Machine learning

  • 6 major Big Data predictions for 2017

    The market has evolved from technologists looking to learn and understand new big data technologies to customers who want to learn about new projects, new companies and most importantly, how organizations are actually benefitting from the technology.

    According to John Schroeder, executive chairman and founder of MapR Technologies, Inc., the acceleration in big data deployments has shifted the focus to the value of the data.

  • Machine learning and microbes: How big data is redefining biotechnology

    Machine learning and artificial intelligence are all the rage today in venture capital circles. We've seen spectacular exits in the past few years, from Google absorbing Deepmind in 2014 for $500 million, to Twitter buying TellApart in 2015 for $533 million, and Intel swallowing Nervana in 2016 for $400 million. But these were all IT plays.

  • Top 10 Big Data Trends in 2016 for Financial Services

    2015 was a groundbreaking year for banking and financial markets firms, as they continue to learn how big data can help transform their processes and organizations. Now, with an eye towards what lies ahead for 2016, we see that financial services organizations are still at various stages of their activity with big data in terms of how they’re changing their environments to leverage the benefits it can offer. Banks are continuing to make progress on drafting big data strategies, onboarding providers and executing against initial and subsequent use cases.