Building platforms for reproducible AI research
CloudCV is an open source cloud platform led by graduate students and faculty at the Machine Learning and Perception Lab at Georgia Tech, with the aim of building tools that for reproducible and accessible AI research and development. At CloudCV, we are building tools that enable researchers to build, compare, and share start-of-the-algorithms. We believe that one shouldn’t have to be an AI expert to have access to cutting-edge vision algorithms. Likewise, researchers shouldn’t have to worry about building a service around their deep learning models to showcase and share it with others.
We are building a platform called EvalAI as a scalable solution for the research community to fulfill the critical need of evaluating machine learning models. This will help researchers, students, and data scientists to create, collaborate, and participate in AI challenges organized around the globe. By simplifying and standardizing the process of benchmarking these models, we seek to lower the barrier to entry for participating in the global scientific effort to push the frontiers of machine learning and artificial intelligence, thereby increasing the rate of measurable progress in this domain.
CloudCV 2019 Projects
Enhance UI/UX of EvalAIThis project will focus on improving the existing UI of EvalAI to improve the experience of both challenge organizers and participants. Beyond this,...
EvalAi-ngxA web application for contesting online AI challenge. The front end has been improved for better user experience and performance.
Evaluating Submission Code in Docker ContainersThe rise of reinforcement learning based problems or any problem which requires that an agent must interact with an environment introduces additional...
Implement robust evaluation pipeline in EvalAICurrently, the submission worker that evaluates the challenge requires manual scaling. For auto-scaling, I'll be migrating it to AWS Fargate from...