Presented By
O’Reilly + Intel AI
Put AI to Work
April 15-18, 2019
New York, NY
Discover opportunities for applied AI
Organizations that successfully apply AI innovate and compete more effectively. How is AI transforming your business?
Be a part of the program—apply to speak by October 16.

Schedule: Computer Vision sessions

Add to your personal schedule
11:05am11:45am Wednesday, April 17, 2019
Models and Methods
Location: Regent Parlor
Siwei Lyu (University of Albany)
In this talk, I will first briefly review the evolution of techniques behind the generation of fake media, and then introduce several projects I was involved in digital media forensics for detection of fake media, with a special focus on some of our recent works on detecting AI-generated fake videos (DeepFakes). Read more.
Add to your personal schedule
2:40pm3:20pm Wednesday, April 17, 2019
Interacting with AI
Location: Regent Parlor
Matt Zeiler (Clarifai)
At the core of today's problems with image classification and deep learning lies one fundamental truth: most AI systems operate by choosing the path of least resistance – not the path of highest long-term quality. Matt Zeiler, founder and CEO of Clarifai, will discuss the company's approach to Closing the Loop on AI and employing techniques to counter the AI quality regression phenomenon. Read more.
Add to your personal schedule
4:05pm4:45pm Wednesday, April 17, 2019
Machine Learning, Models and Methods
Location: Grand Ballroom West
Bichen Wu (UC Berkeley)
For years we have been designing neural networks manually, but such design flow is extremely inefficient and designed networks are sub-optimal. To address this, we introduce an automated framework for neural network design and optimization. This approach generates superior neural network design and greatly reduces the need for manual efforts. Read more.
Add to your personal schedule
4:55pm5:35pm Wednesday, April 17, 2019
Implementing AI
Location: Rendezvous
Ted Way (Microsoft Corporation), Aishani Bhalla (Microsoft)
Deep neural networks (DNNs) have enabled breakthroughs in AI. Serving DNNs at scale has been challenging: fast and cheap? Won’t be accurate. Accurate and fast? Won’t be cheap. You’ll learn how Python and TensorFlow can be used to easily train and deploy computer vision models on Intel FPGAs with Azure Machine Learning and Project Brainwave, getting performance such as ResNet 50 in under 2 ms. Read more.
Add to your personal schedule
1:50pm2:30pm Thursday, April 18, 2019
AI Business Summit, Case Studies
Location: Sutton North/Center
Eric Oermann (Mount Sinai Health System), Katie Link (Allen Institute for Brain Science)
There is a significant interest in applying deep learning based solutions to problems in medicine and healthcare. This talk will focus on identifying actionable medical problems, and then recasting them as tractable deep learning problems and the techniques to solve them. Read more.
Add to your personal schedule
2:40pm3:20pm Thursday, April 18, 2019
Machine Learning, Models and Methods
Location: Grand Ballroom West
Anoop Katti (SAP)
We address understanding documents with 2D layout using machine learning. Examples of such documents are invoices, resumes, presentations etc. (in contrast to plain text documents like tweets, articles and reviews). We explore the shortcomings of the existing techniques and discuss a processing pipeline for 2D documents – the chargrid - pioneered by data scientists at SAP Read more.
Add to your personal schedule
2:40pm3:20pm Thursday, April 18, 2019
Case Studies, Machine Learning
Location: Sutton South
Alina Matyukhina (Canadian Institute for Cybersecurity)
Machine learning models are often susceptible to adversarial deception of their input at test time, which is leading to a poorer performance. In this session we will investigate the feasibility of deception in source code attribution techniques in real world environment. This session will present attack scenarios on users identity in open-source projects and discuss possible protection methods. Read more.
Add to your personal schedule
2:40pm3:20pm Thursday, April 18, 2019
Interacting with AI
Location: Regent Parlor
Behrooz Hashemian (Massachusetts General Hospital)
Artificial Intelligence has shown great potentials to revolutionize clinical medicine and health care delivery. However, incorporating these algorithms into clinical workflows faces a big challenge: convincing clinicians and regulators to trust a “black box” solution. In this talk, I present how we are making deep neural networks interpretable to provide evidences for clinical decisions. Read more.
Add to your personal schedule
2:40pm3:20pm Thursday, April 18, 2019
AI Business Summit, Case Studies
Location: Sutton North/Center
Enhao Gong (Subtle Medical), Greg Zaharchuk (Stanford University)
Clinical radiology is faced with several clinical issues: 1) improvement in imaging efficiency, 2) reduction of risks, 3) high imaging quality. Subtle Medical provides Deep Learning/AI solution, powered and accelerated by industry solution such as OpenVINO, to address these problems by enabling faster MRI, faster PET and low dose, providing real clinical and financial benefit to hospitals. Read more.
Add to your personal schedule
4:05pm4:45pm Thursday, April 18, 2019
Interacting with AI
Location: Mercury Rotunda
Humayun Irshad (Figure Eight)
In this talk, an active learning framework with crowd sourcing approach is introduced to solve a real-world problem in transportation and autonomous driving discipline, parking sign recognition, for which a large amount of unlabeled data is available. It generates an accurate model in a cost-effective and fast way to solve the parking sign recognition problem in spite of the unevenness of the data Read more.