The battle to build chips for the AI boom is about to get serious.
As machine learning has blossomed, the technique has become the hot ticket for businesses keen to innovate (or at least, sound like they plan to). That’s proven to be good news for anyone building hardware that runs AI software—and until now, that really meant Nvidia, which happily found that the graphics processors it had been making for years were surprisingly well-suited to crunching AI problems. But our own Tom Simonite explains that Nvidia’s dominance may be about to slide.
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Is automation actually doing enough to transform the labor market?
We always hear that robots are taking jobs. Now a report by the industry-supported Information Technology and Innovation Foundation provides a counter. It says that 165 years of U.S. labor history show job churn is lower than in the past, suggesting that technology's impact isn't as pronounced as many think. Robots certainly fuel unemployment, but that assumes they're put to use—and many roles still aren't automated which may explain the result. It's questionable to argue the problem doesn't exist, but the ITIF's right about one thing: productivity needs a boost.
Microsoft is looking beyond the smartphone for its next stab at success.
At its annual developer conference this week, Microsoft continued an innovation push by describing its vision for the future. The plan, outlined by the Register: hulking AIs in the cloud, feeding smaller devices—not necessarily smartphones—each running their own nimble AIs. Described by Microsoft’s CEO, Satya Nadella, as the “intelligent cloud and intelligent edge,” it feels to us more like a natural evolution of the current cloud-and-smartphone combination.
"Everyone starts ... with the 'brain' of the robot completely empty. The robot doesn't know anything about the world, but now we want those robots to learn new tasks?"
—Claudia Perez-D'Arpino, from MIT’s Computer Science and Artificial Intelligence Lab, explains why it’s so important to build robots that can learn quickly.