MIT Researchers Develop AI Risk Repository, RAGChecker Evaluates Retrieval-Augmented Generation Systems

MIT researchers release a robust AI governance tool to define, audit, and manage AI risks. Introducing RAGChecker, a fine-grained evaluation framework for diagnosing retrieval and generation modules in RAG systems. Plus, ControlNeXt revolutionizes image and video creation, and Microsoft Copilot takes productivity to new heights with generative AI.

Sources:
https://www.marktechpost.com/2024/08/17/mit-researchers-released-a-robust-ai-governance-tool-to-define-audit-and-manage-ai-risks/
https://www.marktechpost.com/2024/08/17/ragchecker-a-fine-grained-evaluation-framework-for-diagnosing-retrieval-and-generation-modules-in-rag/
https://www.marktechpost.com/2024/08/17/efficient-and-robust-controllable-generation-controlnext-revolutionizes-image-and-video-creation/
https://techcrunch.com/2024/08/17/microsoft-copilot-everything-you-need-to-know-about-microsofts-ai/

Outline:
(00:00:00) Introduction
(00:00:43) MIT Researchers Released a Robust AI Governance Tool to Define, Audit, and Manage AI Risks
(00:03:29) RAGChecker: A Fine-Grained Evaluation Framework for Diagnosing Retrieval and Generation Modules in RAG
(00:03:42) Efficient and Robust Controllable Generation: ControlNeXt Revolutionizes Image and Video Creation
(00:07:03) Microsoft Copilot: Everything you need to know about Microsoft’s AI