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Twin revolutions at the start of the 21st century are shaking up the very idea of what it means to be human. Computer vision and image recognition are at the heart of the AI revolution. And CRISPR is a powerful new technique for genetic editing that allows humans to intervene in evolution.
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!
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.
Jennifer Doudna and Fei-Fei Li, pioneering scientists in the fields of gene editing and artificial intelligence, respectively, will be on stage discussing the ethics of scientific discovery.
Doudna, a professor of chemistry and molecular and cell biology at U.C. Berkeley, rocked the research world in 2012 when she and her colleagues announced the invention of CRISPR-Cas9, a technology that uses an RNA-guided protein found in bacteria to edit an organism's DNA quickly and inexpensively. Li is a professor of computer science at Stanford and co-director of the university's Institute for Human-Centered Artificial Intelligence (HAI). She served as director of Stanford’s AI Lab from 2013 to 2018, and during her sabbatical, she was Vice President at Google and served as Chief Scientist of AI/ML at Google Cloud. Li joined Stanford's faculty in 2009, and her main research areas are in machine learning, deep learning, computer vision and cognitive and computational neuroscience. She invented ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI.
Moderating the discussion will be Russ Altman, the Kenneth Fong Professor of Bioengineering, Genetics, Medicine, Biomedical Data Science and (by courtesy) Computer Science at Stanford. He is the past chairman of the Bioengineering Department at Stanford University. His primary research interests are in the application of computing and informatics technologies to problems relevant to medicine. He hosts the Stanford Engineering program The Future of Everything.
