Jim Carnicelli's AI Blog

[ Audio Version ] I recently finished reading a brief but refreshing book on intelligence titled " On Intelligence ", by Jeff Hawkins with Sandra Blakeslee . I found the ideas espoused concise, yet penetrating; bold, if perhaps a little hasty. I want to recommend that anyone with any serious interest in the future of AI read this book. It may well have as much impact on AI in the coming decade as things like classifier systems, neural networks, and genetic algorithms have had to date. I hope that Sandra Blakeslee, coauthor and surely a bright light in her own regard, will not take too much offense if I attribute the synthesized concept and work of this book primarily to Jeff Hawkins. I apologize if it is unwarranted, but it's certainly simpler for the purpose of writing a review. First, it's worth pointing out that Jeff Hawkins has had a successful career developing handheld computer technologies, including for the venerable Grid computers, as the chief techn

[ Audio Version ] I just completed a small project into general purpose machine vision. The essential concept is to grow "bubbles" within regions of an image that have the same color or smooth gradients of color that shift gradually from one to another. The method is a bit like a traditional flood-fill algorith, but uses a continuous loop of nodes that move and multiply to push the loop ever outward until they hit individual obstacles. The growth is controlled primarily by cellular automata style rules. There's also an algorithm for dealing with cases where the bubble wraps around "islands" of obstacles. Rather than leave a seam behind as the bubble grows, it engulfs these islands by connecting the touching parts of the loop and discarding the parts of the loop left inside. I also critique the shortcomings of the bubble concept and indicate opportunities to build on its successes. I've included the source code for download and provided extensive explan