Prerequisite: None
Laura Madsen
Co-Founder & Chief Blow-Stuff-Up Officer
Moxy Analytics
The rapid evolution of artificial intelligence (AI) technologies has revolutionized the way organizations leverage data to drive innovation and efficiency. Transitioning from predictive analytics to generative AI marks a significant leap, necessitating robust data management foundations to ensure success. This talk delves into the critical data management principles and practices required to facilitate this transformation.
Generative AI, with its ability to create novel content and solutions, demands a more sophisticated data management approach. This session will cover the enhanced data requirements for generative AI, including the necessity for large-scale, high-quality data sets, diverse data sources, and advanced data preprocessing techniques.
Attendees will gain a comprehensive understanding of the foundational data management practices required to navigate the complexities of transitioning from predictive analytics to generative AI, empowering them to harness the full potential of AI-driven innovation in their respective domains.
You Will Learn
- The importance of integrating diverse data sources
- How to ensure data consistency and reliability
- Practical insights and case studies that illustrate how effective data management underpins the development, deployment, and ethical operation of generative AI systems
Geared To
- Chief data and AI officers
- Data leaders
- Project managers