DataRobot Blog

No matter what language you bring to DataRobot, you can always expect to see the same great results. Learn more about the next generation of Text AI for DataRobot AI Cloud Platform.

Many companies struggle to turn the data they collect into true, actionable insights that can increase ROI. Here are some ways that putting AI to work helps organizations make informed marketing decisions instead of guesses.

AI Impact Statements are rapidly becoming the tool of choice for thinking about whether an AI-driven solution will deliver business value, operate safely and ethically, and align with stakeholder needs.

Anima Anandkumar is a world-renowned AI researcher with brilliant answers to some of the most complicated AI questions. In this episode of More Intelligent Tomorrow, we talk about AI’s role in science and how future AGI systems might behave.

This is the final post in a three part series that describes what is needed for companies to properly govern and ultimately trust their AI systems. This article will discuss the technologies DataRobot uses to help ensure trust in the AI systems built on our platform

General Electric (GE) wanted to boost the energy production of its wind farms by 20 percent, which would produce up to an estimated $50 billion in value. That’s when GE turned to AI. Read more.

Trusted AI as a culture and practice is difficult at any level. The focus in this blog will be on the processes that our stakeholders utilize to create structure, repeatability, and standardization. 

In this episode, Cameron Chell discusses use cases for drones today, how humans need to expand their intelligence with new neuropaths, and the vast challenges humanity must overcome in the coming decades.

In the final installment of this blog series examine how Machine Learning Operations (MLOps) allows governments to easily deploy, monitor, and update models in production, paving the way to AI with measurable results.