Presented By O’Reilly and Intel Nervana
Put AI to work
September 17-18, 2017: Training
September 18-20, 2017: Tutorials & Conference
San Francisco, CA

Schedule: Verticals and applications sessions

Add to your personal schedule
1:30pm–5:00pm Monday, September 18, 2017
Location: Yosemite BC Level: Intermediate
Secondary topics:  Data and training, Transportation and autonomous vehicles
Mo Patel (Independent), Laura Froelich (Think Big Analytics, a Teradata Company)
Average rating: **...
(2.00, 3 ratings)
Computer vision is a key component in the artificial intelligence revolution. Assisted by deep learning, object detection allows automotive applications to make key navigation, guidance, and driving decisions to avoid collisions and navigation errors. Laura Froelich and Mo Patel demonstrate how to train deep learning models for object detection using publicly available transportation datasets. Read more.
Add to your personal schedule
11:55am–12:35pm Tuesday, September 19, 2017
Location: Yosemite A Level: Non-technical
Secondary topics:  Media
Paco Nathan (O'Reilly Media)
Average rating: ****.
(4.00, 4 ratings)
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.
Add to your personal schedule
11:55am–12:35pm Tuesday, September 19, 2017
Location: Imperial B Level: Beginner
Secondary topics:  Biopharmaceuticals, Deep learning
Blake Borgeson (Recursion Pharmaceuticals), Nan Li (Obvious Ventures)
Average rating: **...
(2.00, 1 rating)
Blake Borgeson and Nan Li offer a technical overview of how Recursion—a company that applies computer vision and machine learning to create a high-dimensional feature space in which to evaluate cellular health broadly across hundreds of disease states—leverages cellular phenotyping for drug discovery. Read more.
Add to your personal schedule
11:55am–12:35pm Tuesday, September 19, 2017
Location: Franciscan AB Level: Intermediate
Secondary topics:  Algorithms, Finance
Andy Steinbach (NVIDIA)
Average rating: ***..
(3.43, 7 ratings)
Andy Steinbach shares case studies and applications in artificial intelligence that are having an impact on financial markets. Read more.
Add to your personal schedule
1:45pm–2:25pm Tuesday, September 19, 2017
Location: Imperial A Level: Beginner
Secondary topics:  Data science and AI
Jeremy Stanley (Instacart)
Average rating: *****
(5.00, 2 ratings)
In the on-demand economy, if something doesn’t happen in real time, it’s too late. The secret ingredient that makes this possible? Data science. Jeremy Stanley explains how Instacart uses deep learning to enable its shoppers to become the most efficient shoppers ever, putting the company at the top of the food chart in the on-demand economy. Read more.
Add to your personal schedule
4:50pm–5:30pm Tuesday, September 19, 2017
Location: Imperial A Level: Intermediate
Secondary topics:  Deep learning, IoT (including smart cities, manufacturing, smart homes/buildings)
Jisheng Wang (Aruba, a Hewlett Packard Enterprise Company)
Average rating: *****
(5.00, 1 rating)
Recently, both deep learning and the IoT have attracted tremendous attention. Jisheng Wang shares firsthand experience in applying deep learning to solving some real-world enterprise IoT problems (e.g., IoT device identification and IoT security) and outlines some challenges for deep learning in enterprise applications, along with suggestions to overcome them. Read more.
Add to your personal schedule
11:55am–12:35pm Wednesday, September 20, 2017
Location: Yosemite A Level: Non-technical
Secondary topics:  Data science and AI, IoT (including smart cities, manufacturing, smart homes/buildings)
David Rogers (Sight Machine)
Average rating: ***..
(3.33, 3 ratings)
Artificial intelligence in manufacturing has been around for a long time, but are you aware of how it can make your operations more efficient and profitable? David Rogers 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.
Add to your personal schedule
4:00pm–4:40pm Wednesday, September 20, 2017
Location: Franciscan AB Level: Beginner
Secondary topics:  Algorithms, Enterprise adoption
Gang Wang (Intuit)
Average rating: ****.
(4.75, 4 ratings)
Taxes are one of consumers' most complex financial transactions, thanks to a tax code that is 80,000 pages long. Gang Wang explains how Intuit built the industry’s only Tax Knowledge Engine, a constraint-based engine that encodes changing financial regulations and provides the foundation for a host of artificial intelligence technologies that save customers time and money. Read more.
Add to your personal schedule
4:50pm–5:30pm Wednesday, September 20, 2017
Location: Franciscan AB Level: Non-technical
Secondary topics:  Finance, Healthcare
Average rating: *****
(5.00, 2 ratings)
Low-level task-based AI gets commoditized quickly, and more general AI is decades off. While most of the machine learning talent works in big tech companies, massive, timely problems lurk in every major industry outside tech. Bradford Cross explains how vertical AI startups leverage subject-matter expertise, AI, and unique data to deliver their product's core value proposition. Read more.