Accelerated Vector Search on NVIDIA GPU

Join SageCor Solutions for an exclusive session with Corey Nolet, a data scientist and principal engineer at NVIDIA, where he focuses on building and scaling vector search and machine learning algorithms to support extreme data loads at light speed

Unstructured data now makes up 80–90% of enterprise data and is growing three times faster than structured data. By the end of 2025, it’s projected to reach 175ZB. At the core of modern AI workloads is semantic search, powered by vector search on embeddings from unstructured data. This emerging field builds on past advances in data analytics, including approximate nearest neighbor algorithms.

Computing nearest neighbors is computationally intense, but recent breakthroughs in GPU hardware and algorithms are revolutionizing data exploration, analysis, and generative AI. This talk will demonstrate how important vector search has become to the current data processing landscape and discuss how it will continue to pave the way to a future where we can better utilize the growing volumes of unstructured data.

Please note new location at Dave and Buster's in Arundel Mills Mall. We have booked a private event room with lots of great appetizers!

Schedule:

• Networking and Refreshments: 5:30-6:00
• Speaker 6:00-7:00
• Q&A 7:00

Speaker BIO:

Corey Nolet is a principal engineer and data scientist at NVIDIA, where he focuses on building and scaling vector search and machine learning algorithms to support extreme data loads at light speed. Prior to working at NVIDIA, Corey spent over a decade building massive-scale exploratory data science & real-time analytics platforms for big-data and HPC environments in the defense industry. Corey holds Bs. & Ms. degrees in Computer Science. He is also working towards his Ph.D. in the same discipline, focused on the acceleration of algorithms at the intersection of graph and machine learning. Corey has a passion for using data to make better sense of the world.