About this session
Let's face it, the challenge of search today is indexing billions of entries while delivering relevant results quickly. Traditional keyword-based methods have limitations, leaving us searching for a better way to improve search. But what if we could use deep learning to revolutionize search? Imagine representing data as vectors, where the distance between vectors reflects similarity, and using Vector Similarity Search algorithms to search billions of vectors in milliseconds. It's the future of search, and it can transform text, multimedia, images, recommendations, and more. You won't want to miss our panel discussion, where we'll share how you can incorporate vector search into your own applications to harness deep learning insights at scale. Come join us and revolutionize search as we know it!
Speakers
Sam ParteePrincipal Applied AI Engineer at Redis
Sam is a Principal Engineer who helps guide the direction of AI efforts within Redis. Sam assists customers and partners deploying Redis in ML pipelines for feature storage, search, and inference workloads. His background is in high performance computing and machine learning systems.
Harmke AlkemadeAI Cloud Solution Architect at Microsoft
Harmke Alkemade is a Specialized AI Cloud Solution Architect at Microsoft, working in a global team that supports customers in various industries to use Azure services for high impact AI use-cases. Previously, she worked as a Cloud Solution Architect for Microsoft Netherlands in the Data&AI domain.
Jacky KohFounder at Relevance AI
Jacky Koh is the founder of Relevance AI, a low-code platform to help everyone analyze unstructured data 10x faster with embeddings and large language models. Previous to Relevance, Jacky was an app builder and award-winning data scientist, leading teams to deploy impactful machine learning algorithms.
Daniel SvonavaCo-Founder/CEO at Superlinked
Daniel is the CEO at Superlinked – an infrastructure product that helps evaluate, launch and operate real-time ML personalization for consumer apps. Previously, Daniel was a tech lead at YouTube where he built user modeling and ad performance prediction systems that guide the purchase process for $10B+.
Bob van LuijtCEO & Co-Founder at Weaviate
Bob van Luijt, CEO and Co-Founder of Weaviate, an open-source vector search engine. At just 15 years of age, Bob started his own software company in the Netherlands. He went on to study music at ArtEZ University of the Arts and Berklee College of Music, and completed the Harvard Business School Program.
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