Put AI to work
June 26-27, 2017: Training
June 27-29, 2017: Tutorials & Conference
New York, NY

Schedule: Verticals and applications sessions

AI is no longer confined to the worlds of research and technology. Learn how pioneers and entrepreneurs now use AI to transform industries such as finance, healthcare, media, and science.

11:55am12:35pm Wednesday, June 28, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Financial services
Aida Mehonic (The Alan Turing Institute)
Average rating: ****.
(4.67, 3 ratings)
Deploying AI across business functions brings benefits that range from the prosaic to game changers, which in turn also depend on the overall digital and data maturity of the organization. Aida Mehonic shares a case study of an investment firm undergoing an AI transformation across several business units, including trading, reporting, and marketing. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Grand Ballroom West Level: Non-technical
Secondary topics:  Machine Learning, User interface and experience, Vision
Rana el Kaliouby (Affectiva)
Average rating: *****
(5.00, 2 ratings)
Emotion AI is a branch of artificial intelligence that brings emotional intelligence to AI systems. Rana el Kaliouby reviews the state of emotion AI, its commercial applications, its underlying deep learning methods, and the research roadmap, which includes multimodal emotion recognition and the idea of an emotion chip. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Financial services, Machine Learning
Ron Bodkin (Google), Nadeem Gulzar (Danske Bank Group)
Average rating: ****.
(4.33, 3 ratings)
Fraud in banking is an arms race with criminals using machine learning to improve their attack effectiveness. Ron Bodkin and Nadeem Gulzar explore how Danske Bank uses deep learning for better fraud detection, covering model effectiveness, TensorFlow versus boosted decision trees, operational considerations in training and deploying models, and lessons learned along the way. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Location: Sutton South/Regent Parlor Level: Beginner
Secondary topics:  Financial services, Machine Learning, Natural Language
Francisco Webber (Cortical.io)
Average rating: *****
(5.00, 1 rating)
Financial industries are under increased pressure due to regulations that demand extended information management capabilities. Information largely consists of text data, which forces companies to increase headcount to keep up with the growing workload. Francisco Webber demonstrates how Cortical.io’s semantic folding, a neuroscience-based approach to NLU, helps automate these uses cases. Read more.
11:05am11:45am Thursday, June 29, 2017
Location: Gramercy East/West Level: Beginner
Secondary topics:  Health care, Machine Learning, Natural Language
Michael Nova (Pathway Genomics)
Average rating: *****
(5.00, 1 rating)
Precision medicine is largely a big data and systems problem, especially with many different types of "siloed" healthcare information, such as lab results, genetic tests, IoT and wearables data, and insurance information. Michael Nova explains why cognitive computing and artificial intelligence that can dynamically learn using any healthcare data will dramatically impact precision healthcare. Read more.
11:55am12:35pm Thursday, June 29, 2017
Location: Murray Hill E/W Level: Beginner
Yarin Gal (University of Cambridge)
Average rating: ***..
(3.43, 7 ratings)
Yarin Gal shares a new theory linking Bayesian modeling and deep learning and demonstrates the practical impact of the framework with a range of real-world applications. Yarin also explores open problems for future research—problems that stand at the forefront of this new and exciting field. Read more.
1:45pm2:25pm Thursday, June 29, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Health care
Garrett Goh (Pacific Northwest National Lab)
Garrett Goh demonstrates how to use deep learning to construct computational chemistry models that compare favorably to existing state-of-the-art models developed by expert practitioners—with virtually no expert knowledge—proving the potential of AI assistance to accelerate the scientific discovery process from a typical span of years to a matter of months. Read more.
2:35pm3:15pm Thursday, June 29, 2017
Location: Beekman Level: Non-technical
David Rogers (Sight Machine)
Average rating: ***..
(3.50, 2 ratings)
Join David Rogers to learn how AI can make your operations more efficient and profitable. David explains how existing technologies like the digital twin approach, advanced decision making, and downtime cause detection have primed manufacturing for a profitable and efficient future. Read more.
4:50pm5:30pm Thursday, June 29, 2017
Location: Gramercy East/West Level: Non-technical
Secondary topics:  Machine Learning, Media, Natural Language
Paco Nathan (derwen.ai)
Paco Nathan explains how O'Reilly employs AI, from the obvious (chatbots, case studies about other firms) to the less so (using AI to show the structure of content in detail, enhance search and recommendations, and guide editors for gap analysis, assessment, pathing, etc.). Approaches include vector embedding search, summarization, TDA for content gap analysis, and speech-to-text to index video. Read more.