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How Amazon exec uses machine learning at home

Paul Misener
Paul Misener, Amazon’s vice president for global innovation policy and communications, talks about Amazon’s “invention machine” at the Global AI Conference. (GeekWire Photo / Alan Boyle)

Taking advantage of artificial intelligence and machine learning may be part of Paul Misener’s job as an Amazon executive, but he’s doing it for fun as well.

Misener, Amazon’s vice president for global innovation policy and communications, gave a personal endorsement for Amazon Web Services’ machine learning platform today at the Global Artificial Intelligence Conference in Seattle.

“Amazon SageMaker is a really cool service offered by Amazon Web Services,” he told the audience at the Washington State Convention Center. “This brings machine learning out to everyone, including me. I’ve done some fooling around with things on it, some hobby things.”

Like what? We had to ask.

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Paul Allen enlists machine learning as force for good

Elephant identification with AI
Machine-learning technology can contribute to image recognition programs that could identify elephants in aerial imagery on their own. (Vulcan Photo)

Paul Allen has made a name for himself as a co-founder of Microsoft, a supporter of artificial intelligence research and a contributor to causes such as wildlife conservation — so it only makes sense that the Seattle-area billionaire wants to use machine learning to further his philanthropic goals.

His latest contribution comes through the Seattle-based Vulcan Machine Learning Center for Impact, or VMLCI. “Its mission will be to apply the tools of machine learning and AI for good,” Bill Hilf, CEO of Paul Allen’s Vulcan Inc., said today in a tweet.

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How machine learning will affect future jobs

Dermatoscope
A dermatologist uses a dermatoscope, a type of handheld microscope, to look at skin. Computer scientists at Stanford have created an artificially intelligent diagnosis algorithm for skin cancer that matched the performance of board-certified dermatologists. (Stanford Photo / Matt Young)

Computer scientists have created artificial-intelligence algorithms that are at least as good as trained humans at recognizing the signs of skin cancer or malaria, but does that mean your future physician will be a bot?

Two experts on AI explain in the journal Science why the rapid rise of machine learning could be good for well-paid professionals like dermatologists and epidemiologists, no big deal for workers on the low end of the wage spectrum, but big trouble for employees in the middle.

That’s because those middle-spectrum jobs are particularly vulnerable to the machine-learning treatment, MIT’s Erik Brynjolfsson and Carnegie Mellon University’s Tom Mitchell say.

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Experts find quicker way to teach a computer

Image: Human vs. machine
This illustration gives a sense of how characters from alphabets around the world were replicated through human vs. machine learning. (Credit: Danqing Wang)

Researchers say they’ve developed an algorithm that can teach a new concept to a computer using just one example, rather than the thousands of examples that are traditionally required for machine learning.

The algorithm takes advantage of a probabilistic approach the researchers call “Bayesian Program Learning,” or BPL. Essentially, the computer generates its own additional examples, and then determines which ones fit the pattern best.

The researchers behind BPL say they’re trying to reproduce the way humans catch on to a new task after seeing it done once – whether it’s a child recognizing a horse, or a mechanic replacing a head gasket.

“The gap between machine learning and human learning capacities remains vast,” said MIT’s Joshua Tenenbaum, one of the authors of a research paper published today in the journal Science. “We want to close that gap, and that’s the long-term goal.”

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