Put AI to Work
April 15-18, 2019
New York, NY

Schedule: Media, Marketing, Advertising sessions

1:45pm5:15pm Tuesday, April 16, 2019
AI Business Summit
Location: Beekman
Alex Siegman (Dow Jones), Kabir Seth (Wall Street Journal)
Average rating: **...
(2.50, 2 ratings)
Alex Siegman and Kabir Seth walk you through the steps necessary to appropriately leverage AI in a large organization. This includes ways to identify business opportunities that lend themselves to AI as well as best practices on everything from data intake and manipulation to model selection, output analysis, development, and deployment, all while navigating a complex organizational structure. Read more.
11:05am11:45am Wednesday, April 17, 2019
AI Business Summit, Case Studies
Location: Sutton North/Center
Lucy Wang (BuzzFeed), Swara Kantaria (BuzzFeed)
Average rating: *****
(5.00, 2 ratings)
As BuzzFeed’s content production and social networks grow, curation becomes increasingly difficult. The company first built publishing tools that let people work more efficiently, then built artificial intelligence tools that let people work more intelligently. Join Lucy Wang and Swara Kantaria to learn more about this evolution. Read more.
1:00pm1:40pm Wednesday, April 17, 2019
Case Studies, Machine Learning
Location: Sutton South
Cibele Halasz (Twitter), Satanjeev Banerjee (Twitter)
Average rating: *****
(5.00, 1 rating)
Twitter is a company with massive amounts of data, so it's no wonder that the company applies machine learning in myriad of ways. Cibele Montez Halasz and Satanjeev Banerjee describe one of those use cases: timeline ranking. They share some of the optimizations that the team has made—from modeling to infrastructure—in order to have models that are both expressive and efficient. Read more.
1:50pm2:30pm Wednesday, April 17, 2019
Implementing AI
Location: Trianon Ballroom
YU DONG (Facebook)
Average rating: ***..
(3.50, 2 ratings)
Yu Dong offers an overview of the why, what, and how of building a production-scale ML platform based on ongoing ML research trends and industry adoptions. Read more.
2:40pm3:20pm Wednesday, April 17, 2019
Implementing AI
Location: Trianon Ballroom
Yi Zhuang (Twitter), Nicholas Leonard (Twitter)
Average rating: ****.
(4.00, 3 ratings)
Twitter is a large company with many ML use cases. Historically, there have been many ways to productionize ML at Twitter. Yi Zhuang and Nicholas Leonard describe the setup and benefits of a unified ML platform for production and explain how the Twitter Cortex team brings together users of various ML tools. Read more.
4:05pm4:45pm Wednesday, April 17, 2019
Interacting with AI
Location: Regent Parlor
Kevin He (DeepMotion)
Average rating: ****.
(4.00, 2 ratings)
Digital character interaction is hard to fake, whether it’s between two characters, between users and characters, or between a character and its environment. Nevertheless, interaction is central to building immersive XR experiences, robotic simulation, and user-driven entertainment. Kevin He explains how to use physical simulation and machine learning to create interactive character technology. Read more.
4:05pm4:45pm Thursday, April 18, 2019
Machine Learning, Models and Methods
Location: Grand Ballroom West
Marcel Kurovski (inovex)
Average rating: *****
(5.00, 2 ratings)
Recommender systems support decision making with personalized suggestions and have proven useful in ecommerce, entertainment, and social networks. Sparse data and linear models are a burden, but the application of deep learning sets new boundaries and offers remarkable results. Join Marcel Kurovski to explore a use case for vehicle recommendations at Germany's biggest online vehicle market. Read more.
4:05pm4:45pm Thursday, April 18, 2019
Implementing AI
Location: Trianon Ballroom
Jaewon Lee (Naver/LINE), Sihyeung Han (Naver/LINE)
Jaewon Lee and Sihyeung Han walk you through implementing a self-trained dialogue model using AutoML and the Chatbot Builder Framework. You'll discover the value of AutoML, which allows you to provide better model, and learn how AutoML can be applied in different areas of NLP, not just for chatbots. Read more.
4:55pm5:35pm Thursday, April 18, 2019
Models and Methods
Location: Trianon Ballroom
Matthew REYES (Technergetics)
Average rating: *....
(1.00, 1 rating)
Matthew Reyes casts consumer decision making within the framework of random utility and outlines a simplified scenario of optimizing preference on a social network to illustrate the steps in a company’s allocation decision, from learning parameters from data to evaluating the consequences of different marketing allocations. Read more.