But No Cookie

The Register reports on the NeuFlow system, presented at the High Performance Embedded Computing (HPEC) workshop in Boston, which "uses custom hardware modelled on the brain's visual-processing centres, all built on a single chip. Its designers say that it can process megapixel images and extract 3D information from them in real time."

As is the case for AI in general, Artificial Vision is full of claims as bold as they are unsubstantiated, so I took the time to read through the researchers' website. As a MSc in Computer Intelligence with interest in Artificial Vision, I think they have some really nice ideas going, and some of them may well come together into a very good autonomous system eventually – but right now they're nowhere near delivery. Actually that's the problem with most AI research: everyone has a wonderful proof-of-concept to show, but actual products – stuff you can take to the field and solve real problems with – are few and far between.

Much of it, I believe, has to do with differing standards of success between academia and industry. Whereas a commercial project, to be considered successful, must produce something that can be readily sold (ideally by the hundred thousands), a research project can "succeed" by providing a "solution" that leaves out practical usability concerns, by "solving" only part of a large problem, or even by posing interesting new questions about the subject, without actually solving anything.

I once worked for a small ISV that attempted to create a commercial product out of academic research in Artificial Vision. At first we thought we'd only write some user-friendly GUI interfaces around the research system; however, as soon as customer requirements came into play, we realized we only got one piece of a pretty big puzzle, whose overall complexity the original research had conveniently chosen not to deal with. Trying to complement what we got with results from other research projects brought us much of the same – stuff that was great under carefully controlled test conditions, but couldn't on its own live up to the harshness of production environments.

Over time it became clear that far from the usual contractor projects we were used to do, we'd first have to invest real money and real time – years, probably – to turn that pile of academic papers into something approaching a real solution, and only then hope to attract any customers. The project was subsequently put on hold, pending the granting of government research funds; soon after I left the company for a job in another city. Last I heard of them, they did got the funds, but still weren't nowhere close to delivering an actual product.

Mind you, I'm not saying that academic research isn't fruitful. We owe academia a lot of useful stuff, from RISC machines to the search algorithms used by Google and Bing, and much more is yet to come out of it. However, researchers alone can rarely pull it off; it's the industry players who most often make the bridge from promising research to usable products. Research announcements are useful to get the gist of where academia is headed, but unless they're backed by a business partner, it's unlikely they're going to bring something to the market anytime soon.

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