AI and ML are enabling a new paradigm for deploying truly transformational data projects. By leveraging voluminous real-time information and new algorithms, there is a promise of better and more efficient decision making and processes. Join this session, led by two data titans, DataRobot's CEO, Jeremy Achin and Tamr's CEO, Andy Palmer. Together they will discuss why AI and ML should have a front row seat in your next data project and what are the most critical best practices to establish the right technology, people and processes to drive project and mission success.

What do we call the collection of technologies that make up what we used to call "artificial intelligence?" This conundrum reminds me of a Raymond Carver short story (and book) called What We Talk About When We Talk About Love. I was prompted to discuss this issue by a conversation with Jeremy Achin, the young CEO of DataRobot. We were preparing for a collaborative presentation at the Open Data Science Conference in Boston a few weeks ago, and I told him I could present on "The Cognitive Company." Achin, who doesn't mince words, wrinkled up his nose and said he really didn't like the use of the word "cognitive".

DataRobot, the leader in automated machine learning, announced it has acquired Nutonian, Inc., a data science software company specializing in time series analytical modeling. The terms of the acquisition were not disclosed, and the deal is officially closed. Developed in Cornell's Artificial Intelligence Lab by two of the "World's Most Powerful Data Scientists," Nutonian's A.I.-powered modeling engine, Eureqa, powers predictive and prescriptive analytics at global companies, including Audi, Beck's Hybrids, NASA, and RealPage. Eureqa is renowned for its success in time series analytics and for creating easy-to-interpret predictive models in minutes rather than weeks or months. The addition of the Nutonian team and technology helps DataRobot accelerate its mission to bring machine learning to the masses by bolstering its capabilities across different types of modeling problems, particularly those involving time series data.