John Schulman and Barret Zoph | ChatGPT and the Art of Post Training
HAI Seminar with John Schulman & Barret Zoph
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HAI Seminar with John Schulman & Barret Zoph
This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!
This session is specifically designed for full-time graduate students within one year of obtaining their PhD, as well as current postdoctoral scholars, fellows, and researchers.

This session is specifically designed for full-time graduate students within one year of obtaining their PhD, as well as current postdoctoral scholars, fellows, and researchers.
Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.
Abstract:
At this seminar, we’ll talk about the history and development process of ChatGPT, tracing its journey from initial prototypes to becoming a large-scale product and research effort. We’ll delve into the technical and operational challenges involved in post-training, including fine-tuning for conversational behavior, addressing alignment issues, and optimizing for large-scale deployment. Additionally, we’ll highlight some of the innovative solutions developed to tackle these challenges. To conclude, we’ll explore a set of open problems in the field, including ethical considerations, maintaining factual accuracy, and advancing the contextual understanding of conversational AI.

