Evolution is a very slow process, due largely to the fact that nature doesn’t “know” in advance which features of an animal will be beneficial. A new AI-based algorithm does know, however, allowing it to design purpose-specific robots within a matter of seconds. The algorithm was developed by a team of American scientists led by Northwestern University’s Asst. Prof. Sam Kriegman. Two years ago, Kriegman made headlines when he revealed tiny bioengineered robots known as Xenobots, which were capable of reproduction. An early version of the algorithm was used in that study, to determine the optimum body shape for the Petri-dish-swimming li’l bots – they ultimately ended up looking a bit like Pac Man. Whereas a supercomputer took months to come up with that design, the algorithm has now been refined to the point that it runs on an ordinary laptop computer, and it can deliver results within less than half a minute. It was trained utilizing the principles of natural evolution, hugely boosted by the fact that the programmers could look back through time to see what sort of biological traits worked and what sort didn’t. “Evolving robots previously required weeks of trial and error on a supercomputer, and of course before any animals could run, swim or fly around our world, there were billions upon billions of years of trial and error,” said Kriegman. “This is because evolution has no foresight. It cannot see into the future to know if a specific mutation will be beneficial or catastrophic. We found a way to remove this blindfold, thereby compressing billions of years of evolution into an instant.”
Full report : AI-based algorithm uses “compressed evolution” to create functional robots.
