LMSYS and Kaggle have joined forces for an epic competition: predicting human preferences with machine learning! This competition aims to use machine learning to better understand how humans make choices, which can help improve AI technologies. Winners walk away with a cool $100,000. Are you up for the challenge?
What is the AI Challenge by LMSYS and Kaggle?
This competition challenges participants to predict user preferences between responses given by chatbots powered by advanced large language models (LLMs). Entrants will access a dataset filled with dialogues from the Chatbot Arena, where various LLMs respond to user prompts.
By crafting a model that can predict preferred responses, participants will enhance how chatbots understand and interact with humans, aligning more closely with human preferences. Models will be evaluated based on the log loss between the predicted probabilities and the actual outcomes, ensuring a rigorous assessment of prediction accuracy.
Important Dates
- Start Date: May 2, 2024
- Entry and Team Formation Deadline: July 29, 2024
- Final Submission Deadline: August 5, 2024 All deadlines are set at 11:59 PM UTC or or 5:29 AM IST. The organizers reserve the right to adjust the competition timeline as necessary.
Who can Participate and How to Participate?
If you have an interest in data science and machine learning you can join this competition. This competition is open to everyone, whether you’re a student, a professional data scientist, or just a tech enthusiast looking to test your skills, go ahead and register now.
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Steps to Participate in AI Challenge by LMSYS and Kaggle
- Visit the Kaggle competition page.
- Click on “Join the Competition” after reading all the competition rules and details carefully.
- Start using the provided datasets to build your models.
- Submit your predictions as per the guidelines on the Kaggle page.
Our Say
This competition is a great chance to contribute to the advancements in AI, particularly in understanding human behavior. Participants get to work with unique datasets and can compare their skills against other talented individuals in the field. Plus, the substantial prize money is a great incentive!
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