Today, just about every organization wants to adopt artificial intelligence (AI) and machine learning to deliver insights and predictions from the massive amounts of business and operations data they have collected. However, many of these companies don’t have the data science talent or experience to develop and deploy machine learning or AI. In fact, just knowing where to start is preventing a lot of companies from launching machine learning initiatives. Enter DataRobot.
While the demand for AI has been growing exponentially, the supply of data scientists has not grown as fast. The global demand for machine learning and AI solutions greatly exceeds the production capacity of all the data scientists in the world, and this gap is continuing to grow. DataRobot forecasts that in five years, trillions of narrow AI systems will be deployed, impacting all aspects of business, our lives, and the world around us.
Simple math dictates that the vast majority of AI applications will be developed automatically by machines.
Founded in 2012, DataRobot’s mission is to make machine learning accessible to all businesses, to bridge the gap between the supply and demand for machine learning and AI.
Automated machine learning is a technology invented by DataRobot to automate many of the tasks needed to develop AI and machine learning applications. Incorporating the knowledge and expertise of some of the world’s top data scientists, DataRobot enables more users across an enterprise to succeed with machine learning by simply utilizing their understanding of their data and business and letting DataRobot do the rest.
Just as the automobile revolutionized life in the 20th century, AI is set to revolutionize life in the 21st century. Just as Henry Ford revolutionized the production of automobiles, building its millionth car on 10th December 1915, DataRobot is revolutionizing the mass production of machine learning and AI. And speaking of mass production, DataRobot recently achieved an extremely significant milestone.
Over 1,000,000,000 models (and counting) have been built on the DataRobot Cloud platform.
Customers in industries such as healthcare, banking, manufacturing, retail, and information technology are confidently building machine learning models for hundreds of use cases, driving AI transformation across their organizations. Over ONE BILLION models! Today we’re celebrating DataRobot Cloud customers who have collectively contributed to this major achievement!
Erin Sullivan, Executive Director at Steward Health Care, and her team jumped into building models on DataRobot Cloud to improve staffing at eight of their 36 hospitals, and are seeing the results:
“We have data – a lot of data – and we want to use it to our advantage,” said Sullivan. “The best way to use it to our advantage is to learn from it, and DataRobot has the tools to help us take historical data, manipulate it, and learn from it.”
Jason Mintz, VP of Product at DemystData, expressed his experience with DataRobot Cloud in a succinct and simple way.
“Life before DataRobot was long, slow, and painful.”
Pauline McKinney, VP Data Analytics at Wellen Capital, has leveraged DataRobot Cloud to keep default rates predictable and low while being able to test and iterate with data more often.
“I’ve been in technology for 20 years. I’ve learned to enjoy getting creating with data. With DataRobot, I can get creative quickly. And that’s really where the gold is.”
To our customer community, those building the actual models that are revolutionizing their industries, thanks a billion!
About the Author
Colin Priest is the Sr. Director of Product Marketing for DataRobot, where he advises businesses on how to build business cases and successfully manage data science projects. Colin has held a number of CEO and general management roles where he has championed data science initiatives in financial services, healthcare, security, oil and gas, government and marketing. Colin is a firm believer in data-based decision making and applying automation to improve customer experience. He is passionate about the science of healthcare and does pro bono work to support cancer research.