CHALLENGES

AI Accelerator projects are developing and prototyping challenges that engage the public to advance AI.

MULTI EARTH 2023 CHALLENGE
Project: Multimodal Vision for Synthetic Aperture Radar
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PUCKBOARD CHALLENGE
Project: AI-Assisted Optimization of Training Schedules
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MAGNETIC NAVIGATION
Project: Robust Neural Differential Models for Navigation and Beyond
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SEVIR: WEATHER FORECASTING
Project: The Earth Intelligence Engine
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A challenge is a means to engage academia, industry, and the public towards solving a common problem. In the context of Machine Learning, challenges have commonly involved open competitions organized around a publicly released data set. The team or individual developing the best Machine Learning model to learn from or analyze that data set wins! The world-wide collaboration resulting from such challenges has historically driven fundamental advances in many fields. In some communities, these challenges are also called “Hackathons.” Challenges such as the Datathon (DoD challenge) and the MagNav (public challenge) at JuliaCon play an important role in advancing diverse fields of AI research. A major goal of each AI Accelerator project is to develop and prototype challenges. AI Accelerator challenges are coordinated by Dr. Vijay Gadepally.

List of AI Accelerator Challenges

Anonymized Network Sensing Challenge (NEW)
AI Innovation in Space Challenge
MultiEarth 2023 Challenge
Pizza Simultaneous Localization and Mapping Challenge
MultiEarth 2022 Challenge
Puckboard Challenge
Magnetic Navigation Challenge
SEVIR: Weather Challenge
Datacenter Challenge
  • Project: Fast AI
  • Learn more about this challenge on DCC
RF Challenge
Maneuver ID Challenge
CogPilot Data Challenge
MORE ON NEW CHALLENGES COMING SOON!
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