In 1956, during a year-long trip to London and in his early 20s, the mathematician and theoretical biologist Jack D. Cowan visited Wilfred Taylor and his strange new “learning machine”. On his arrival he was baffled by the “huge bank of apparatus” that confronted him. Cowan could only stand by and watch “the machine doing its thing”. The thing it appeared to be doing was performing an “associative memory scheme” – it seemed to be able to learn how to find connections and retrieve data.
It may have looked like clunky blocks of circuitry, soldered together by hand in a mass of wires and boxes, but what Cowan was witnessing was an early analogue form of a neural network – a precursor to the most advanced artificial intelligence of today, including the much discussed ChatGPT with its ability to generate written content in response to almost any command. ChatGPT’s underlying technology is a neural network.
