Archive for July, 2014


Empirical evidence from human resting state networks has shown a tendency for multiple brain areas to synchronise for short amounts of time, and for different synchronous groups to appear at different times. In dynamical systems terms, this behaviour resembles metastability — an intrinsically driven movement between transient, attractor-like states. However, it remains an open question what the underlying mechanism is that gives rise to these observed phenomena. Recent theories suggest that transient periods of synchronisation and desynchronisation provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Hence such seemingly metastable dynamics could facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby support sophisticated cognitive processing in the brain.

The visionary inventor, technologist, and futurist Ray Kurzweil now works at Google. He is heading a research team trying to crack artificial general intelligence seemingly by building a model of the neocortex. Google offers him resources to do this which are unmatched. Kurzweil recently gave a talk at Google I/O about his thoughts on the matter which you can watch here.

Rays talk doen’t give away much about the tech he is developing so I thought I’d buy his most recent book How To Create A Mind and see how he intends to achieve his goal. Ray did early and ground breaking work in text and speech recognition and the technologies he developed are used these days in things such as Apples SIRI. Rays states in his book that the neocortex is a vast hierarchical pattern recognition system and I don’t think anyone would contradict this. Further to this he sites communication with Henry Markham whos work has shown that there are repeated patterns of connectivity in the brain with assemblies of 12 or so neurons connected in a Lego like way. These assemblies are presumed to be individual pattern recognisers, and a hierarchical system of these would support hierarchies of feature detectors leading all the way to abstract concepts. However, I find the implicit belief that all the brain does is pattern recognition rather naive. Questions such as: how does pattern recognition relate to thought processes, behaviour or creativity? are not even approached.

Whist his book continues to discuss philosophical matters such as ‘what is the similarity between a computer and a brain?’ ,’do we have free will?’, and ‘what is the notion of identity?’, not only does he only cover old ground here but he also does not in any way relate them to his design thesis. His main and concluding thoughts seem to be with regard to the Law of Accelerating Returns, which states that once something becomes an information technology then it is subject to exponential price/performance enhancement. The problem Ray is faced with is that the mechanics of thought are presently unknown and therefore not as yet an information technology and so are not subject to this law. Unfortunately, Ray has not really suggested much on how we might tackle understanding and emulating the mechanics of thought, or perhaps he does know but Google want him to keep it under wraps.