Over the past 12 years, I have been fortunate to explore what is possible AI through innovation, starting in graduate school at Cornell University, to building a company based on Eureka algorithm, and leads a team of innovators in DataRobot. Since then, I’ve been more and more motivated to take what I’ve learned over the years and push these boundaries even further. For the past few months, I’ve been working with Dom Divakaruni, the Product Lead for the Azure OpenAI Service. I couldn’t be more excited to share what we’re doing with DataRobot and Microsoft Azure OpenAI service.
Today we are unveiling a new cutting-edge integration with the Microsoft Azure OpenAI Service. This integration, which uses the ChatGPT model in Azure OpenAI, provides a conversational AI experience that will allow you to directly interact with and interpret the model’s results and predictions. This important milestone is the first step in drastically modernizing not only the development, but most importantly, the interpretation, understanding, and adoption of AI use cases.
The integration of DataRobot and Azure OpenAI Service breaks down a barrier that has long existed between data teams and business stakeholders. This integration takes the power of one of the most advanced large language model technologies in existence today in the Azure OpenAI Service, and through DataRobot, drives value-centric machine learning results.
Traditionally, generating appropriate data science code and interpreting the results to solve a use-case was done manually by data scientists. This is a time-intensive process that can slow down the adoption of AI in an organization. However, we now capture information managed by DataRobot (such as data, features, models, predictions) and using Azure OpenAI Service capabilities to make it more accessible and understandable. The integration allows you to build intelligent data science code that reflects your use case. For example, developing code to prepare data as well as training and deploying a model. And, it allows you to translate modeling results into key business takeaways. An example of this is suggesting why a feature has a high impact on predictions. Data scientists still need to analyze and analyze these results. However, data science teams can spend less time developing interpretations of ML predictions and business users can gain more understanding from their ML applications. Ultimately, users benefit from a transparent, clear explanation of what ML predictions mean to them.
While I’m very excited about what this means for the increasing applications and impact of AI, this is just the beginning. Microsoft and DataRobot will work together to expand the performance and reliability of these solutions together, giving customers more confidence to rely on insights.
This new innovation is a testament to DataRobot’s relentless focus on developing pioneering solutions to kick-start a customer’s AI projects for game-changing results. This is another example of how DataRobot AI Platform makes it easy to seamlessly integrate with new technologies, such as Azure OpenAI Service, so you can build innovative business solutions using ML.
Accelerating Value-Driven AI with DataRobot and Azure OpenAI
So how does this happen? With this new approach, we’re doing something completely new data science experience in development and collaboration. DataRobot and Microsoft have provided new capabilities from large modeling languages to anticipate the code that AI developers need to write to solve a specific use case, and translate the resulting statistical results into business language that required to communicate and collaborate with key business stakeholders.
For example, a data scientist can develop data prep code appropriate for a use-case, such as aggregating relevant data and delivering targets, automatically, by describing the problem in a natural language. This saves us the time it would otherwise take to memorize metadata and APIs.
Next, when the business user starts asking questions and analyzing insights, the DataRobot AI Platform dynamically displays use case information, data, and models along with analysis generated using Azure OpenAI models to generate text description of the most important observations. , and the interpretations of what they mean. Rather than simply explaining models in business language, Azure OpenAI Service’s conversational capabilities enable business stakeholders to ask follow-up questions and drill into what the most impactful findings are .
It’s a revolutionary conversational experience that allows everyday people to interact with an ML model and its insights. New for data scientists, it helps translate model math into business impact, and it also helps business stakeholders get the answers they need to drive change.
Giving Data Scientists New Power Tools to Go Faster
As any data scientist knows, building models and interpreting results is a time-consuming process. Coding includes memorizing APIs, debugging, and fixing errors. Interpreting the results means translating what the raw data features represent and contextualizing the insight trends. While a data scientist may know the data, AI-generated explanations help others understand what various findings mean as well.
The unique user experience, which combines DataRobot and Azure OpenAI Service, modernizes and accelerates many of the repetitive tasks required to develop and implement models, such as building in a notebook and summarizing the key outcomes for stakeholders. Data scientists can quickly innovate to address new ML problems and see their organizations work impact. Integration also helps data scientists create new ways to clearly express and explain ML models. DataRobot and Azure OpenAI Service together help generate more actionable insights.
The Potential of DataRobot and Microsoft Azure OpenAI Service
We are just getting started. It’s a natural fit for Microsoft and DataRobot to work together. We’ll work together to embed complex generative AI techniques from Azure into DataRobot’s modeling techniques going forward – unlocking entirely new use cases for the enterprise.
A History Rooted in Innovation
DataRobot is leading innovation in the areas of AutoML, MLOps, Automated Time Series, and feature engineering. I am personally excited about what the integration with Azure OpenAI Service means for data science and our future customers.
We’ve been innovating for the last decade, and we’re not done yet. Stay tuned and watch what’s coming. The DataRobot team strives to push the boundaries with all the new innovations emerging in AI to help organizations apply them in their organizations for value-driven AI.
See DataRobot and Azure OpenAI capabilities in action and learn more about the DataRobot and Microsoft partnership at the virtual event, From Vision to Value: Creating Impact with AIlive or on-demand.
About the author
Chief Technology Officer, DataRobot
Michael Schmidt serves as DataRobot’s Chief Technology Officer, where he is responsible for leading the next frontier of the company’s innovative technology. Schmidt joined DataRobot in 2017 following the company’s acquisition of Nutonian, a machine learning company he founded and led, and was instrumental in successful product launches, including the Automated Time Series. Schmidt earned his PhD from Cornell University, where his research focused on automated machine learning, artificial intelligence, and applied math. He lives in Washington, DC.