The current data stack is built on top of foundations laid down a decade ago for tabular data. But AI datasets are much more complex and workloads are much more diverse. Enterprises scaling AI in production often find data management prohibitively expensive and overly complicated.Lance columnar format is an open-source project designed to provide the new data foundations for AI, delivering much better performance and scalability for AI datasets, and makes them natively searchable using vector or full text queries.In this talk we’ll dive into the main challenges that AI data poses, how Lance format works, and the value it delivers to AI teams training models or putting applications into production.
The current data stack is built on top of foundations laid down a decade ago for tabular data. But AI datasets are much more complex and workloads are much more...
Quantization is an excellent technique to compress Large Language Models (LLM) and accelerate their inference. In this session, lets explore different quantization methods and techniques, the common libraries used and...
Literature reviews are a critical component of evidence-based medicine, serving as a structured approach to addressing clinical questions by systematically analyzing the breadth of published academic literature. However, traditional methods...
This talk draws from the paper “LLMs Will Always Hallucinate, and We Need to Live With This” and presents a critical analysis of hallucinations in large language models (LLMs), arguing...
We developed and evaluated an AI chatbot that provides reliable menopause information based on trusted, peer-reviewed sources, such as medical guidelines and position statements from The Menopause Society (TMS). The...
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