Apple Inc. (NASDAQ:AAPL) is highly expected to release its next big iOS update during its upcoming September event, along with a host of new devices. Previously, it was believed that Apple would always have a limited approach towards artificial intelligence due to its tight control over user policy. However, iOS users might have not realized it but there is already artificial intelligent capability applied in the current generation iOS operating system. Top Apple executives revealed this in a recent interview with Backchannel. The company has given a clear indication that it will continue to implement artificial intelligence features in its next generation operating system.

Why can't computers watch the Earth from above and automatically map our roads, buildings, and trash heaps? Satellite operator DigitalGlobe is teaming up with Amazon, the venture arm of the CIA, and chipmaker Nvidia to try to make it happen. In a joint project, DigitalGlobe today released satellite imagery depicting the whole of Rio de Janeiro to a resolution of 50 centimeters. The outlines of 200,000 buildings inside the city's roughly 1,900 square kilometers have been manually marked on the photos. The SpaceNet data set, as it is called, is intended to spark efforts to train machine-learning algorithms to interpret high-resolution satellite photos by themselves.

There's a myth going around that music geeks are essential to good music curation. Just look at BuzzFeed writer Reggie Ugwu's glowing feature on the "small teams of anonymous, hardcore music fans [racing] to solve the record industry's toughest problem." Indeed, Pandora, Apple, Spotify, Tidal, Google Play, and the rest bend over backwards to make clear how much they rely on music experts, and there seems to be no worse slander than saying a competitor is dependent on algorithms. But do you really need a human to pick your music? In a world when we increasingly trust AI to pick our movies, dating options, email replies, scheduling, and much more?

Google is now using its RankBrain machine learning system to process every query that the search engine handles, and the system is changing the rankings of lots of queries. The news emerged this week as part of Steven Levy's Backchannel story about machine learning efforts at Google. Google is characteristically fuzzy on exactly how it improves search (something to do with the long tail? Of the hundreds of "signals" Google search uses when it calculates its rankings (a signal might be the user's geographical location, or whether the headline on a page matches the text in the query), RankBrain is now rated as the third most useful. We've already heard before that RankBrain is considered the most useful search ranking signal, behind content and links.

And while computer scientists have tried to simply program computers to speak and understand natural language, it has become more and more apparent that learning a language is the only way to truly understand it and capture all of the nuances. That's where the machine learning comes into play. NLP is more about a class of problems than a particular method. That being said, nearly all modern NLP solutions use machine learning.)

In this video H2O.ai Deep Learning Engineer and Architect Fabrizio Milo provides on overview of TensorFlow and explains how to the library within the H2O platform. TensorFlow is an open source, deep learning framework utilized by Google and DeepMind.

And while computer scientists have tried to simply program computers to speak and understand natural language, it has become more and more apparent that learning a language is the only way to truly understand it and capture all of the nuances. That's where the machine learning comes into play. NLP is more about a class of problems than a particular method. That being said, nearly all modern NLP solutions use machine learning.)

In this video, I explain the basics of recurrent neural networks. Then we code our own RNN in 80 lines of python (plus white-space) that predicts the sum of two binary numbers after training. I'm about to hit 10K subscribers soon. If and when I do, I'm going to start working on a machine learning music video to celebrate! I recently created a Patreon page.

How much can a 17-year-old boy really know about women? For starters, that thousands face heartbreaking and costly misdiagnosed breast cancer scares every year. Abu Qader, who's about to start his final year in the Chicago public school system's Lane Technical College Prep High School, was born in war-scarred Afghanistan but has spent most of his 17 years on Earth in the U.S. Qader and European business partner Vedad Mesanovic, who focuses on young and under-resourced scientists, created a company they call GliaLab (named after the cells that support and protect neurons). They are now courting venture capitalists for a targeted 600,000 to help finance the breast cancer-focused artificial intelligence that Qader first created for a 10th-grade class project. Qader believes his technology can help women (and men, too) take on potentially deadly breast tumors and non-cancerous growths by using the convenience of their own mobile phone or tablet to aid in diagnosis and classification, reduce human error and save the expense of false-positive readings.

Ok /r/MachineLearning, I've exhausted my resources and I'm looking for assistance. I'm attempting to train a VGG style network and I'm having issues with layers dropping to 0. I collect summary stats for each layer -- conv, pool, affine -- and monitor stats while training. Layer weights drop to 0 within the first 200 mini batches. If you have any tips or suggestions, I'd really like to hear it. The link below contains code snippets and a more complete description of the problem.