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Machines are becoming more creative than humans

Reporter: Aviva Lev-Ari, PhD, RN

Can machines be creative? Recent successes in AI have shown that machines can now perform at human levels in many tasks that, just a few years ago, were considered to be decades away, like driving cars, understanding spoken language, and recognizing objects. But these are all tasks where we know what needs to be done, and the machine is just imitating us. What about tasks where the right answers are not known? Can machines be programmed to find solutions on their own, and perhaps even come up with creative solutions that humans would find difficult?

The answer is a definite yes! There are branches of AI focused precisely on this challenge, including evolutionary computation and reinforcement learning. Like the popular deep learning methods, which are responsible for many of the recent AI successes, these branches of AI have benefitted from the million-fold increase in computing power we’ve seen over the last two decades. There arenow antennas in spacecraft so complex they could only be designed through computational evolution. There are game playing agents in Othello, Backgammon, and most recently in Go that have learned to play at the level of the best humans, and in the case of AlphaGo, even beyond the ability of the best humans. There are non-player characters in Unreal Tournament that have evolved to be indistinguishable from humans, thereby passing the Turing test— at least for game bots. And in finance, there are computational traders in the stock market evolved to make real money.

Many new applications have suddenly come within our reach thanks to computational creativity — even though most of us do not realize it yet. If you are facing a design problem where potential solutions can be tested automatically, chances are you could evolve those solutions automatically as well. In areas where computers are already used to draft designs, the natural next step is to harness evolutionary search. This will allow human designers to gain more traction for their ideas, such as machine parts that are easier to manufacture, stock portfolios that minimize risk, or websites that result in more conversions. In other areas, it may take some engineering effort to define the design problem for the computer, but the effort may be rewarded by truly novel designs, such as finless rockets, new video game genres, personalized preventive medicine, and safer and more efficient traffic.

Sourced through Scoop.it from: venturebeat.com

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