Get the app
Stanford Computational Antitrust
chevron_right
Episode 1: Gleaning Insight from Antitrust Cases Using Machine Learning (Massarotto & Ittoo)
Mar 5, 2021
35:40
share
Share
public
Creator website
AI Chapters
Episode notes
1.
Introduction
4min
info_outline
2.
How Much Did the Experiment Cost You?
4min
info_outline
3.
The Cost of a New Algorithm
3min
info_outline
4.
The Benefits of Unsupervised Learning in Antitrust
3min
info_outline
5.
Why Unsupervised Learning Is the Best Approach for AI Applications
3min
info_outline
6.
The Importance of Combining Data From the FTC and the DOJ in AI Applications
4min
info_outline
7.
The Importance of Clean Data in AI Algorithms
3min
info_outline
8.
Machine Learning and Antitrust in the Pharmaceutical Industry
5min
info_outline
9.
The Tall Order of Machine Learning Techniques
2min
info_outline
10.
The Future of Computational Antitrust
4min
info_outline
11.
The Future of AI in Antitrust
2min
info_outline
expand_more
Show more
In this episode 1, Thibault Schrepel discusses Stanford Computational Antitrust's newest article, "Gleaning Insight from Antitrust Cases Using Machine Learning" (with Giovanna Massarotto & Ashwin Ittoo).
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
Get the app
