Ray Kurzweil Clarifies his Vision of Reverse Engineering the Brain and Developing Artificial Intelligence from Principles Gleaned from Brain Science

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Ray indicated that we would be able to reverse-engineer the brain sufficiently to understand its basic principles of operation within two decades.

Ray is responding to a charge by PZ Myers that Ray does not understand the brain.

I attended the Ray Kurzweil talk at the Singularity Summit and I can attest to the fact that Myers misrepresents what Ray said.
In the liveblogging there were specific examples of how understanding the brain processes gave an insight that inspired algorithms and approaches to hearing and image recognition.

Demis Hassabis gives a more detailed description of a hybrid of neuroscience inspired approaches and machine learning which seems to be a more detailed description of what Ray was outlining

Ray presented a number of arguments as to why the design of the brain is not as complex as some theorists have advocated. This is to respond to the notion that it would require trillions of lines of code to create a comparable system. The argument from the amount of information in the genome is one of several such arguments. It is not a proposed strategy for accomplishing reverse-engineering. It is an argument from information theory, which Myers obviously does not understand.

The amount of information in the genome (after lossless compression, which is feasible because of the massive redundancy in the genome) is about 50 million bytes (down from 800 million bytes in the uncompressed genome). It is true that the information in the genome goes through a complex route to create a brain, but the information in the genome constrains the amount of information in the brain prior to the brain’s interaction with its environment.

It is true that the brain gains a great deal of information by interacting with its environment – it is an adaptive learning system. But we should not confuse the information that is learned with the innate design of the brain. The question we are trying to address is: what is the complexity of this system (that we call the brain) that makes it capable of self-organizing and learning from its environment? The original source of that design is the genome (plus a small amount of information from the epigenetic machinery), so we can gain an estimate of the amount of information in this way.

The goal of reverse-engineering the brain is the same as for any other biological or nonbiological system – to understand its principles of operation. We can then implement these methods using other substrates other than a biochemical system that sends messages at speeds that are a million times slower than contemporary electronics. The goal of engineering is to leverage and focus the powers of principles of operation that are understood, just as we have leveraged the power of Bernoulli’s principle to create the entire world of aviation.

As for the time frame, some of my critics claim that I underestimate the complexity of the problem. I have studied these issues for over four decades, so I believe I have a good appreciation for the level of challenge. What I would say is that my critics underestimate the power of the exponential growth of information technology.

Here is a pointer to where I link to all of my livebloggig coverage of the 2010 Singularity Summit

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