Facebook is arguably the world's foremost artificial intelligence laboratory. Given the size of its platform, and the pressure to keep users entertained and coming back, it needs to be. On Thursday, Facebook announced that it would release another open-source A.I. tool, dubbed fastText, which is incredibly good at understanding huge blocks of text. That may not sound compelling, but the method's ripples will do wonders for your Facebook browsing experience. And, as the research is open source, those ripples will propagate throughout and thereby enhance your entire experience online.

An anonymous reader cites a report on VentureBeat: Nvidia chief executive Jen-Hsun Huang announced that the company has created a new chip, the Tesla P100, with 15 billion transistors, 16GB high-bandwidth memory for deep-learning computing. It's the biggest chip ever made, Huang said. "We decided to go all-in on A.I.," Huang said. "This is the largest FinFET chip that has ever been done." The chip has 15 billion transistors, or three times as much as many processors or graphics chips on the market.

When you think about the last two decades of data center innovation that has been driven on a foundation of Intel architecture, all of the technology advancements that have been driven from virtualization to, advances in supercomputing and advanced analytics have one thing in common: they were most likely discussed at the Intel Developer Forum prior to achieving broad market adoption. Today, the next chapter of Intel's vision for the data center was unveiled by Diane Bryant, Intel Executive Vice President and General Manager of the Data Center Group. The foundation of the next wave of compute innovation is the delivery of thousands of clouds delivering millions of services and connecting billions of consumers and businesses worldwide. This is the vision of Intel's Cloud for All initiative, working to accelerate easy to deploy cloud solutions that are self-service, self-managed and self-aware. Diane shared the advancement in enterprise cloud deployments from 12% of enterprises in 2014 to 20% this year.

Every day, billions of pieces of content are shared on Facebook. To keep up with the data, Facebook has been using a variety of tools to classify text. Traditional methods of classification, like deep neural networks are accurate, but have serious training requirements. In an effort to classify both accurately and easily, Facebook's Artificial Intelligence Research (FAIR) lab developed fastText. Today, fastText is going open source so developers can implement its libraries anywhere.

Facebook's'FastText' A.I. is the Tesla of Natural Language Processing This AI can tell if you're depressed by looking through your Instagram photos

We've talked before about the prospects of artificial intelligence (AI) and how it will likely disrupt things like we've never seen before with some estimates predicting that up to 80% of all service jobs will be impacted. Healthcare is one area where AI is receiving a good chunk of funding. We looked before at one example of an artificial intelligence company called Enlitic that uses machine learning technology to read X-rays better than a human radiologist who makes 286,000 a year on average. There are actually quite a few artificial intelligence companies in healthcare and CB Insights recently identified 65 of them at various stages of funding. Founded just last year, Chinese company iCarbonX has taken in nearly 200 million in funding from investors that include the 200 billion Chinese internet giant Tencent.

In 2005, Hanna Wallach, a machine learning researcher, found herself bunking with colleagues to attend the Neural Information Systems Processing (NIPS) conference. Wallach had been working in the field since 2001 and had attended numerous conferences, but this was the first time she had roomed with other women who specialized in machine learning, a branch of artificial intelligence that researches how computer programs can learn and grow. As a discipline, it is overwhelmingly male: Wallach estimates that only 13.5% of the entire machine learning field is female. At the conference, Wallach and her roommates, Jennifer Wortman Vaughan, Lisa Wainer, and Angela Yu, began discussing their experiences and commiserating about the lack of female allies. "We couldn't believe that there were four of us [at the conference]," Wallach says.

Scientists in Japan reportedly saved a woman's life by applying artificial intelligence to help them diagnose a rare form of cancer. Faced with a 60-year-old woman whose cancer diagnosis was unresponsive to treatment, they supplied an AI system with huge amounts of clinical cancer case data, and it diagnosed the rare leukemia that had stumped the clinicians in just ten minutes. The Watson AI system from IBM matched the patient's symptoms against 20m clinical oncology studies uploaded by a team headed by Arinobu Tojo at the University of Tokyo's Institute of Medical Science that included symptoms, treatment and response. The Memorial Sloan Kettering Cancer Center in New York has carried out similar work, where teams of clinicians and data analysts trained Watson's machine learning capabilities with oncological data in order to focus its predictive and analytic capabilities on diagnosing cancers. IBM Watson first became famous when it won the US television game show Jeopardy in 2011.

To pinpoint Inbenta's proposition in the marketplace, Jordi begins by making the important distinction between human-to-computer communication and human-to-human communication: "When we have to communicate with computers, historically humans have used HTML, Java, XML, 'command line' and a variety of languages that we collectively call'Formal Languages'. But when humans communicate with each other, we use English, Spanish and thousands of other languages called'Natural Languages'". Natural Language Processing (NLP), of course, is an area of AI that allows a computer to understand a Natural Language – and it's in this field that Inbenta thrive. At Inbenta we have developed a true natural language understanding platform that takes care of user conversations in website sites and mobile apps, answering 99% of user questions automatically and also guiding customers through all sales and support processes using chatbots. Inbenta are already working with an impressive array of enterprises, as their website shows.

In a 5,200-square-foot office in Orlando, Edison "Eddy" Ortiz and his team are building the next generation of artificial intelligence-based products for Royal Bank of Canada. The objective is to have customers interacting with virtual tellers that will make suggestions and decisions based upon machine-based learning. Someday, years from now, UCF student Sylvia DiPaulo may look at a photograph snapped during a NASA launch and see her legacy. With her University of Central Florida classmates, DiPaulo helped design a working space for NASA engineers in the agency's firing room, the area where launches are orchestrated... Someday, years from now, UCF student Sylvia DiPaulo may look at a photograph snapped during a NASA launch and see her legacy. With her University of Central Florida classmates, DiPaulo helped design a working space for NASA engineers in the agency's firing room, the area where launches are orchestrated... "It will allow us to provide virtual banking," said Ortiz, a 51-year-old Ecuadorian who has worked for the company 19 years.