Everyone is talking about the transformational capabilities of generative AI—a subset of artificial intelligence that utilizes machine learning techniques to generate new content in a variety of forms, including but not limited to images, music, speech, and text. There is a great deal of interest in this technology among the data and analytics community. However, not all organizations are ready for it! There are significant challenges to overcome in order to prepare your enterprise’s data to become a launch pad for generative AI.
To make the most out of generative AI requires a robust data platform to fully utilize the capabilities of the models—including large language models (LLMs)—which are at the core of generative AI. This requires deploying scalable data and ML pipelines, creating extensible system architectures, developing modern data acquisition practices, and taking advantage of rapid innovations in AI technologies.
Join this webinar to learn from AWS, Impetus and TDWI experts about what it takes to be ready to leverage generative AI to boost business performance and unlock new sources of growth.
- Generative AI: What it means for organizations and use cases for it
- The platform approach to make your data ready for generative AI
- Essential AI/ML capabilities organizations require to leverage generative AI
- Need for robust data architectures, frameworks, and governance to implement generative AI models
- Taking into consideration responsible AI to ensure a high level of trust can be maintained
Dr. Ravishankar Rao Vallabhajosyula
Senior Director-Data Science
Senior Research Director, Data Management
Head of Data Analytics Partner GTM