I’m Chip Huyen, a writer and computer scientist. I grew up chasing grasshoppers in a small rice-farming village in Vietnam. I’m currently at Voltron Data, working on GPU-native data processing and open data standards (Ibis, Apache Arrow, Substrait). Previously, I built machine learning tools at NVIDIA, Snorkel AI, and Netflix. I also founded Claypot AI, which was acquired. I graduated from Stanford University, where I taught CS 329S: Machine Learning Systems Design. The lectures became the foundation for the book Designing Machine Learning Systems, which is an Amazon #1 bestseller in AI (very proud)! My new book AI Engineering will (hopefully) come out late 2024.
As data use cases become more complex, data platforms evolve to meet their needs. Data workloads run in different environments (local and production), in different modes (batch and streaming), and across different hardware (CPU and GPU). This talk introduces Ibis, an open-source project that allows users to work with different backends in different settings. We’ll go into how Ibis works under the hood, common use cases, and the roadblocks towards a unified API vision.
Starts: 11:55 AM
Ends: 12:40 PM
Our "Future of Machine Learning" panel will explore cutting-edge developments and emerging trends that are shaping the field. Leading experts will discuss advancements in areas such as deep learning architectures, reinforcement learning, and federated learning. The panel will delve into practical applications of ML. Join us for a fascinating look into the future of machine learning and its potential to revolutionize industries, scientific research, and our daily lives.
Starts: 1:40 PM
Ends: 2:30 PM