Generative AI, driven by the rapid adoption of large language models (LLMs), has become a global phenomenon. TDWI research indicates a growing interest in this technology, particularly among companies aiming to leverage their own data for building solutions and extracting value from generative AI. To realize this aspiration, your organization must strategically architect its on-premises or cloud infrastructure and advance its data estate. This will enable your organization to tap into the vast potential of generative AI while prioritizing data privacy and mitigating risks associated with LLMs.
This foundation is crucial for the development and scalability of contemporary chatbots and summarization applications and supports future applications encompassing video, audio, verbal content, sensor data, and other diverse and complex data formats.
The fundamental question is “How can you position your organization to become generative AI-ready and stay ahead of the curve?” Join this Impetus and TDWI fireside chat to explore the principles for implementing generative AI in industry-specific solutions. Topics covered include:
- Establishing essential generative AI foundations to elevate enterprise readiness
- Design principles for structuring your generative AI infrastructure
- Governance and responsible AI guidelines for mitigating risks
- Enhancing generative AI with domain-specific knowledge
- Scaling generative AI adoption across your organization
- Prominent use cases, such as enterprise search
- Facilitating new customer experiences through application integration
VP, GTM Strategy- Unified Data Platforms
Dr. Ravishankar Rao Vallabhajosyula
Senior Director-Data Science