Our human cognition is mainly based on pattern recognition. (compare Ray Kurzweil “How to Create a Mind”). Information stored in the structures of our cranial neural network is waiting sometimes for decades until a trigger stimulus makes a pattern recognizer fire. Huge amounts of patterns can be stored while most pattern recognizers are in sleeping mode consuming very little energy.
Quantum computing with incoherence time in orders of seconds is totally unsuitable for the synergistic task of pattern analysis and long term pattern memory with millions of patterns.
IBMs newest SyNAPSE chip with 5.4 billion transistors on 3.5cm² chip and only 70mW power consumption in operation is far better suited to push technological development towards AI.
Our human cognition is mainly based on pattern recognition. (compare Ray Kurzweil “How to Create a Mind”). Information stored in the structures of our cranial neural network is waiting sometimes for decades until a trigger stimulus makes a pattern recognizer fire. Huge amounts of patterns can be stored while most pattern recognizers are in sleeping mode consuming very little energy. Quantum computing with incoherence time in orders of seconds is totally unsuitable for the synergistic task of pattern analysis and long term pattern memory with millions of patterns. IBMs newest SyNAPSE chip with 5.4 billion transistors on 3.5cm² chip and only 70mW power consumption in operation is far better suited to push technological development towards AI.