Dr. Goertzel spoke with Critical Thought’s Stuart Mason Dambrot following his talk at the recent 2011 Transhumanism Meets Design Conference in New York City. His presentation, Designing Minds and Worlds, asked and answered the key questions, How can we design a world (virtual or physical) so that it supports ongoing learning and growth and ethical behavior? How can we design a mind so that it takes advantage of the affordances its world offers? These are fundamental issues that bridge AI, robotics, cyborgics, virtual world and game design, sociology and psychology and other areas. His talk addressed them from a cognitive systems theory perspective and discussed how they’re concretely being confronted in his current work applying the OpenCog Artificial General Intelligence system to control game characters in virtual worlds.
If we want to, we can make the boundary between the virtual and physical worlds pretty thin. Most roboticists work mostly in robot simulators, and a good robot simulator can simulate a great deal of what the robot confronts in the real world. There isn’t a good robot simulator for walking out in the field with birds flying overhead, the wind, the rain, and so forth – but if you’re talking about what occurs within someone’s house a lot can be accomplished.
If you took the best current robot simulators, most of which are open source, and integrated them with a virtual world, then you could build a very cool massive multiplayer robot simulator. The reason this hasn’t happened so far is simply that businesses and research funding agencies aren’t interested in this.
The cat brain that you mention was actually Dharmendra Modha’s work. It was a totally different project based on IBM hardware that was the next generation from what Markham used. They simulated a neural network similar in size and connection complexity to a cat’s brain. However, the pattern of connections was random – not derived from study of the cat brain and it didn’t go down to the level of neurotransmitter concentrations either. It was a wonderful hardware demonstration of building a formalized neural network of that huge size, but it didn’t have the same dynamics or structures as a cat brain because we don’t know what those are.
Eventually if you bring that kind of connectivity diagram together with the kind of simulation that they did, potentially you could get a large-scale simulation with more of the same structures and dynamics as a real animal’s brain – but they haven’t gotten there yet.
Open Connectome is another interesting project, at John Hopkins University, to mention in that regard. It’s a little bit earlier stage that what Modha’s team did with the monkey brain, but it’s all Open Source. Their scientists upload connectivity data from different parts of the brain, and make open source tools where anyone can go online and help map out neurons, synapses and what’s connecting to what in the data – and this could produce a much more fine-grained map of the connectivity structure. If something like that succeeds, then you could really make a large-scale brain simulation that does what the brain does – which is something that neither Markham nor Modha did in their simulations.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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