Update: Though Yoshua Bengio originally referred to his incubator as Element.AI, the official name is now Element AI.

Office 365 is going to get a whole lot smarter, all thanks to Genee. Genee, an AI that has been around for two and a half years, is essentially a digital assistant that books appointments, sets reminders, and can even reschedule meetings on the fly using simple commands from your phone or computer. Now, Genee is set to come to Office 365, and it is not exactly clear what role it will play. "As we continue to build new Office 365 productivity capabilities and services our customers value, I'm confident the Genee team will help us further our ambition to bring intelligence into every digital experience," writes Corporate Vice President for Microsoft Outlook and Office 365, Rajesh Jha, in an official release. According to Genee co-founders Ben Cheung and Charles Lee, the service shuts down on September 1 in its current form.

IBM Watson Virtual Agent is a set of preconfigured cognitive components based on the IBM Watson Conversation service. By configuring the virtual agent with your company's information, you can quickly implement an automated chat bot that enables your customers to achieve their goals. The established model of creating a digital or virtual agent requires experienced developers with a highly specific skill set to create complex systems that rely on custom – and often cumbersome – rules. Watson Virtual Agent allows businesses to simply build and deploy conversational agents. Watson Virtual Agent helps accelerate users' ability to deploy bots, including pre-trained cross-industry content, with minimal configuration, simplifying the process for both seasoned developers or users without formal technical training.

Black holes are an ongoing area for research and discovery. However, many mysteries of the universe can be solved with Big Data analytics. Artificial intelligence (AI) is the killer application of Big Data analytics. Logically based on machine learning and Big Data analytics, the more data available, the more intelligent it will get, resulting in more widespread applications. In future, you may own a smart robot or even a smart dog.

Financial market watchdogs to use A.I. to catch cheaters Microsoft releases'how to train your AI' open-source toolkit GM Wants IBM's Watson AI To Sell You Stuff While You Drive Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

IN the summer of 1956, a remarkable collection of scientists and engineers gathered at Dartmouth College in Hanover, New Hampshire. Among them were computer scientist Marvin Minsky, information theorist Claude Shannon and two future Nobel prizewinners, Herbert Simon and John Nash. Their task: to spend the summer months inventing a new field of science called "artificial intelligence" (AI). They did not lack in ambition, writing in their funding application: "every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it." Their wish list was "to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves".

The irony, of course, is that this year the computer security industry, with $75 billion in annual revenue, has started to talk about how machine learning and pattern recognition techniques will improve the woeful state of computer security. "The thing people don't get is that cybercrime is becoming automated and it is scaling exponentially," said Marc Goodman, a law enforcement agency adviser and the author of Future Crimes. He added, "This is not about Matthew Broderick hacking from his basement," a reference to the 1983 movie War Games.

LAS VEGAS, Oct. 25, 2016 /PRNewswire/ IBM (NYSE: IBM) today announced IBM Watson Data Platform to help companies gain more valuable insights from data. The platform delivers the world's fastest data ingestion engine and cognitive-powered decision-making to data professionals, allowing them to collaborate in the IBM Cloud, with the services they prefer. IBM is also making IBM Watson Machine Learning Service available making machine learning simple with an intuitive, self-service interface. "Machine learning is incredibly powerful, but many of today's data professionals lack the skills to fully exploit it for business and the ability to effectively collaborate on datasets," said Bob Picciano, Senior Vice President, IBM Analytics. "Watson Data Platform applies cognitive assistance for creating machine learning models, making it far faster to get from data to insight. It also, provides one place to access machine learning services and languages, so that anyone, from an app developer to the Chief Data Officer, can collaborate seamlessly to make sense of data, ask better questions, and more effectively operationalize insight."

For the past eight years, Glassdoor has given workers a place to discreetly share information about their salaries and their work environment. The site now attracts 33 million people each month and has amassed reviews, ratings and salary information for around 600,000 companies in 190 countries. Glassdoor is now harnessing all of that data it's collected -- from its salary database in particular -- to give users a better understanding of whether or not they're being paid fairly. The free "know your worth" tool that's being rolled out in beta this week asks users to input some basic information including their job title, employer, current salary, location and relevant work experience. With that, Glassdoor is using a proprietary machine learning algorithm to calculate an individual's "market value" -- the median base pay he or she could potentially earn in their local job market.

Know which one is the lie? A new artificially intelligent camera system is picking up lies with the same accuracy as polygraph -- though those same habitual liars that con even the polygraph will likely still fool the system. The machine learning firm Tselia Data Lab recently developed a camera algorithm that detects lies based on facial signals -- and the work-in-progress already has a 75 percent accuracy rate. A high-definition camera focuses on the subject's facial features while software maps the changes in those facial features to pick up on subtleties like pupil dilation and facial tics, according to the Wall Street Journal. Fraudoscope, as the system is currently dubbed, starts much like a traditional polygraph with a set of calibration questions with a well-known answer.