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AI WILDLIFE MONITORING

Cup - ybara
challenge 2025

An open competition to develop cutting-edge AI models for automated wildlife species detection.

Combining Machine Learning and real-world biodiversity data to push the boundaries of AI for conservation.

About the challenge

The problem

Tracking wildlife through camera trap footage is slow, time-consuming, and costly. Conservationists spend thousands of hours manually analyzing video to monitor species, delaying crucial actions.

The solution

AI can automate species detection, saving conservation teams time. This challenge aims to build models that classify wildlife in camera trap videos, supporting biodiversity efforts.

Technical details

By leveraging AI, we can reduce the hours spent manually analyzing camera trap footage and empower conservationists.

Data volume

Over 1,000 labeled and unlabeled video segments from Uruguayan wildlife.

Objective

Train AI models for video classification of local fauna.

Suggested approach

Experiment with multimodal LLMs or pre-trained models to enhance labeling accuracy.

Build solutions to transform wildlife monitoring

CHALLENGE FRAMEWORK
Key info
Follow our challenge roadmap from announcement to implementation
March 2025
March 2025
Official announcement.
Q2 2025
Q2 2025
Challenge launch | 6-week competition.
Q3 2025
Q3 2025
Winners announced, NGO deployment begins.

Shape the future of wildlife monitoring