Facebook's long-term roadmap is focused on building foundational technologies in three areas: connectivity, artificial intelligence and virtual reality. We believe that major research and engineering breakthroughs in each of these areas will help us make more progress toward opening the world to everyone over the next decade. Our work in AI is helping us move all these projects forward. We're conducting industry-leading research to help drive advancements in AI disciplines like computer vision, language understanding and machine learning. We then use this research to build infrastructure that anyone at Facebook can use to build new products and services.

Researchers at Microsoft achieved what they say is a breakthrough in speech recognition claiming they've developed a system that's as effective or better than people with professional transcription skills. The software's word error rate (WER) is down to 5.9 percent -- an improvement from the WER of 6.9 the team reported in September. The milestone was enabled with the new Microsoft Cognitive Toolkit, the software that enables those speech recognition advances (as well as image recognition and search relevance). Microsoft announced both developments two weeks ago, though the timing wasn't the best as IBM was holding its huge World of Watson event in Las Vegas. Watson, of course, is Big Blue's AI system made famous several years ago when it appeared on Jeopardy and, in advance of its latest rollout, made the talk-show circuit including CNN and CBS's 60 Minutes, where IBM Chairman, President and CEO Ginni Rometty talked up Watson's own achievements including the ability to discover potential cancer cures deemed not possible by humans, among other milestones.

Definition – What does Artificial Intelligence (AI) mean? Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Artificial intelligence is a branch of computer science that aims to create intelligent machines. It has become an essential part of the technology industry. Research associated with artificial intelligence is highly technical and specialized. Knowledge engineering is a core part of AI research.

In the past 5 years, technology has revolutionized how marketers interact with their customers. Now, you've got access to advanced software and customer data for more relevant, targeted and engaging marketing. No wonder that 50 to 65% of executives expect to spend more on marketing technology in the coming year. But, what if I told you that we're only at the beginning? In the next 5 years, marketing is going to make a huge pivot- probably almost unrecognizable from its current form. You probably won't perform search engine optimization. Instead, you'll create an exotic virtual experience for your customers. A great example is artificial intelligence-powered voice assistants on your smartphones, for performing simple tasks. Sure, they lack context and aren't functional for complex tasks. But, we'll get there soon. To give you an overview, here are the 5 emerging technologies that Forrester expects to change the world, in the next 5 years. We already have some info on how these technologies are going to affect the customer-business relationship.

Even professional lip-readers can figure out only 20% to 60% of what a person is saying. Slight movements of a person's lips at the speed of natural speech are immensely difficult to reliably understand, especially from a distance or if the lips are obscured. And lip-reading isn't just a plot point in NCIS: It's an essential tool to understand the world for the hearing-impaired, and if automated reliably, could help millions. A new paper (pdf) from the University of Oxford (with funding from Alphabet's DeepMind) details an artificial intelligence system, called LipNet, that watches video of a person speaking and matches text to the movement of their mouth with 93.4% accuracy. The previous state of the art system operated word-by-word, and had an accuracy of 79.6%.

In a speech today at Web Summit, Facebook CTO Mike Schroepfer laid out a vision for the role artificial intelligence and machine learning will play in the company's ambitions to improve global connectivity, technology accessibility, and human computer interaction. "People want to stay connected and close to other people, so whatever is the best current technology to deploy that is the business we want to be in," said Schroepfer. Large companies like Facebook play an incredibly important role in the artificial intelligence and machine learning ecosystem. Their sheer size and ability to corner the market on talent makes almost every strategic decision they make an industry-wide declaration. Despite setbacks, like the explosion of Facebook's satellite aboard a SpaceX Falcon 9 earlier this summer, the company remains steadfast in its goals to better connect the world.

Ben Dickson is a software engineer and the founder of TechTalks. As artificial intelligence and machine learning mature and manifest their potential to take on complicated tasks, we've become somewhat expectant that robots can succeed where humans have failed -- namely, in putting aside personal biases when making decisions. But as recent cases have shown, like all disruptive technologies, machine learning introduces its own set of unexpected challenges and sometimes yields results that are wrong, unsavory, offensive and not aligned with the moral and ethical standards of human society. While some of these stories might sound amusing, they do lead us to ponder the implications of a future where robots and artificial intelligence take on more critical responsibilities and will have to be held responsible for the possibly wrong decisions they make. At its core, machine learning uses algorithms to parse data, extract patterns, learn and make predictions and decisions based on the gleaned insights.

Facebook users will be able to record smartphone videos that ape the style of famous artworks with a new feature unveiled Tuesday. Using a technique called style transfer, the feature takes live video and turns it into something that resembles the work of Van Gogh, Picasso and other artists. That effect is probably familiar to people who have used the app Prisma, which uses similar techniques to change the look of photos. Prisma's app can't perform live filtering, and some filters require a connection to the internet. Facebook's system can work offline and render live.

If you're a whip-smart investor with big bucks to spend, chances are you've got your fingers in the AI pie. It's a market where $50 million is chump change, so if you really want to play with the high rollers you'll need more room on the check. Sentient's up to $144 million in an AI platform play, while Vicarious Systems has thrown $67 million at AI algorithms. So it's pretty fair to say that if you're a bot, you're going to enjoy a top-notch private education. What's made machine learning and AI the hot stuff du jour?

Almost a year ago, we published our now-annual landscape of machine intelligence companies, and goodness have we seen a lot of activity since then. This year's landscape has a third more companies than our first one did two years ago, and it feels even more futile to try to be comprehensive, since this just scratches the surface of all of the activity out there. As has been the case for the last couple of years, our fund still obsesses over "problem first" machine intelligence--we've invested in 35 machine intelligence companies solving 35 meaningful problems in areas from security to recruiting to software development. At the same time, the hype around machine intelligence methods continues to grow: the words "deep learning" now equally represent a series of meaningful breakthroughs (wonderful) but also a hyped phrase like "big data" (not so good!). We care about whether a founder uses the right method to solve a problem, not the fanciest one.