DataRobot 7.1 to take AI projects to the 'next level'

DataRobot doubles down on MLOps with remote model lifecycle management agents, automatic deployment reports, centralised prediction job scheduling, and scoring code in Snowflake, in addition to innovations across every other product in its Augmented Intelligence platform.

In its second major release of the year, DataRobot has introduced several product upgrades to its Augmented Intelligence platform designed to further democratise AI. Building on several enhancements announced at DataRobot’s AI Experience Worldwide last month, these latest additions will enable organisations to drive better business outcomes with AI and further accelerate customers’ time to value.

With its 7.1 Release, DataRobot introduces:

•MLOps Management Agents – DataRobot’s new MLOps Management Agents provide advanced lifecycle management for an organisation’s remote models. Management Agents understand the state of any remote model regardless of how they were created, or where they are running, and can automate various tasks including the retrieval model artifacts and deployment or replacement of models directly in their environment.

•Feature Discovery Push-Down Integration for Snowflake – Joint DataRobot and Snowflake customers can benefit from the automatic discovery and computation of new features for their models directly in the Snowflake Data Cloud without moving any data, making feature engineering faster, more accurate, and more cost-effective.

•Time Series Eureqa Model Enhancements – DataRobot Automated Time Series now runs its unique Eureqa forecasting models as part of the regular Autopilot process. Eureqa models are based on the idea that a genetic algorithm can fit different analytic expressions to trained data and return a mathematical formula as a machine learning model. With smart feature selection, Eureqa models dramatically reduce complexity and work well with both large and small datasets.

•No-Code AI App Builder – Introduced during the recent AI Experience event, the new No-Code AI App Builder allows customers to quickly turn any deployed model into a rich AI application without a single line of code. AI Apps can be built to help decision makers score new data, perform what-if scenarios, and even run hundreds of simulations to identify the ideal combination of input values to optimise the target outcome.

“We are in constant communication with our customers regarding the challenges they face when deploying AI, and as a result will tailor our updates based on their unique needs,” said Nenshad Bardoliwalla, SVP of Product at DataRobot. “We’re thoroughly committed to creating a platform that empowers every individual—from the most advanced data scientists to the everyday, non-technical business user—to take advantage of AI. By easing the model lifecycle process and cutting down time to value, this latest round of enhancements gives enterprises the tools they need to better build, manage, and see value from their AI projects.”

The latest platform also includes additional product upgrades, such as:

•Automated Data Prep for Time Series to solve for the most common issues with time series datasets, including gap handling and dataset aggregation.

•Nowcasting for Time-Aware Models to collect critical insights by estimating the present, and yet unknown, conditions of the target variable of interest.

•Automated AI Reports to summarise the most important findings of a modeling project to stakeholders in an easily consumable way.

•Prediction Jobs and Scheduling UI to manage and maintain prediction schedules in one place.


Healthcare professionals at Portsmouth Hospitals University NHS Trust are trialling an AI application designed to help detect lung cancers on chest x-rays sooner, in the first UK project set up using the Sectra Amplifier Service.
More than eight out of ten respondents (84%) in Kaleido Intelligence IoT survey, sponsored by Eseye, cited hardware design as the top challenge for initial IoT deployments.
VMware is empowering Centrica in its mission to help customers live sustainably, simply, and affordably by providing better visibility into the company’s cloud-native applications running on Amazon Web Services (AWS).
Red Box, the leading platform for voice capture, and EvaluAgent, the all-in-one quality and performance management platform, have joined forces to enable call centre managers to access high quality voice conversations and transform quality assurance (QA) processes through automation.
BT’s Digital unit is partnering with Dynatrace, making it a core component of a new service management stack for BT Group.
This year's VMware State of Observability report notes an increase in organizations recognizing the business benefits modern observability can bring. Learn about that and other key findings.
New AI-ready infrastructure-as-a-service solution enables customers to deploy AI models and applications near critical data sets, addressing data localization and compliance challenges.
Juniper Networks has published the findings of a global research project that shows a big increase in enterprise artificial intelligence (AI) adoption over the last 12 months, which is yielding tangible benefits to organisations. However, a shortage of human talent still exists, and governance policies continue to lack in maturity – both of which are needed to responsibly manage AI’s growth when considering privacy issues, regulation compliance, hacking and AI terrorism.