December AI, Machine Learning & Data Science Meetup
December 7 at 10 AM PDT [1 PM EDT]
December 7, 2023 – 10:00 AM PDT (1:00 PM EDT)
Virtual / Zoom
- Building Yourself a Private Search System with Retrieval Augmentation with Haystack – Tuana Çelik at deepset
- Rise of the Intelligent Data Platform – Franco Patano at Databricks
- Scaling Similarity Search with USearch – Ash Vardanian at Unum Cloud
Building Yourself a Private Search System with Retrieval Augmentation with Haystack
In this talk we will have a look at Haystack, an open source LLM framework, and how we can use it to create custom, private search systems on our own data. We will look at how we can build retrieval augmented generative pipelines for our Notion pages, and how Haystack can help you create custom tooling for larger NLP applications.
Speaker: Tuana Çelik is a Lead Developer Advocate at deepset, where she focuses on the open-source NLP community. With a background in engineering, her main focus is to help the Haystack developer community.
Rise of the Intelligent Data Platform
At Databricks, we see organizations looking to leverage the power of AI, not only to deliver intelligent solutions, but to also have intelligent user interfaces. Join us as we delve into how lakehouse architecture forms the backbone of intelligent data platforms, integrating AI to enhance user interaction and self-management. Discover how this evolution is democratizing data and AI access for all data workers in modern organizations, paving the way for the next generation of data and AI enabled solutions.
Speaker: Franco Patano is a Strategic Data and AI Advisor at Databricks, where he collaborates with customers to understand their business needs, challenges, and goals, and help them leverage the power of Databricks to deliver data products that drive value, innovation, and growth.
Scaling Similarity Search with USearch
Vector and similarity search is increasingly critical in 2023, but most libraries struggle to fully utilize modern hardware due to issues rooted in their code architecture. Many rely on object-oriented programming, which reduces memory-efficiency and data-locality. Additionally, dependence on compilers for low-level optimizations fails to properly emit key AVX-512 and SVE Assembly instructions for x86 and Arm. My talk will dissect these and other pitfalls, and demonstrate how USearch innovates in areas like architecture and SIMD utilization to overcome them.
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