Ryan Orban: Panel Data, Code, and Life with LLMs
Nick Hill: Efficiently serving LLMs at scale
Chris Matteson: Cost and Performance Optimization of LLM Inferencing
Charles Frye: Parallel Processors: Past & Future Connections Between LLMs and OS Kernels
Mihai Maruseac: Model transparency for AI/ML security
Graham McNicoll: Open Source Warehouse Native A/B Testing
Miguel Bernadin: Panel Data, Code, and Life with LLMs
Eric Peter: Panel Data, Code, and Life with LLMs
Nate Slater: What problems should enterprises actually trust an LLM to solve?
Nikita Shulga: How to help yourself and ML community make PyTorch better.
Pete Skomoroch: Panel Data, Code, and Life with LLMs
Boyang Jerry Peng: Latency goes sub-second in Apache Spark Structured Streaming
Shea Hawkins:Open-Source OLAP on Open-Source Data Warehouses
Mihai Maruseac: Model transparency for AI/ML security
Karl Wehden: An introduction to Open Accelerated Discovery: An integrated framework for computation
Stefan Krawczyk: Hamilton: Natively bringing SWE best practices to python data transformations
Yingjun Wu: Revolutionizing Text Transformation: Going Beyond Standard SQL with LLM
Wangda Tan: Revolutionizing Text Transformation: Going Beyond Standard SQL with LLM
Ryan Wright: Streaming Graph Search with Quine
Manasi Vartak: Can AI Write Its Own Story? Unveiling the Power of Self-Documenting AI