For the second year in a row, DataRobot has been named one of the most promising AI companies by Forbes magazine. Forbes’ annual list, which was first published in 2019, highlights private companies that are applying artificial intelligence to solve problems in innovative ways. We are honored to be included once again.  In all, Forbes received hundreds of entries this…

Over the past several years, Machine Learning Operations (commonly referred to as MLOps, or ModelOps) has gained a growing following. With the rise of AI, many organizations recognize the need for a dedicated set of people, processes and technologies to scale AI across the enterprise.  That’s where MLOps comes in. Like DevOps for software development, MLOps helps organizations realize the…

On June 16-17, DataRobot hosted the inaugural AI Experience Worldwide conference. The two-day virtual event attracted over 7,000 registrants; we offered 31 sessions, presented by over 60 speakers. The keynotes by Alex Honnold, Michael Phelps, and Stephen Dubner, as well as the various sessions by our esteemed speakers, sparked imaginations and gave our guests a peek into some of the…

This article is part of a series, highlighting AI thought leadership recently exhibited during the AI Experience Worldwide conference. This session featured leaders from finance and healthcare, talking about their adaptations to these turbulent times, including through the use of AI. This panel was moderated by Thomas Davenport - a distinguished professor at Babson College and author specializing in analytics,…

DataRobot is excited to share its latest integration with Partner Connect, which allows us to continue to build upon our Snowflake integrations.  The DataRobot on Partner Connect announcement means that Snowflake users now have a new workflow to easily experience the power of DataRobot with the power of the leading data cloud platform. The offering makes it easier than ever…

“People are asking, when will we get back to normal? I say, let’s not get back to normal, let’s get back to remarkable, because there were parts of ‘normal’ that were not great to begin with. Let’s take this opportunity to build businesses that are more resilient, more equitable, a world that is better, where access to technology is available…

Let’s suppose you have a number of machine learning models running in your production environment. Perhaps you are using DataRobot MLOps to help you with this effort. Perhaps you are doing it using your own custom-built method. Let’s also suppose that you are monitoring those models using metrics that help you understand their service health, accuracy, and so on.  First…

On June 16 and 17, 2020, DataRobot hosted AI Experience Worldwide, our first-ever virtual conference, which brought together customers, partners, and AI visionaries to discuss how we all can accelerate the time-to-impact of AI solutions across the enterprise. Recognizing the obstacles presented by the uncertain times we live in today, the DataRobot team designed the conference agenda to address pragmatic…

Do you trust the predictions your models are generating? Let’s think about this for a moment. Machine learning models learn from historical data and use the patterns they discover to make predictions about new data. If this were a perfect world, the model would have a stable problem to solve, copious amounts of training data, and the new data received…