AI & ML Research 24 Hours

Last updated: March 26, 2026, 11:30 AM ET

AI Workflow & Evaluation

Research is advancing efforts to integrate generative models across the complete data science pipeline, moving beyond simple code generation. New approaches utilize architectures like Codex and MCP to orchestrate complex operations linking disparate repositories such as Google Drive, GitHub, and Big Query into a single, continuous analytical workflow. Concurrently, practitioners are refining evaluation metrics for Retrieval-Augmented Generation (RAG) systems, recognizing that retrieval performance that appears strong on paper, measured by metrics like "Bits-over-Random," often translates poorly to agent behavior, suggesting retrieval quality needs deeper contextual evaluation for real-world deployment.