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

Schedule: Data and Data Networks sessions

11:05am11:45am Wednesday, April 17, 2019
Deepashri Varadharajan (CB Insights)
Average rating: ***..
(3.80, 5 ratings)
CB Insights tracks over 3,000 AI startups across 25+ verticals. While every vertical has benefited from deep learning and better hardware processing, the bottlenecks and opportunities are unique to each sector. Deepashri Varadharajan explores what's driving AI applications in different verticals like healthcare, retail, and security and analyzes emerging business models. Read more.
1:00pm1:40pm Wednesday, April 17, 2019
Machine Learning, Models and Methods
Location: Regent Parlor
Danny Lange (Unity Technologies)
Average rating: *****
(5.00, 7 ratings)
Join Danny Lange to learn how to create artificially intelligent agents that act in the physical world (through sense perception and some mechanism to take physical actions, such as driving a car). You'll discover how observing emergent behaviors of multiple AI agents in a simulated virtual environment can lead to the most optimal designs and real-world practices. Read more.
11:05am11:45am Thursday, April 18, 2019
Thomas Marlow (Black Hills IP)
Average rating: *****
(5.00, 1 rating)
Three elements will control the AI market: technology, data, and IP rights. Leveraging rich patent data, Thomas Marlow uncovers the companies with the top patent holdings across the world in groundbreaking research and implementation technologies, surfacing insights into the sources and owners of AI technology as well as the hurdles and opportunities that those entering the field today face. Read more.
2:40pm3:20pm Thursday, April 18, 2019
Implementing AI
Location: Trianon Ballroom
Ryan Mukherjee (JHU/APL), Neil Fendley (JHU/APL)
Average rating: *****
(5.00, 1 rating)
While deep learning has led to many advancements in computer vision, most research has focused on ground-based imagery. Ryan Mukherjee and Neil Fendley offer an overview of functional Map of the World (fMoW), an ImageNet for satellite imagery built to address this issue, and explain how you can attack or defend these deep learning models. Read more.
4:05pm4:45pm Thursday, April 18, 2019
Interacting with AI
Location: Rendezvous
Humayun irshad (Figure Eight)
Average rating: **...
(2.00, 1 rating)
Humayun Irshad offers an overview of an active learning framework that uses a crowdsourcing approach to solve parking sign recognition—a real-world problem in transportation and autonomous driving for which a large amount of unlabeled data is available. The solution generates an accurate model, quickly and cost-effectively, despite the unevenness of the data. Read more.
4:05pm4:45pm Thursday, April 18, 2019
AI Business Summit, Case Studies
Location: Sutton North/Center
Tammy Bilitzky shares a case study that details lights-out automation and explains how DCL uses AI to transform massive volumes of confidential disparate data into searchable and structured information. Along the way, she outlines considerations for architecting a solution that processes a continuous flow of 5M+ “pages” of complex work units. Read more.
4:05pm4:45pm Thursday, April 18, 2019
Paco Nathan (derwen.ai)
Average rating: ****.
(4.33, 3 ratings)
Effective data governance is foundational for AI adoption in enterprise, but it's an almost overwhelming topic. Paco Nathan offers an overview of its history, themes, tools, process, standards, and more. Join in to learn what impact machine learning has on data governance and vice versa. Read more.
4:55pm5:35pm Thursday, April 18, 2019
Implementing AI
Location: Rendezvous
Dmitry Petrov (Iterative AI), Ivan Shcheklein (Iterative AI)
Average rating: ****.
(4.67, 3 ratings)
ML model and dataset versioning is an essential first step in the direction of establishing a good process. Dmitry Petrov and Ivan Shcheklein explore open source tools for ML models and datasets versioning, from traditional Git to tools like Git-LFS and Git-annex and the ML project-specific tool Data Version Control or DVC.org. Read more.