- [Narrator] The modern origins of artificial intelligence can be traced back to World War II and the prodigious human brain of Alan Turing.

The legendary British mathematician developed a machine capable of deciphering coded messages from the Nazis.

After the war, he was among the first to predict computers might one day match the human brain.

There are no surviving recordings of Turing's voice, but in 1951, he gave a short lecture on BBC Radio.

We asked an AI generated voice to read a passage.

- [AI Voice] I think it is probable for instance that at the end of the century, it'll be possible to program a machine to answer questions in such a way that it will be extremely difficult to guess whether the answers are being given by a man or by the machine.

- [Narrator] And so the Turing test was born.

Could anyone build a machine that could converse with a human in a way that is indistinguishable from another person?

In 1956, a group of pioneering scientists spent the summer brainstorming at Dartmouth College.

- And they told the world that they have coined a new academic field of study.

They called it artificial intelligence.

- [Narrator] For decades, their aspirations remained far ahead of the capabilities of computers.

At the time, researchers were developing expert systems, purpose built to perform specific tasks.

- And so the the thing that we need to do to make machine understand, you know, our world is to put all our knowledge into a machine and then provide it with some rules.

- [Narrator] Classic AI reached a pivotal moment in 1997 when an artificial intelligence program devised by IBM called Deep Blue, defeated world chess champion and Grandmaster, Gary Kasparov.

It searched about 200 million positions a second, navigating through a tree of possibilities to determine the best move.

- The program analyzed the board configuration, could project forward millions of moves to examine millions of possibilities, and then picked the best path.

- [Narrator] Effective, but brittle, Deep Blue wasn't strategizing as a human does.

From the outset, artificial intelligence researchers imagined making machines that think like us.

The human brain with more than 80 billion neurons learns not by following rules, but rather by taking in a steady stream of data and looking for patterns.

- The way that learning actually works in the human brain is by updating the weights of the synaptic connections that are underlying this neural network.

So we have trillions of parameters in our brain that we can adjust based on experience.

I'm getting a reward, I will update the strength of the connections that led to this reward.

I'm getting punished, I will diminish the strength of the connections that led to the punishment.

So this is the original neural network.

We did not invent it, we, you know, we inherited it.