This is a great move for Google's AI research, since their current Director of Research,Peter Norvig, comes from a mathematical background and is a strong defender the use of statistical models that have no biological basis.[1] While these techniques have their use in specific areas, they will never lead us to a general purpose strong AI.
Lately Kurzweil has come around to see that symbolic and bayesian networks have been holding AI back for the past 50 years. He is now a proponent of using biologically inspired methods similar to Jeff Hawkins' approach of Hierarchical Temporal Memory.
Hopefully, he'll bring some fresh ideas to Google. This will be especially useful in areas like voice recognition and translation. For example, just last week, I needed to translate. "We need to meet up" to Chinese. Google translates it to (can't type Chinese in Slashdot?)
, meaning "We need to satisfy". This is where statistical translations fail, because statistics and probabilities will never teach machines to "understand" language.
Leaders in AI like Kurzweil and Hawkins are going to finally crack the AI problem. With Kurzweil's experience and Google's resources, it might happen a lot sooner than you all expect.
[1] http://www.tor.com/blogs/2011/06/norvig-vs-chomsky-and-the-fight-for-the-future-of-ai