The Data-AI Loop: How Circularity Drives Innovation

We’re excited to bring you another thought-provoking episode in Season 4, The Data-AI Loop: How Circularity Drives Innovation! Joining us today is Andrea Zinno, Data Evangelist at Denodo, who brings over three decades of experience in IT, covering Machine Learning, Digital Transformation, Advanced Data Analytics, and Innovation. In this episode, we explore the concept of the Data-AI Loop—a continuous cycle where data fuels AI, and AI, in turn, refines and enhances data, driving ongoing learning and adaptation. We’ll dive into key areas, including: Circularity Between Data & AI – How a continuous feedback loop strengthens AI models and prevents deterioration. Data Quality & AI Performance – The critical role of data quality, bias mitigation, and dataset relevance in AI training. Challenges in AI & Data Management – Addressing explainability, trust, hallucinations, and privacy concerns. AI’s Learning vs. Human Learning – Why AI models must continuously adapt and where they fall short compared to human cognition. Optimizing AI with Denodo – How companies can leverage data virtualization to streamline AI training and enhance efficiency. Tune in as we uncover the transformative power of the Data-AI Loop and its implications for organizations looking to stay ahead in the AI-driven world.

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