The Wright Brothers of AI
I just watched Scott Brown's and Dileep George's Singularity Summit talk on YouTube. Brown and George are the founders of Vicarious Systems Inc., the Redwood City, CA startup that got funded by a couple of big names in Silicon Valley to develop the next big thing in computing, a machine that mimicks the functions of the human brain. That was back in February. I was expecting a major announcement. I was disappointed. The talk was just hype: "we got something big but our IP lawyer told us not to say anything" kind of thing. Lame.
The main point of their presentation was that, just as the Wright brothers studied nature (the flight of birds) to arrive at the design for their first motorized airplane, they too, are studying nature (the brain) to design the first brain-like artificial intelligence. The suggestion seems to be that Vicarious is conducting pioneering research in AI that nobody else is doing, which is not true, of course. There are many other researchers and organizations in the field, including George's previous company, Numenta, who are using the exact same approach. The main difference is that, unlike the Wright brothers who conducted their research in plain view, Brown and George are conducting theirs in secret.
So what do I think of Vicarious' chances of solving the AI problem? I'll be blunt. I think they have no chance whatsoever. Zilch. Here's why. Dileep George, the brain of the company, is a PhD electrical engineer and mathematician who believes that math is essential to solving the AI puzzle. This alone tells me that he has no real understanding of the problem. Furthermore, although I think that a study of the brain can eventually lead to a major breakthrough, it is highly unlikely that this approach will lead to a breakthrough in the foreseeable future. The brain has a bad habit of hiding its secrets in a forest of apparent complexity. The Wright brothers never had to deal with hidden knowledge. They, like everyone else, could easily observe the gliding flight of birds and derive useful principles.
As an example, let's take George's adoption of Bayesian inference for sequence prediction in hierarchical memory. Bayesian statistics is the sort of thing that a mathematician like George would find attractive just because it's math. But is it based on the known biology of the brain? Not at all. Can George search the neuroscience and biology literature to find out what method the brain uses for prediction? The answer is no because biologists have not yet discovered how the brain does it. They just know from psychology that the brain is very good at judging probabilities based on experience. That is the extent of their knowledge.
The reality is that brain theorists are using the Bayesian brain hypothesis only as a possible avenue of research. They hope and pray that the brain is using Bayesian statistics but it's just speculation. There is no biological evidence for it. In my opinion, looking into a maze of dendritic wiring to get a glimpse of how the brain handles prediction is an exercise in futility, unless one has a thousand years to work on the problem. Does Vicarious have a thousand years to do research? I don't think so.
Rebel Speech Update
As usually happens when I am trying to implement a major paradigm shift in my work, I am swamped with personal and legal problems that are taking most of my time and have nothing to do with my research. Still, I am making excellent progress with my Rebel Speech experiments and I hope to have an uploadable demo program that anybody can play with before the end of November.
And, by the way, I have changed my mind about turning Rebel Speech and Rebel Vision into a business. I have decided to reveal all when the demo is ready for public consumption.
Rebel Speech Recognition Theory
The Second Great AI Red Herring Chase
The Myth of the Bayesian Brain