Earth Day. Explaining Green Machine Learning

April 17, 2020
· 1 min read

This post was originally part of the DataRobot Community. Visit now to browse discussions and ask questions about DataRobot, AI Platform, data science, and more.

Machine learning and (especially) deep learning have become increasingly more accurate in recent years. This has improved our lives in ways we couldn’t have imagined. As the AI revolution continues to evolve, more improvements are on the way.

The AI revolution isn’t without costs, though. The additional infrastructure needed to support AI has a negative impact on our environment. As models get more accurate, they typically emit more CO2; in fact, a 1% boost in model accuracy often means a 10x increase in model size and related CO2 emissions. As expected, these are some of the undesirable side-effects of the AI revolution.

Join our experts as they discuss:

  • How we can make AI “green” by reducing CO2 emissions.
  • How selecting the correct use cases and deploying the right models can make AI more efficient and accurate.


  • Oskar Eriksson (DataRobot, Customer Facing Data Scientist)
  • Jack Jablonski (DataRobot, AI Success Manager)

Now what?

After watching the learning session, check out this DataRobot article: Moving from Red AI to Green AI, Part 1: How to Save the Environment and Reduce Your Hardware Costs

Also, search the DataRobot public documentation for:

Explore Our Marketplace of AI Use Cases
Visit Now
About the author
Linda Haviland
Linda Haviland

Community Manager

Meet Linda Haviland
  • Listen to the blog
  • Share this post
    Subscribe to DataRobot Blog
    Thank you

    We will contact you shortly

    Thank You!

    We’re almost there! These are the next steps:

    • Look out for an email from DataRobot with a subject line: Your Subscription Confirmation.
    • Click the confirmation link to approve your consent.
    • Done! You have now opted to receive communications about DataRobot’s products and services.

    Didn’t receive the email? Please make sure to check your spam or junk folders.

    Newsletter Subscription
    Subscribe to our Blog