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Huh, I wonder how much truth there is to your words. As an outsider to Machine learning and neural networks, it seems to me that algorithms can be very valuable and big companies do not lack training data. Of course, training data is expensive and very important, but if training data were that important, their most important resource would not be machine learning scientists, but an army of do-monkeys that provide training data. It won't be the victory of the smartest scientist but of the one with the most employees. And that does not seem to be the case.



It absolutely is the case. Why do you think Google has been providing such services as Google Voice, ReCaptcha, Street View, heck... Maps... and basically everything that's awesome and free? (other than the stuff that puts advertisements in your peripheral vision)

Andrew Ng told a story about one of his first robots that was supposed to roam around the lab and collect coffee cups to deposit in the sink. He ran out of varieties of coffee cups to train the robot's vision well before the robot learned how to detect a coffee cup.

The key to being a successful AI company is to figure out how to get the world to send you data.

Edit: That or figure out how real brains work and how to scale them. Which is probably almost, but not quite, entirely unlike a convolutional neural net.

Edit2: This also leads us to a twist of the dogmatic refrain: If you're not the customer, you're the employee.


It's mix between who has the most data, who can pose the problem best, who can wield the largest computers and who can handle the most complex algorithms




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