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
 
Nob Hill 2 & 3
Add word2vec and friends to your personal schedule
9:00am word2vec and friends Bruno Gonçalves (New York University)
1:30pm
Yosemite A
Add Probabilistic programming to your personal schedule
9:00am Probabilistic programming Vikash Mansinghka (MIT)
Yosemite BC
Add Introduction to reinforcement learning to your personal schedule
9:00am Introduction to reinforcement learning Marcos Campos (Bonsai)
Add Training vision models with public transportation datasets to your personal schedule
1:30pm Training vision models with public transportation datasets Mo Patel (Think Big Analytics), Laura Froelich (Think Big Analytics, a Teradata Company)
Imperial A
Add Getting started with TensorFlow to your personal schedule
9:00am Getting started with TensorFlow Yufeng Guo (Google), Amy Unruh (Google)
Add Building reinforcement learning applications with Ray to your personal schedule
1:30pm Building reinforcement learning applications with Ray Ion Stoica (UC Berkeley), Robert Nishihara (UC Berkeley), Philipp Moritz (UC Berkeley)
Imperial B
Add AI for business to your personal schedule
9:00am AI for business Jana Eggers (Nara Logics)
Add Here and now: Bringing AI into the enterprise to your personal schedule
1:30pm Here and now: Bringing AI into the enterprise Kristian Hammond (Narrative Science)
12:30pm Lunch sponsored by Intel Nervana | Room: Grand Ballroom B
Add AI 2017 Startup Showcase to your personal schedule
5:00pm AI 2017 Startup Showcase | Room: Grand Ballroom B
Add AI Dine-a-Round to your personal schedule
7:00pm AI Dine-a-Round | Room: Various locations
10:30am Morning Break | Room: Yosemite Foyer
3:00pm Afternoon Break | Room: Yosemite Foyer
9:00am-12:30pm (3h 30m) Implementing AI Algorithms, Case studies
word2vec and friends
Bruno Gonçalves (New York University)
Bruno Gonçalves explores word2vec and its variations, discussing the main concepts and algorithms behind the neural network architecture used in word2vec and the word2vec reference implementation in TensorFlow. Bruno then presents a bird's-eye view of the emerging field of "anything"-2vec methods that use variations of the word2vec neural network architecture.
1:30pm-5:00pm (3h 30m)
Session
9:00am-12:30pm (3h 30m) Implementing AI Data science and AI
Probabilistic programming
Vikash Mansinghka (MIT)
Probabilistic inference, a widely used, mathematically rigorous approach for interpreting ambiguous information using models that are uncertain or incomplete, is central to everything from big data analytics to robotics and AI. Vikash Mansinghka surveys the emerging field of probabilistic programming, which aims to make modeling and inference broadly accessible to nonexperts.
1:30pm-5:00pm (3h 30m) Implementing AI Data science and AI, Tools and frameworks
Topological data analysis as a framework for machine intelligence
Gunnar Carlsson (Ayasdi)
Topological data analysis (TDA) is a framework for machine learning that synthesizes and combines machine learning algorithms to identify the shape of data. The technique is responsible for several major breakthroughs in our understanding of science and business. Gunnar Carlsson offers an overview of TDA's mathematical underpinnings and its practical application through software.
9:00am-12:30pm (3h 30m) Implementing AI Algorithms, Data science and AI, Transportation and autonomous vehicles
Introduction to reinforcement learning
Marcos Campos (Bonsai)
Marcos Campos offers an overview of reinforcement learning, walking you through the various classes of reinforcement learning algorithms, the types of problems that can be solved with this technique, and how to build and train AI models using reinforcement learning and reward functions.
1:30pm-5:00pm (3h 30m) Verticals and applications Data and training, Transportation and autonomous vehicles
Training vision models with public transportation datasets
Mo Patel (Think Big Analytics), Laura Froelich (Think Big Analytics, a Teradata Company)
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.
9:00am-12:30pm (3h 30m) Implementing AI Deep learning, Tools and frameworks
Getting started with TensorFlow
Yufeng Guo (Google), Amy Unruh (Google)
Yufeng Guo and Amy Unruh walk you through training and deploying a machine learning system using TensorFlow, a popular open source library. Yufeng and Amy take you from conceptual overviews all the way to building complex classifiers and explain how you can apply deep learning to complex problems in science and industry.
1:30pm-5:00pm (3h 30m) Implementing AI Algorithms, Open source, Transportation and autonomous vehicles
Building reinforcement learning applications with Ray
Ion Stoica (UC Berkeley), Robert Nishihara (UC Berkeley), Philipp Moritz (UC Berkeley)
Ion Stoica, Robert Nishihara, and Philipp Moritz lead a deep dive into Ray, a new distributed execution framework for reinforcement learning applications, walking you through Ray's API and system architecture and sharing application examples, including several state-of-the art RL algorithms.
9:00am-12:30pm (3h 30m) Implementing AI Case studies, Enterprise adoption
AI for business
Jana Eggers (Nara Logics)
Now is the time for us to define roles and capabilities for AI in business. Jana Eggers demonstrates how to deliver on an AI project for business, walking you through defining your project, setting expectations, assembling your team, hunting for data, assessing capabilities, implementing it, and rinsing and repeating.
1:30pm-5:00pm (3h 30m) Implementing AI Enterprise adoption, Tools and frameworks
Here and now: Bringing AI into the enterprise
Kristian Hammond (Narrative Science)
Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Kristian Hammond shares a practical framework for understanding the role of AI technologies in problem solving and decision making.
12:30pm-1:30pm (1h)
Break: Lunch sponsored by Intel Nervana
5:00pm-6:30pm (1h 30m)
AI 2017 Startup Showcase
What new companies are at the leading edge of the AI space? Meet some of the best, most innovative founders as they demonstrate their game-changing ideas at the Startup Showcase.
7:00pm-9:00pm (2h)
AI Dine-a-Round
Looking for dinner plans Monday night? Sign-up to join a group of fellow attendees for the AI Dine-A-Round. Details on the restaurants and sign-ups are at registration, Yosemite Foyer - Ballroom Level, Tower 2. This is non-sponsored, so you are responsible for paying your portion of the bill on your own.
10:30am-11:00am (30m)
Break: Morning Break
3:00pm-3:30pm (30m)
Break: Afternoon Break