On "The path to an artificial mind", DeepMind is probably right, but there's a huge shortcut we could take, albeit not an easy one. Mimic the human hardware.
As Jeff Hawkins states in "A thousand brains", the neocortex functions as a kind of “memory prediction framework”, building models about how the world works and then constantly making predictions based on those models. Each one of our 150,000 cortical columns is a tiny learning machine ceaselessly adapting its reference frame in response to the external stimuli they receive such as the saccadic movements of our eyes, which send fresh inputs to the brain three times a second. Our brain then counts the “votes” from all of the related cortical columns to form a unified understanding of what is going on in the world at any particular time and any particular subject, compares new inputs against the predictions and makes decisions based on that.
Iif reference frames can be built into AI systems then machines could far exceed human capabilities. Whereas human neurons take at least five milliseconds to do anything useful, silicon transistors can operate a million times faster and could therefore, potentially think and learn a million times faster.
Hi David,
On "The path to an artificial mind", DeepMind is probably right, but there's a huge shortcut we could take, albeit not an easy one. Mimic the human hardware.
As Jeff Hawkins states in "A thousand brains", the neocortex functions as a kind of “memory prediction framework”, building models about how the world works and then constantly making predictions based on those models. Each one of our 150,000 cortical columns is a tiny learning machine ceaselessly adapting its reference frame in response to the external stimuli they receive such as the saccadic movements of our eyes, which send fresh inputs to the brain three times a second. Our brain then counts the “votes” from all of the related cortical columns to form a unified understanding of what is going on in the world at any particular time and any particular subject, compares new inputs against the predictions and makes decisions based on that.
Iif reference frames can be built into AI systems then machines could far exceed human capabilities. Whereas human neurons take at least five milliseconds to do anything useful, silicon transistors can operate a million times faster and could therefore, potentially think and learn a million times faster.
DeepMind (Google) should try this approach too.
Cheers,