DataRobot Blog

“A wrecking-ball of a paper” -- this was Brandon Rohrer’s takeaway on a new paper, Underspecification Presents Challenges for Credibility in Modern Machine Learning by D’Amour, et al. Using a set of actual use cases, the paper articulates how machine learning often fails in the real world. But then the paper stops.   My customers have asked me what they should…

Those who watched the vision presentation at the recent AI Experience 2021 event might have noticed that we quietly announced a new MLOps feature called Continuous AI. I want to take some time and drill into this feature in a little more detail. First off, I won’t call it a feature again. Calling something a feature diminishes its value, and…

DataRobot and Palantir share a philosophy that AI value is delivered by uniting an organization's data scientists, decision-makers, and everyday employees in an environment of collaboration on AI/machine learning-powered operations. Today, the two organizations are excited to announce that they have partnered together to tackle one of the most complex challenges that retailers face: demand forecasting.  While many retailers already…

As they strive to improve models, data scientists continually try new approaches to refine their predictions. To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. This allows data science teams to incorporate any machine learning algorithm or feature engineering method and seamlessly combine them with hundreds of built-in methods. After adding the preferred code,…

As AI has become more ubiquitous, we’ve started to see increasingly more examples of AI behaving badly. Recent high-profile examples include hiring models that are biased against women and facial recognition systems that can’t identify black individuals. At DataRobot, we want to ensure that users have the right tools at their disposal to investigate bias. To meet that goal, we…

True Story About Eureqa  The idea of computers helping to make scientific discoveries is incredibly fascinating to me. My advisor at Cornell (and advisor on Eureqa), Hod Lipson, once joked to me “maybe all the laws of physics are elegant and beautiful because that’s all that human minds can ever hope to understand.” Along with Hod and another brilliant educator,…

In several earlier blog posts, we have focused on what we at DataRobot call the AI production gap, which refers to the gap that makes it difficult to transition models from the data science teams who develop them to the IT and DevOps teams who are responsible for deploying and monitoring them in production. Deployment and Monitoring Challenges Our DataRobot…

Announced at our recent AI Experience ‘21 conference and now in Release 7.1, we are thrilled to introduce the new No-Code AI App Builder. This allows any user, regardless of their technical expertise, to quickly turn a deployed model into a rich AI application without requiring any coding. This means that any predictive model can become an AI app in…

When I offered recent podcast guest Cindi Howson the opinion that data science has become much simpler, she had a ready response: “Are you telling me it’s not hard anymore?” I had to laugh. But Howson knows her data science. Now the chief data strategy officer at the company ThoughtSpot and host of the podcast The Data Chief, Howson has…