But the breakthroughs haven't come without the roadblocks. "Right now," said Page, "we feel like computers are still pretty bad."
Admitting that not all of Google's attempts at technological advancement have been successful, Page pointed to Google's 'I'm Felling Lucky' feature, which was intended to allow users to skip the search results and go straight to the answer. "Maybe you don't want to ask questions, maybe you just want to have it answered before you ask it," said Page. "That would be better."
Brain predicts that the first true circuit breaker will be when robots can see, rather than think, like humans. "Computer science hasn't figured out a solution to the general vision problem yet, but as soon as that gets figured out, it opens up this huge range of jobs for replacement that have been immune to replacement for a long time," said Brain.
On that list: most remaining factory jobs, along with the fast food, retail and construction industries. "If we just take those sectors," said Brain, "that's tens of millions of jobs."
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Take leading retailer Walmart, which currently employs over 2 million people. Many of those jobs entail helping customers check out, stocking the shelves, mopping the floors, and picking up carts from the parking lot. "We are close to being able to automate these things now," says Brain. "But with a good vision system, it's a no-brainer."
According Brin, who leads the hush-hush R&D division known as Google X, cutting-edge machine learning is already capable of taking inputs such as vision—which is currently being used for Google's self-driving cars.
Google recently acquired DeepMind Technologies, a London-based startup focusing on artificial intelligence research that seeks to achieve tasks such as recognizing words in human speech or faces in video. "In theory," said Brin, "we hope it will one day be fully reasoning [artificial intelligence]."
Key word: hope.
Many dispute Brain's claim that Robots can ever truly, well, have brains.
"Computer scientists have been promising that for decades and not at all delivered," said Brin during Thursday's discussion. "So I think it would be foolish for us to make prognoses about that."
Although machine learning has never reached its speculated potential, Brin predicts it very well could down the road. "You should presume that some day we will be able to make machines that can reason and think and do things better than we can," said Brin.
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So, for now, millennials need not worry too much about a robot having a better resume, or seeing the problem more clearly. For now.
—By The Fiscal Times' Reilly Dowd