In the mid twenteeth century, a group of young French mathematicians from various universities felt the need to form a group to jointly reformulate mathematical coursework by grounding it in a single foundational theory for generability and rigour. These meetings led to the creation of several books, works and concepts that later went on to influence several branches of modern mathematics.
Based upon the same idea, we are working upon creating a biennial Bourbaki Congress for machine learning researchers from all around the world to establish a new set of baselines for mathematical rigour and generality in machine learning research.
At MLNerdie, instead of being a research camp committed to a particular set of available methodologies including deep learning, evolutionary computation or symbolic A.I., we focus on core challenges in each of these three areas.
Thus, we divide all machine learning research in three major areas - Building Intelligent Agents, Building Training Environments and Developing Automated Pipelines.
For building intelligent agents, we divide the research into Cognition, Language and Vision. For building training environments, we divide this research into single-agent and multi-agent systems and for developing automated pipelines, we break the area further into developing automated pipelines and emergence.
We are currently exploring a Micro Grants program to provide an opportunity to award $1K - 5K to machine learning researchers doing cutting edge research in line with the principles of Bourbaki Congress. The winners will also recieve free membership to the Congress.
All the candidates will work a group of assigned mentors on their proposed research via weekly remote calls and will be required to submit an end of project report.
One of the strong consideration factors as such would be community engagement on the proposed research topic via local MLNerdie Chapter events, social media or online bloposts.
MLNerdie is a cultural movement propagated around the world by some incredibly dedicated machine learning researchers who believe in making machine learning research more accessible to everyone. As such, they conduct local events, hackathons and conferences to propagate a rigorous research culture.
MLNerdie provides a platform for the A.I. industry, academics, post-graduate and published graduate students to present their research and collaborate to build strong machine learning culture and communities locally.Learn More