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R.U.R. was first performed in Prague in January 1921 and was such a success that an English-language adaptation was on Broadway in 1922.
By 1923, the play had been translated into thirty languages. By the end of that decade, the Oxford English Dictionary defined "robot" as "a machine capable of carrying out a complex series of actions automatically."
Karel Čapek first thought of calling his artificial people "labors," but was not satisfied and turned to his brother Josef for advice. Josef suggested the Czech word "robota," which referred to a system of forced serf labour.
When Čapek wrote R.U.R., he was known as one of the leading anti-fascist commentators of the 1930s. His writing, ideas, style, and attitude brought him to the attention of the Nazis, who named him "public enemy number two" in Czechoslovakia.
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When we're talking about robots taking people's jobs, we're speaking of automation.
Mechanical automation, like car assembly lines, has been around for a while.
Low-skill jobs, where 70% of the responsibilities are predictable physical and cognitive tasks, are straightforward to automate, especially as automation technology becomes cheaper than paying a human to do the same job.
Complex tasks that require creativity and other forms of higher-order thinking are very difficult to automate. The reason is that you need cognitive technology like AI (artificial intelligence) and automation together. At this point, AI is still limited.
Neuroevolution is a form of artificial intelligence. It is a meta-algorithm, an algorithm for designing algorithms. It adopts the principles of biological evolution in order to design smarter algor...
Traditionally, evolutionary algorithms are used to solve specific problems. For instance, the ability to control a two-legged robot. Solutions that perform the best on some metrics are selected to produce offspring.
In spite of successes, these algorithms are more computationally intensive than approaches such as "deep learning."
It goes beyond traditional evolutionary approaches. It explains innovation. Instead of optimizing for a specific goal, it embraces the creative exploration of a diverse population of solutions.
The steppingstone’s potential can be seen by analogy with biological evolution: feathers likely evolved for insulation and only later became handy for flight.