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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.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Abstract: This training focuses on efficient strategies for using multiple GPUs and nodes. We will overview how to deploy strategies of data parallelism and model parallelism to scale to multiple GPUs, enabling faster training times and better model performance.
Speaker: Aastha Jhunjhunwala is a Solution Architect in the NVIDIA AI Enterprise team working with customers across different industries. She helps customers build optimized generative applications by leveraging NVIDIA hardware and software stack.
We are excited to announce a series of NVIDIA-led workshops designed to enhance your expertise in GPU computing. Whether you're a beginner or looking to deepen your skills, these sessions offer valuable insights and hands-on learning opportunities. Workshops are expected to be held on a monthly basis.
