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We are excited to join forces with Slack to host a series of workshops across Europe. These are one-day workshops, focused on making software that improves the workplace. The workshops will begin with API overviews from both companies during which Watson developer advocate Yacine, will dish out some handy tips on getting started quickly with many of the Watson services. We'll then stay to help you brainstorm, scope, and eventually build out your projects. Everyone can expect to walk away with a working prototype built on top of Slack and Watson Developer Cloud APIs.

PC Mag recently interviewed Rob High, IBM Watson's Vice President and Chief Technology Officer. Thanks to High's experience with Watson, IBM's artificial intelligence (AI) supercomputer, he is one of the preeminent thinkers in the AI space. In his interview, High spoke about how technology, and AI in particular, is transforming jobs, culture, and life for humanity. For High, one of the biggest misconceptions the public holds about AI is the sort of dystopian worldview we see in Hollywood and, in some cases, from other thinkers in the field. He points out that AI is not replacing the human mind, but augmenting human intelligence and amplifying its reach: "[I]f you look at almost every other tool that has ever been created, our tools tend to be most valuable when they're amplifying us, when they're extending our reach, when they're increasing our strength, when they're allowing us to do things that we can't do by ourselves as human beings."

Doctors are often deluged by signals from charts, test results, and other metrics to keep track of. It can be difficult to integrate and monitor all of these data for multiple patients while making real-time treatment decisions, especially when data is documented inconsistently across hospitals. In a new pair of papers, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) explore ways for computers to help doctors make better medical decisions. One team created a machine-learning approach called "ICU Intervene" that takes large amounts of intensive-care-unit (ICU) data, from vitals and labs to notes and demographics, to determine what kinds of treatments are needed for different symptoms. The system uses "deep learning" to make real-time predictions, learning from past ICU cases to make suggestions for critical care, while also explaining the reasoning behind these decisions.

Ensemble methods are meta-algorithms that combine several machine learning techniques into one predictive model in order to decrease variance (bagging), bias (boosting), or improve predictions (stacking). Most ensemble methods use a single base learning algorithm to produce homogeneous base learners, i.e. learners of the same type, leading to homogeneous ensembles. There are also some methods that use heterogeneous learners, i.e. learners of different types, leading to heterogeneous ensembles. In order for ensemble methods to be more accurate than any of its individual members, the base learners have to be as accurate as possible and as diverse as possible. Bagging stands for bootstrap aggregation.

Since their first appearance decades ago, chatbots have come a long way thanks to leaps in natural language processing and generation (NLP/NLG), the branches of artificial intelligence that enable us to interact with computers in a conversational manner. Today AI-powered chatbots have established a prominent role in various fields, including customer service, healthcare, banking and more. Meanwhile, the technologies that power chatbot assistants are growing smarter and more efficient. I had a chance to talk with Rob High, Chief Technology Officer at IBM Watson, on the evolution of chatbots and where the trend is leading to. He shared some very interesting insights on the prospects and challenges that lie ahead.

To gauge the future of IBM (NYSE: IBM) one needs to understand its cognitive computing platform, Watson.

This episode of Fast Forward was recorded in the IBM Watson Experience Center here in New York City. My guest was Rob High, the Vice President and Chief Technology Officer of IBM Watson. High works across multiple teams within IBM, including engineering, development, and strategy. He is one of the most lucid thinkers in the space of artificial intelligence, and our conversation covered many of the way that technology is reshaping our jobs, our society and our lives. Read and watch our conversation below. Dan Costa: What is the dominant misconception that people have about artificial intelligence? Rob High: I think the most common problem that we're running into with people talking about AI is they still live in the world where I think Hollywood has amplified this idea that cognitive computing, AI, is about replicating the human mind, and it's really not. Things like the Turing test tend to reinforce that what we're measuring is the idea of AI being able to compete with fooling people into believing that what you're dealing with is another human being, but that's really not been where we have found the greatest utility. This even goes back to, if you look at almost every other tool that has ever been created, our tools tend to be most valuable when they're amplifying us, when they're extending our reach, when they're increasing our strength, when they're allowing us to do things that we can't do by ourselves as human beings. That's really the way that we need to be thinking about AI as well, and to the extent that we actually call it augmented intelligence, not artificial intelligence.

When people in an emergency situation call into their local 911 operations center, there might be another "brain" listening in on the call. The Association of Public-Safety Communications Officials (APCO) International, which has more than 29,000 members, tapped IBM to bring Watson into their software. APCO recently announced that APCO International's new guide card software called APCO IntelliCommä will use IBM Watson Speech-to-Text and Watson Analytics to improve the scripts used by 911 operators. The guide card system provides guidance to 911 operators on what to ask and say to gather needed information to access specific emergency call types. Essentially, the software helps operators "provide rapid and customized instructions so callers get the fast, consistent, and appropriate information they need and expect in an emergency," according to a press release.

The Aim of the Conference The aim of the conference is to bring together researchers from all over the world who deal with machine learning and data mining in order to discuss the recent status of the research and to direct further developments. Basic research papers as well as application papers are welcome. Paper submissions should be related but not limited to any of the following topics: association rules case-based reasoning and learning classification and interpretation of images, text, video conceptional learning and clustering Goodness measures and evaluaion (e.g. Long Paper The paper must be formatted in the Springer LNCS format. They should have at most 15 pages.