GTC 2015 Artificial intelligence boffin Andrew Ng told engineers today that worrying about the rise of evil killer robots is like worrying about overpopulation and pollution on Mars before we've even set foot on it.
Ng – chief scientist at Chinese web search giant Baidu and an associate professor at Stanford University – said fretting about an evil AI enslaving the human race was "an unnecessary distraction."
The software guru, who was nabbed by Baidu Research from Google in 2014 after building the US goliath's huge machine-learning apparatus, said he will not even bother to work against the emergence of malevolent machines.
Celebrities in the tech world have voiced concerns over the potential development of an artificial intelligence bent on eradicating its creators: last year, Professor Stephen Hawking said the human race "cannot compete and will be superseded," and SpaceX supremo Elon Musk said a super-intelligent computer could be a greater worry than nuclear annihilation.
But Ng – who pioneered powerful deep-learning systems accelerated by graphics processors, and is a leading light in the growing field – is having none of it.
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"There’s also a lot of hype, that AI will create evil robots with super-intelligence. That’s an unnecessary distraction," Ng told techies gathered at Nvidia's GPU Technology Conference in San Jose, California, on Thursday.
"Those of us on the frontline shipping code, we’re excited by AI, but we don’t see a realistic path for our software to become sentient.
"There's a big difference between intelligence and sentience. There could be a race of killer robots in the far future, but I don’t work on not turning AI evil today for the same reason I don't worry about the problem of overpopulation on the planet Mars.
"If we colonize Mars, there could be too many people there, which would be a serious pressing issue. But there's no point working on it right now, and that's why I can’t productively work on not turning AI evil."
Ng also recapped Baidu's work on its Deep Speech engine, which uses deep-learning to recognize and process voice commands even in noisy restaurants, cafes and offices. It needed more than 100,000 hours of speech samples, modified using special effects, to train the GPU-powered neural network.
Access to the system will be opened up to application developers. ®