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.

Facebook on Wednesday introduced DeepText, an artificial intelligence-fueled text analytics engine. "Text is a prevalent form of communication on Facebook," wrote Facebook software engineers Ahmad Abdulkader, Aparna Lakshmiratan and Joy Zhang in a post describing its capabilities. "Understanding the various ways text is used on Facebook can help us improve people's experiences with our products," they continued, "whether we're surfacing more of the content that people want to see or filtering out undesirable content like spam." DeepText can understand with near-human accuracy the textual content of several thousands posts per second, spanning more than 20 languages. The engine leverages several deep neural network architectures and can perform word-level and character-level based learning, noted Abdulkader, Lakshmiratan and Zhang.

While Facebook has lot of noise around using artificial intelligence to better sort photos and videos, text is still a huge part of the Facebook experience. Today, we got a look behind the scenes on how AI is helping Facebook sift all that text and improve the Facebook experience with "Deep Text" -- a system developed by Facebook's AI labs that scans 10,000 posts every second in 20 languages. People post more than 1 billion items -- statuses, links, photos, whatever -- to Facebook every day, says a company spokesperson. Deep Text is "deep learning-based text understanding engine," as Facebook puts it. Its ability to understand text like a human would is already being put to work in Facebook Messenger.

While Facebook has lot of noise around using artificial intelligence to better sort photos and videos, text is still an huge part of the Facebook experience. Today, we got a look behind the scenes on how AI is helping Facebook sift all that text and improve the Facebook experience with "Deep Text" -- a system developed by Facebook's AI labs that scans 10,000 posts every second in 20 languages. People post more than 1 billion items -- statuses, links, photos, whatever -- to Facebook every day, says a company spokesperson. Deep Text is "deep learning-based text understanding engine," as Facebook puts it. Its ability to understand text like a human would is already being put to work in Facebook Messenger. And Facebook plans to take it a lot further.

Text is a prevalent form of communication on Facebook. Understanding the various ways text is used on Facebook can help us improve people's experiences with our products, whether we're surfacing more of the content that people want to see or filtering out undesirable content like spam. With this goal in mind, we built DeepText, a deep learning-based text understanding engine that can understand with near-human accuracy the textual content of several thousands posts per second, spanning more than 20 languages. DeepText leverages several deep neural network architectures, including convolutional and recurrent neural nets, and can perform word-level and character-level based learning. We use FbLearner Flow and Torch for model training.

Text is a prevalent form of communication on Facebook. Understanding the various ways text is used on Facebook can help us improve people's experiences with our products, whether we're surfacing more of the content that people want to see or filtering out undesirable content like spam. With this goal in mind, we built DeepText, a deep learning-based text understanding engine that can understand with near-human accuracy the textual content of several thousands posts per second, spanning more than 20 languages. DeepText leverages several deep neural network architectures, including convolutional and recurrent neural nets, and can perform word-level and character-level based learning. We use FbLearner Flow and Torch for model training.

While Facebook has lot of noise around using artificial intelligence to better sort photos and videos, text is still an huge part of the Facebook experience. Today, we got a look behind the scenes on how AI is helping Facebook sift all that text and improve the Facebook experience with "Deep Text" -- a system developed by Facebook's AI labs that scans 10,000 posts every second in 20 languages. People post more than 1 billion items -- statuses, links, photos, whatever -- to Facebook every day, says a company spokesperson. Deep Text is "deep learning-based text understanding engine," as Facebook puts it. Its ability to understand text like a human would is already being put to work in Facebook Messenger. And Facebook plans to take it a lot further.

Facebook has seemingly positioned artificial intelligence as one of the catalysts for innovation for the company over the next 10 years. Outlining its technology roadmap for the next 10 years, the company highlighted artificial intelligence, as well as virtual and augmented reality, as technologies to drive new features and user experience. New features highlighted include translation, photo image searches, 'talking pictures' and real-time video classification. "Artificial Intelligence will power all kinds of different services with better than human level perception and we'll see the emergence of the next major computing platform in virtual and augmented reality," said Facebook founder Mark Zuckerberg during his opening keynote at F8. "These are all elements of our 10 year roadmap to connect the world and each of these elements is in service of our mission. It's about bringing people together, that's what we do here."

Today I spoke at F8 about how the Applied Machine Learning (AML) team at Facebook is working with dozens of product teams across the company to give people communication superpowers through AI. To do this, we built an AI backbone that powers much of the Facebook experience and is used actively by more than 25 percent of all engineers across the company. Powered by a massive 40 PFLOPS GPU cluster that teams are using to train really large models with billions of parameters on huge data sets of trillions of examples, teams across the company are running 50x more AI experiments per day than a year ago, which means that research is going into production faster than ever. Here are a few of the ways that AI powers various Facebook experiences, with some demos that give a glimpse into what's possible by continuing to research and advance the state of the art in AI. Today, 50 percent of the Facebook community does not speak English, and most people don't speak each other's languages.

Today we are rolling out automatic alternative (alt) text on Facebook for iOS. Automatic alt text provides visually impaired and blind people with a text description of a photo using object recognition technology. Starting today, people using a screen reader to access Facebook on an iOS device will hear a list of items that may be shown in a photo. This feature is now available in English for people in the U.S., U.K., Canada, Australia, and New Zealand. We plan to roll it out to more platforms, languages, and markets soon.