DrivenData and Microsoft AI for Earth are launching an exciting new kind of challenge with a $20,000 prize pool.

The competition is now live and will be until January 22, 2020. Come join the fun!

Go to the Competition!


 Sign up for the competition as soon as it goes live on DrivenData. 


 Submit your code to predict animal labels for brand new imagery. 


Top-performing solutions earn a share of the $20,000 prize pool provided by Microsoft.

This challenge is unlike any we have run before.

More images, more animals, more impact

In this competition, participants will predict the presence and species of wildlife in new camera trap data from the Snapshot Serengeti project, which boasts over 3 million images.

Camera traps are motion-triggered systems for passively collecting animal behavior data with minimal disturbance to their natural tendencies. Camera traps are an invaluable tool in conservation research, but the sheer amount of data they generate presents a huge barrier to using them effectively. This is where AI can help!

There are two immediate challenges where efforts like this competition are needed:

  • Camera traps can't automatically label the animals they observe, creating an immense (and sometimes prohibitive) burden on humans to determine where and what type of wildlife are present.
  • Even when automated animal tagging models are available, the models that do exist don't generalize well across time and locations, severely limiting their usefulness with new data.

To address these opportunities, we're challenging data scientists, researchers, and developers from around the world to build the best algorithms for wildlife detection.

Just lion around.

Your models running in the cloud

The competition is designed with a few objectives in mind:

  • Innovation: Participants use state-of-the-art approaches in computer vision and AI and get live feedback on how well their solutions perform
  • Generalization: This challenge will feature more data and a more realistic holdout set to encourage more generalizable models
  • Execution: Models are trained locally and submitted to execute inference in the cloud - read on!
  • Openness: All prize-winning models are released under an open source license for anyone to use and learn from

This is a brand new kind of DrivenData challenge! Rather than submit your predicted labels, you'll package everything needed to do inference and submit that for containerized execution on Azure. By leveraging Microsoft Azure's cloud computing platform and Docker containers, we're moving our competition infrastructure one step closer to translating participants’ innovation into impact. 

We can't wait to run what you come up with! Sign up above to get notified when the competition is released!

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