Naïve algorithms

Computers could only execute commands they couldn’t store them or “remember” them.

In 1950 English Mathematician Alan Turing published a paper entitled “Computing Machinery and Intelligence” posing the question, “Can machines think?” within it he devised the Turing Test, or “Imitation Game”, which was a simple test that could be used to prove that machines could think.

In 1956 The term artificial intelligence was first coined by John McCarthy when he held an academic conference on the subject.

In 1959 Arthur Samuel coins the term “machine learning,” saying one day a computer will be able to beat a person at chess. It was Claude Shannon who first wrote a paper about developing a chess playing program.

Machine Learning

Machine learning enables computers to act and make data-driven decisions rather than being explicitly programmed to carry out a certain task.

In 1965 Joseph Weizenbaum develops ELIZA, an interactive program that is able to have a dialogue on any subject.

In 1986 Mercedes-Benz builds the first driverless car at Bundeswehr University in Munich under the direction of Ernst Dickmanns.

In 1997 Deep Blue (IBM) challenged and defeated the then world chess champion Gary Kasparov. The machine uses power to examine thousands of moves using a min-max search algorithm. It wasn’t a decisive victory but with machines continually increasing in power, many feel the match was just a taste of things to come.

Deep Learning

Computing power caught up to need, allowing computers to learn unsupervised from data that is unstructured or unlabelled, recognize objects and translate speech in real-time.

In 2011 IBM’s Watson wins Jeopardy beating two former champions.

In 2014 Chatbot Eugene Goostman is said to have passed the Turing Test at Reading University.

In 2016 Google DeepMind’s AlphaGo defeats Go champion Lee Sedol.

Deep reinforcement learning

Today “I learn to learn” algorithms allow us to create ever smarter machines, even ones that can learn by themselves.

Distributed agents, Swarm deep reinforcement learning

The next generation “I contribute, I exchange” algorithms will make distributed AIs cooperating a reality. They’re already there in the most advanced research labs.