HAI Weekly Seminar with Harikesh Nair
Digital Advertising: The Golden Age of Experiments
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Digital Advertising: The Golden Age of Experiments
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.
Running experiments is part and parcel of science and have lead to dramatic breakthroughs in fields such as biology, medicine and physics. Compared to these, business experiments – focused on outcomes and issues of interest to firms – are a relatively newer phenomenon but are now becoming increasingly prevalent. In some areas, such as digital advertising, experimentation has become a core feature of how business is run, so much so that the current decade in computational advertising represents a golden age of experimentation in the social sciences. This talk describes how online experimentation works in modern ad-systems, and how advertising experiments differ significantly from their natural science counterparts. I also discuss practical challenges in building experimental systems within technology-driven platforms and in driving adoption of experimentation-driven tools amongst advertisers and marketers using examples from the Chinese and US markets.
