Friday, May 6, 2016 Registration and breakfast begin at 9 a.m. Upon arrival, be prepared to show a picture ID and sign the Building Visitor Log when approaching the Lobby Floor Security Desk. Alert them to the name of the event you are attending and ask them to direct you to the appropriate floor. The talks will be held the First Floor Conference Center, Horace Mann Conference Room. Hospitality Notice for University and Government Employees: Microsoft Research is providing hospitality at this event.

Synopsis: There is more to Text Mining than TDM and TF-IDF. Come explore the world of Sentiment Analysis using Advanced Text Mining techniques with cutting edge tools like Stanford's CoreNLP and analysing it's output using Python. Speaker: Aditya Shankar is a Lecturer in the Intelligent Systems practice at the Institute of Systems Science in the National University of Singapore. He started his career consulting for Microsoft in Redmond, WA, Nike in Portland, OR and T-Mobile in Seattle, WA. He then moved on to work for companies in the Healthcare domain, mostly healthcare providers in Tennessee.

While there may be millions of developers, there simply aren't enough data scientists to go around, and most of them are committed to working for large companies with big budgets and humongous data sets. Companies like Montreal-based Fuzzy.io are filling in the talent gap by offering an API to a set of artificial intelligence (AI) services that allows web and mobile developers to easily incorporate AI-based decision-making into their projects -- ranging from recommendations, to dynamic pricing decisions, and matching users in marketplaces. "Most of the existing ML development services are built to be used by data scientists or developers who have expertise in building AI/ML systems," said Fuzzy.io co-founder Matt Fogel. "Additionally, most of these tools require the developer to bring a great deal of data in order to train custom models. The company was founded by Fogel, who was the former produce vice president at Agendize, along with serial entrepreneur and developer Evan Prodromou. The company also recently added Kevin Fox, who, when he was at Google, helped create the user interfaces for Gmail and Google Calendar. These virtual intelligent machines use an adaptive rule base to translate pre-set, intuitive and vague "business rules" into a framework that can generate precise results. It could be as vague as "new", "old", "warm" and "good," as the company explains on its blog: "A fuzzy agent accepts some input variables and maps them onto fuzzy sets -- intuitive terms from the problem domain.

CEO Marc Benioff has made no secret of the fact that Salesforce.com's (NYSE:CRM) future will include comprehensive artificial intelligence (AI) capabilities to enhance the customer experience. Benioff's commitment to AI isn't new: He and Salesforce.com president Keith Block have been raving about its analytics cloud for nearly a year now. Deep learning, or AI, is a natural fit for Saleforce.com Salesforce.com fans may recall last summer when Benioff shared the news that its new analytics cloud was the fastest-growing product introduction ever. Benioff's conference calls are known for his over the top "rah-rah" feel, but when it comes to deep learning, Salesforce.com is doing a lot more than shouting from the rooftops.

While voice-recognition-powered virtual assistants like Siri, Cortana, Google Now and Amazon's Echo continue to get more useful and reliable on the march to platform-dom, there is a parallel wave of development underway that has captured the public eye, where machine learning, artificial intelligence and natural language processing are getting corralled for more narrowly purposed means -- by way of bots. Today, a New York-based startup called X.ai -- which has developed a bot that helps you arrange meetings with other people by way of a virtual assistant ('Amy' or'Andrew') -- announced that it has raised 23 million. The Series B funding will be used to take X.ai from a closed and free beta to a commercial product, and the startup also plans to hire more data scientists and other engineers. X.ai is not releasing details of its valuation, but we understand from reliable sources that it is now around 100 million -- a decent jump on the 40 million valuation the company had when it announced its Series A of 9 million in January 2015. The funding is being led by Two Sigma Ventures, with other new investors including DCM Ventures and Work Bench Ventures.

Pablo Picasso once declared: "Computers are useless. They can only give you answers." The Spanish artist's joke may have been true of the 20th century, when computers were for the most part souped-up calculating machines performing clearly prescribed functions. But the expansion of computing power in the early 21st century means that computers are now posing some of the most testing questions of our times. And it is not clear who is responsible for providing the answers.

In the late '90s, Tomi Poutanen, a precocious computer whiz from Finland, hoped to do his dissertation on neural networks, a scientific method aimed at teaching computers to act and think like humans. As a student at the University of Toronto, it was a logical choice. Geoffrey Hinton, the godfather of neural network research, taught and ran a research lab there. But instead of encouraging Poutanen, who went on to work at Yahoo and recently co-founded media startup Milq, one of his professors sent a stern warning about taking the academic path known as deep learning. "Smart scientists," his professor cautioned, "go there to see their careers end."

The U.S. unveiled the prototype of an autonomous, experimental warship Thursday that would drastically reduce the cost of operations at sea and mark progress in the move toward robotic warfare. It comes as the military has increasingly aimed to boost unmanned technology to counter Chinese and Russian investments. "This is an inflection point," Deputy U.S. Defense Secretary Robert Work told Reuters in an interview. "This is the first time we've ever had a totally robotic, trans-oceanic-capable ship." Work said he hoped unmanned ships would be stationed in the western Pacific within as few as five years.

Nvidia's chief executive says its self-driving system will be installed in all the cars in the Roborace Formula E series, an all-robotic, all-electric variant of Formula One that's to begin by early next year. In a speech on Tuesday at the GPU Technology Conference, in San Jose, Calif., Jen-Hsun Huang said his company's Drive PX 2 system would be standard in all the cars that the 10 Roborace teams will manage. The hardware, which was unveiled in January at CES, can be held in one hand and can perform 24 trillion operations per second while wrangling data from a dozen cameras as well as radar sets and LIDAR. When the original developer's kit was released a year ago, Michael Houston, the technical lead for the project, told IEEE Spectrum that the system could accommodate knowledge gleaned from deep learning, a method that uses reiterative analysis to discover patterns in masses of data. "Deep learning has different applications," he said.

The US has officially christened its experimental self-driving warship designed to hunt for enemy submarines for months at a time. The 132ft-long (40-metre) unarmed prototype, dubbed Sea Hunter, is the naval equivalent of Google's self-driving car, designed to cruise on the ocean's surface without a crew. The ship's projected 20 million ( 14.2 million) price tag and its 15,000 ( 10,650) to 20,000 ( 14,300) daily operating cost make it relatively inexpensive for the navy. The 132ft-long (40-metre) unarmed prototype, dubbed Sea Hunter, is the naval equivalent of Google's self-driving car, designed to cruise on the ocean's surface without a crew. The ship's projected 20 million ( 14.2 million) price tag and its 20,000 ( 14,300) daily operating cost make it relatively inexpensive for the navy The vessel was unveiled by Deputy US Defense Secretary Robert Work and has been developed by the Pentagon's Defense Advanced Research Projects Agency (Darpa).