Crowdsourcing AI to solve real-world problems

AIcrowd enables data science experts and enthusiasts to collaboratively solve real-world problems, through challenges.

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Round 2: Completed

NeurIPS 2020: Procgen Competition

Measure sample efficiency and generalization in reinforcement learning using procedurally generated environments

1 Authorship/Co-Authorship

Misc Prizes : To be announced

#neurips #reinforcement_learning

OpenAI

Round 2: 15 days left

Seismic Facies Identification Challenge

3D seismic image Interpretation by Machine Learning

30,000 USD Prize Money

Misc Prizes : 8 x DJI Mavic Drones

SEAM AI

Round 2: 41 days left

Learning to Smell

Predicting smell of molecular compounds

CHF 6000 Prize Money

#fragrance

Firmenich

Round 2: Completed

NeurIPS 2020: Flatland Challenge

Multi-Agent Reinforcement Learning on Trains

4 Travel Grants

Misc Prizes : 1x RTX 2080, 3x Jetson Nano

#neurips #reinforcement_learning

SBB

Deutsche Bahn

SNCF

Round 3: 16 days left

#supervised_learning #instance_segmentation

Seerave Foundation

Round 1: 29190 days left

Spotify Million Playlist Dataset Challenge

A dataset and open-ended challenge for music recommendation research

Spotify

Round 1: 6 days left

#neurips #reinforcement_learning

MineRL Labs - Carnegie Mellon University

Round 1: 46 days left

Hockey: Player localization

$5,000 USD Prize Money

#classroom #hockey #computer_vision #localization

HAC Software Inc

Round 2: 63 days left

REAL 2020 - Robot open-Ended Autonomous Learning

Robots that learn to interact with the environment autonomously

1 Authorship/Co-Authorship

Misc Prizes : Free registrations for ICDL-2020 and ICDL-2021 conference

GOAL-Robots

"Crowdsourcing far exceeded our expectations - you not only get new solutions, but also a deeper insight to the problem you are trying to solve."

Erik Nygren, Deep Learning and Artificial Intelligence Research, SBB CFF FFS

Thanks to the agile structure of the platform, it was easy to design an ML challenge outside of the standard framework of the training/test data challenges. For new challenges, I would choose AIcrowd over other platforms.

Łukasz Kidziński, Postdoctoral Researcher, Stanford