If you missed the webinar, you can find the recording Here .

As language models reshape how we interact with information, a new generation of AI-powered applications—language apps—is emerging. From chatbots to document search, these apps rely on vector embeddings to turn raw content into machine-understandable form. That shift opens the door to semantic search: retrieving meaning, not just matching words.

But embeddings need more than models—they need a place to live.

This talk introduces vector support in Db2, including native vector types, similarity search, and a growing set of vector operations. We’ll explore how these features enable enterprises to build scalable, secure, and intelligent applications—right where their data already lives.

Speaker:

Shaikh Quader

Shaikh Quader is the AI Architect and a Master Inventor at IBM Db2. He leads the development of AI features in Db2, including vector search and in-database machine learning. He joined IBM over 20 years ago as a software developer and moved into AI in 2016. His work spans engineering, applied research, and academic collaboration. He holds several patents, has published many peer-reviewed papers, and is pursuing a PhD on AI in relational databases. He writes about AI systems, AI careers, and technical leadership in his newsletter, AI Architect’s Playbook and LinkedIn.

#db2webinarseries
#globaldata-event