You can, for instance, train a deep-learning algorithm to recognize a cat with a cat-fancier’s level of expertise, but you’ll need to feed it tens or even hundreds of thousands of images of felines, capturing a huge amount of variation in size, shape, texture, lighting, and orientation Gamalon uses a technique that it calls Bayesian program synthesis to build algorithms capable of learning from fewer examples.
The game sucks: it’s tough and not that fun until a certain point and then it gets really easy to win. It’s like a metaphor for something in my life I can’t quite figure out. Perhaps because HBO can’t get you to a party and you can’t make out in a Buzzfeed? - Whatsapp, TMZ, Vice, and Yahoo are all super uncool. The first book is great, the next two are good but pretty depressing. While this didn’t grab me as much as it did everyone else, the Academy got it right. I even got a little teary at the end but perhaps that’s just because my emotional life is a puddly mess rn. That’s 10,000 trillion kilometers, and you can see it with your naked eye!
The new series of Doctor Who starts tonight, the first series of the world's longest-running and most successful sci-fi show since it celebrated its 50th birthday in November.
It is the first series with the Twelfth Doctor, played by Peter Capaldi.
Still, in theory, Lake says, the approach has significant potential because it can automate aspects of developing a machine-learning model.
“Probabilistic programming will make machine learning much easier for researchers and practitioners,” Lake says.