REVOLUTIONIZING DATA SCIENCE AND METHODS:A SHIFT FROM MODEL-CENTRIC TO DATA-CENTRIC
Abstract
My work explores a pivotal role which discuss about the shift from human-intensive pipelines towards autonomous self-healing architectures. It explains how Integration of Agentic AI and Synthetic Data helps to eliminate data scarcity. It also gives an introduction about "Recursive Validation" which is a framework that anchors synthetic training loops with "gold standard" real-world data to ensure model integrity🤖 📊.
Fields of Study & Subjects
Machine Learning and Data Classification
Artificial Intelligence Applications
Ethics and Social Impacts of AI
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 13 February 2026
- Language
- EN