Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

DataRobot 7.0 Release Comes With Enhancements and Upgrades for Every Product in its Enterprise AI Platform

Boston-based DataRobot has revealed new upgrades to every product in its enterprise AI platform. Customers’ voices led to the development of these enhancements, which are designed to optimize the value seen through AI deployments and enable organizations to drive better business outcomes with AI.

“We are committed to helping enterprises experience the greatest value from their AI models”

Recommended AI News: Decentralized Oracle Solution Umbrella Network Expands Strategic Partnership with HashQuark

As per the shared press release, some notable enhancements include:

  • MLOps remote model challengers, which allow organizations to challenge any production model – no matter where it is running and regardless of the framework or language in which it was built. By analyzing how challenger models perform versus the current champion model on the exact same production data, companies can easily determine which model is best for them now or at any point in history – helping inform decisions about whether to keep or replace the current champion model, ensuring they always get the most accurate predictions possible.
MLOps Remote Model Challengers
Source: DataRobot
  • Choose your own forecast baseline, which lets companies compare the output of their forecasting models with predictions from DataRobot’s Automated Time Series product. Through this capability, organizations can feel confident that DataRobot is forecasting as expected and understand if DataRobot’s models are more or less accurate than their existing ones so they can leverage the best possible forecasts.
  • Visual AI image augmentation, available through DataRobot AutoML, which creates new training images from a company’s dataset by intelligently replicating and transforming the original images. As a result, organizations can improve the overall accuracy of their image models while reducing the need to manually capture and label new images, which is time-consuming and expensive.
Visual AI Image Augmentation
Source: DataRobot
  • Enhanced prediction preparation. DataRobot’s visual data prep capabilities empower organizations to quickly and easily prepare their data for model training. In release 7.0, customers can now use visual data prep to more easily s**** new data from models already deployed. This is because DataRobot’s Data Prep tools work seamlessly within its end-to-end platform, enabling companies to easily secure scored data and prediction explanations from any deployed model – ensuring full transparency and trusted AI.
Related Posts
1 of 40,589
Enhanced Prediction Preparation
Source: DataRobot

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

  • AutoML automatic bias and fairness testing is enhanced and now generally available.
  • Data Prep now contains enhanced improved APF monitoring, automatic date transformations, and a new elastic Spark-based infrastructure.
  • Automated Time Series offers monotonicity constraints and a new unsupervised anomaly over time model comparison feature.
  • MLOps now provides support for connecting to GitHub Enterprise and Bitbucket Server, in addition to offering new features that help organizations more effectively manage production models.

Recommended AI News: Tempered Combines Strengths with Nozomi Networks to Deliver Industry-Leading IoT/OT Security

The official blog post states, “Release 7.0 of DataRobot, provides innovation across our entire platform through enhancements to all the products you know and love. We’ve improved our scoring tools in Data Prep, added image augmentation to Visual AI, introduced customizable compliance reports in AutoML and AutoTS, and added a way to easily compare your forecasting models to ours. In MLOps, we’ve added the ability to challenge any model built in any language or framework, and deployed to any environment. Here are the major headlines for this exciting new release.”

While Nenshad Bardoliwalla, SVP of Product at DataRobot said, “We are committed to helping enterprises experience the greatest value from their AI models. Through ongoing engagement with our customers, we’ve developed an intimate understanding of the challenges they face, as well as the opportunities they have, with AI. Our latest platform release has been specifically designed to help them seize the transformative power of AI and advance on their journeys to becoming AI-driven enterprises.”

Recommended AI News: Dream Advisors Acquires Additional German Logistics Assets

Earlier in September 2020, DataRobot introduced major changes in the enterprise AI platform. It provided new capabilities for every step in the data science lifecycle, including next-level feature discovery, a new comprehensive autopilot mode to maximize accuracy, anomaly assessment insights governed approval workflows for MLOps, and much more.

As we are moving rapidly towards the digital world, businesses of all sizes have recognized the value of having AI-powered processes. Industry 4.0, Robotic Process Automation, Chatbots, Natural language Processing has risen up to handle the duties of automation. This value has driven the enterprise AI market to grow at around a CAGR of 52.17 %, during the forecast period of 2021 – 2026, according to Mordor Intelligence.

Comments are closed.