Computational AI: Steven Pinker

Part 2 The non-computational brain model

Video capture of the introduction to the original article published in August.

One of the most influential authors in my research has been Steven Pinker. I bought most of his books and worked through them with zest, creating endless notes on my quest to understand how our brain works.

Today, I look through some of the strengths and weaknesses of what I learned.

Along these lines, my distant cousin, the scientist Michael Faraday, once said:

“Nothing is too wonderful to be true, if it be consistent with the laws of nature.”

When the science is consistent with nature’s laws, a researcher easily becomes an industry expert, as the application of science enables engineering. But when the science is inconsistent, the expertise does not lead to successful engineering. The system doesn’t work!

My quest to emulate the human brain is littered with concepts that sound good in principle, but don’t work in practice. As I say, I know thousands of ways not to create Natural Language Understanding (NLU).

Trial and error incorporates the scientific model in which theory is set and tested for accuracy.

In this series, the limitations of the science from the 1940s to the present are discussed. Which concepts did not work, which ones did and why?