Meanwhile, something else that machine learning will push forward is robotics. And the 3D-printed partition will be flying in the A320 later this year. Courtesy of DJIĪutodesk is already using this technology on a project with Airbus to reimagine and redesign a new airplane cabin partition that is stronger than the original yet half the weight. And the computer could create these ideas entirely on its own, without the drawing prowess of a human. One example is designing a quadcopter: The designer wants it to do a good job of flying around and supporting its payload, which means making the chassis lightweight with low aerodynamic drag.īy giving the computer those constraints, it can explore every possible solution and come back with ideas that designers alone could never have imagined. How will this rapid advancement in machine learning in design benefit business?įirst, it will accelerate generative design. But when one computer masters Breakout, so do all of them because they’re all connected. In other words, just because you got good at Breakout didn’t help your friend get good at it. So, it could learn faster on its own than humans could ever teach it, and it can also spread its newfound knowledge to other computers quickly. One example is the Atari video game Breakout: By looking at only the score and controller input, DeepMind’s AI learned how to play the game better than any human by playing millions of games throughout the night. There’s something exponential happening throughout the past 60 years of milestones here: In less than a single human lifetime, the computer has gone from learning a child’s game to mastering the game recognized as the pinnacle of strategic thought. And by developing that trait, there was a point when even its programmers didn’t understand why it was doing what it was doing. And more recently, AlphaGo beat the best human at Go, the world’s most complex game, which has more possible moves than there are atoms in the universe.īy developing a sort of intuition, AlphaGo was able to to beat its human opponent. In 2011, Watson, a descendant of Big Blue, used reasoning to overcome its human Jeopardy! opponents. But as impressive as that was, it was pretty much brute-force computation. By 1997, Deep Blue beat Kasparov at chess. Since then, computers have gotten smarter. Sixty years ago, a programmer taught a machine to beat humans at tic-tac-toe. What does the evolution of AI and machine learning look like? Here, he talks about how machine learning is accelerating the progress of robotics, generative design, and the Internet of Things, transforming the way things are designed and made. Former Autodesk CTO Jeff Kowalski-who pursues innovative ideas on the horizon rather than trends of the moment-envisions a more positive outcome for humans and artificial intelligence (AI). Computer-gaming pioneer Arthur Samuel once defined “ machine learning” as “a field of study that gives computers the ability to learn without being explicitly programmed.” But for some people, the meaning takes a negative turn-as in what happens in dystopian movies after computers have conquered humanity.īut the future of machine learning doesn’t have to be a doom-and-gloom scenario.
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