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Facebook details its company-wide machine learning platform, FBLearner Flow

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Facebook today is talking for the first time about FBLearner Flow, a piece of software that manages machine learning models for employees throughout the social networking company. It's similar in some ways to cloud-based machine learning services like Microsoft's Azure Machine Learning, or the open-source Airflow from Airbnb, but it's optimized for Facebook's own infrastructure and filled with algorithms developed by Facebook engineers, so that many other people inside the company can make use of them for their own models. "More than 25 percent of the company are using it, in scenarios that we haven't really envisioned before," Hussein Mehanna, director of Facebook's Core Machine Learning Group, told VentureBeat in an interview. Facebook could go beyond just publishing academic papers on FBLearner Flow; the company may well end up open-sourcing it. Facebook engineers have discussed this type of technology with people at LinkedIn, Twitter, and Uber, and they've all been excited about it, Mehanna said.


Facebook's computer vision system supervises its own learning process

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The extent to which AI systems have made life easy in possibly every field needs no special mention. Healthcare, defence, transportation, or any sector for that matter – you name it and you know how positive the impact has been. Be it assisting the doctors while surgery is performed, controlling the traffic, assisting you at restaurants, teaching online or even getting done with your daily chores, AI has got you covered. However, a point here to note is that no matter how much AI promises to automate, human involvement cannot be eliminated totally. Simply put, AI has no meaning unless humans are involved.


Facebook Wants to Teach Machine Learning

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When you think of technical education about machine learning, Facebook might not be the company that pops into your head. However, the company uses machine learning, and they've rolled out a six-part video series that they say "shares best real-world practices and provides practical tips about how to apply machine-learning capabilities to real-world problems." None of the videos are longer than 10 minutes, so you'll invest less than an hour. The videos focus less on a specific product and more on the architecture and implementation strategies. Quite a bit of these videos cover things we think are pretty obvious engineering axioms applied to machine learning.


Facebook open-sources A.I. software for segmenting objects in images

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Facebook today is announcing that it's open-sourcing some of its latest artificial intelligence (A.I.) software for segmenting objects within images. The DeepMask, SharpMask, and MultiPathNet tools are available now on GitHub under a BSD license. It's not as if Facebook is opening up about these programs for the first time. They've been described in academic papers (specifically this one, this one, and this one). Now Facebook's Artificial Intelligence Research (FAIR) lab is connecting the dots with an extensive blog post and is also, of course, making the software available free for others to inspect and build on.


6 ways Facebook uses AI

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In the world of Facebook, Chief Global Security Officer Nick Lovrien says, "A day is a week, a week is a month, a month is a year." As a company, Facebook owns Instagram, Oculus, WhatsApp, and hundreds others, buying around 160 businesses just last year. The company's goal is to connect every person on the planet through Facebook-owned tech within 100 years. To get there, they're using AI. Here's a look at how Facebook is making use of artificial intelligence for projects today -- and tomorrow.