Embedded, Self Organizing Systems

A few years back, after many years developing embedded, real-time systems, I turned my attention to AI systems of the day to explore opportunities for embedding them into new products. Fuzzy Logic was in vogue at the time along with Expert Systems and Neural Networks. Each had enabled new products in limited spheres but it was painfully apparent nothing could yet approach what natural systems do so effortlessly, such as a fly avoiding the branches and leaves of a bush while zipping through it at top speed. This caught my imagination, and I became aware of how far computer architectures based on Turing machines were from real life nervous systems with their massively parallel, noisy, slow, self-organizing fabrics. In addition, none of the pattern recognition systems took much consideration of temporal changes in the environment which is the hallmark of any living creature’s ability to react to stimulus.

It seemed unlikely folks would ever glean insight about how a brain does anything from looking at a cross section of neurons or attempting to top down reverse engineer the neocortex from people’s outward behavior. As it has to so many others, it eventually seemed clear to me the realization of systems that could best do the things that biological systems do should be derived from a system self organizing its own complex networks similar to what all living creatures do either through eons of generations of genetic conditioning or through the process of behavioral learning. This seemed counter intuitive at first: after all, software engineers produce highly complex systems by incrementally battling the deterministic rules of merciless computers, quite unlike neurons; and I had lived in that environment for many years. To give up that paradigm in order to take a step in the direction of solving problems that have eluded AI is a tall order and a controversial one but nevertheless a direction I believed was required so as to make real progress.

I still think that’s the best route and, thanks to inspiration from a myriad of places on the Internet and books that I’ve enjoyed like Jeff Hawkin’s “On Intelligence,” I’m motivated to explore this field and related topics in this blog which has so much potential and has held such a fascination for me and so many others over the years. In my opinion it’s also a great time to be exploring applications of embedded, parallel, self organizing systems as cost and processing power are no longer the barriers to entry they were in earlier times. Platforms like the Arudino open source hardware environment with its CCL license both legally and financially position small business to begin to break down the barriers that have held back traditional machine architectures and patents, commercialization of applications will no doubt follow.

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