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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!
As we navigate through this massive corpus of technical literature, four categories of ethical transgressions come to fore: Dataset curation, Modeling, Problem definitions and sycophantic tech-journalism. In this talk, we will explore specific examples in each of these categories with a strong focus on computer vision. The goal of this talk is to not just demonstrate the widespread usage of these datasets and models, but to also elicit a commitment from the attending scholars to either not use these datasets or models, or to insert an ethical caveat in case of unavoidable usage.