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 seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.

This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.

As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.
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.

