Computer Vision
NLP
Deep Learning
Machine Learning
AutoML
Machine Learning in Production
| 8:00am | Check In | |||
| 9:00am Keynote | On Blending Machine Learning with Microeconomics Michael Jordan, UC Berkeley | |||
| 9:40am Keynote | On the Road to Artificial General Intelligence Danny Lange, VP of AI, Unity | |||
| 10:20am | Coffee break and networking | |||
| 10:45am Keynote | AI Innovation In Microsoft Erez Barak, Sr. Director, Microsoft AI | |||
| 11:25am Keynote | Travel in the AI-First World Luyuan Fang, Head of AI labs/VP, Expedia Group | |||
| 12:00pm | Lunch break and networking | |||
1:00pm - 1:50pm | ||||
| Track 1 | Developing and troubleshooting neural networks Cibele Montez Halasz, Apple | |||
| Track 2 | Taming the Transformer Lukasz Kaiser, Google Brain | |||
| Track 3 | Marquez: An Open Source Metadata Service for ML Platforms Willy Lulciuc & Shawn Shah, WeWork | |||
| Track 4 | Accelerating computer vision models with TensorFlow on FPGAs Ted Way, Microsoft | |||
| Track 5 | Google AI Training: Machine Learning and Image Processing 1 Sponsored by Google | |||
2:00pm - 2:50pm | ||||
| Track 1 | How Salesforce Einstein Leverages NLP to Deliver Customer Experience at Scale Peter Krmpotic, Salesforce | |||
| Track 2 | Deep Learning in Precision Agriculture Andrei Polzounov, Blue River Technology | |||
| Track 3 | Elastic Distributed Deep Learning Training at large scale Yonggang Hu, IBM Watson | |||
| Track 4 | Scalable enterprise AutoML Erin Ledell, H2O.ai | |||
| Track 5 | Google AI Training: Machine Learning and Image Processing 2 Sponsored by Google | |||
2:50pm -3:10pm: Coffee break and networking | ||||
3:10pm - 4:00pm | ||||
| Track 1 | Unleash Computer Vision at the Edge Steve Griset, alwaysAI | |||
| Track 2 | Machine Learning for Digital Identity Chirag Mahapatra, Airbnb | |||
| Track 3 | Building an AI Engine for Time Series Data Analytics Sanjian Chen & Jian Chang, Alibaba Group | |||
| Track 4 | Deep technical insights for AI engineering platform to deliver automate AI solutions at scale Suqiang Song, Mastercard | |||
| Track 5 | Google AI Training: Machine Learning and Image Processing 3 Sponsored by Google | |||
4:10pm - 5:00pm | ||||
| Track 1 | AI in Healthcare Anitha Kannan, Curai | |||
| Track 2 | Impact of ML on Perception for Autonomous Vehicles Sean Harris, Cruise | |||
| Track 3 | Taking Machine Learning Research to Production: Solving Real Problems Robert Crowe, Google | |||
| Track 5 | Google AI Training: Machine Learning and Image Processing 4 Sponsored by Google | |||
5:30pm - 8:00pm: Evening Session | ||||
| Dinner Reception | Speakers, Invited Guests, and ConferencePlus ticket/Workshop ticket holders only. | |||
| Community Event | A Night with AI & Data: In-stream data process, data Orchestration & Data Lake (Free to attend, open to public) | |||
| 8:30am | Check In | |||
9:30am - 10:20am | ||||
| Track 1 | Video Understanding at Facebook Matt Feiszli, Facebook | |||
| Track 2 | Introduction to Reinforcement Learning and Contextual Bandits Paul Mineiro, Microsoft | |||
| Track 3 | Model-based Candidate Generation for Recommendations at Twitter Jay Baxter, Twitter | |||
| 10:20am | Coffee break and networking | |||
10:50am - 11:40am | ||||
| Track 1 | Multivariate content optimization: Real-time recommendation and business insights Daniel Hill, Amazon | |||
| Track 2 | TransmogrifAI: efficient machine learning with Scala, Spark, and friends Chris Suchanek, Salesforce | |||
| Track 3 | How to Train Accurate Models with Less Data Bindu Reddy, RealityEngines.AI | |||
| 11:50am | Lunch break and networking | |||
12:45pm - 1:30pm | ||||
| Track 1 | Testing AI and Bias Jason Arbon, test.ai | |||
| Track 2 | Build and Integrate AI into Applications using the Cloud Nisha Talagala, Sindhu Ghanta, Pyxeda AI | |||
| Track 3 | Reinforcement learning with open-ended algorithms Rui Wang, Uber AI | |||
1:40pm - 2:25pm | ||||
| Track 1 | More Data Science with Less Engineering: ML Infrastructure at Netflix Ville Tuulos, Netflix | |||
| Track 2 | Algorithm and System for EHR-based Medical Decision-Making Pengtao Xie, Petuum | |||
| Track 3 | Tensorflow Lite - AI on the edge for Mobile and IoT Yunlu Li, Google | |||
2:35pm - 3:20pm | ||||
| Track 1 | Model versioning: Why, When and How Manasi Vartak, Verta.AI | |||
| Track 2 | Deep Learning for Speech Recognition Pranjal Daga, Cisco | |||
| Track 3 | Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeFlow, Airflow, and MLflow Chris Fregly, PipelineAI | |||
3:30pm - 4:30pm | ||||
| All | Women in AI Panel Yunlu Li (Google), Sandhya Ramu (LinkedIn), Nanda Vijaydev (HPE), Manasi Vartak (Verta AI), Luyuan Fang (Expedia) Nisha Talagala (Moderator from Pyxde AI) | |||
9am - 12pm | |
| Track 1 | Real World Reinforcement Learning in Action Tyler Clintworth, Microsoft Team *Hands-on workshop, with lectures, demo, and code labs. *In this workshop you will learn real world reinforcement learning and how applies to content personalization. We will walk you through setting up the service, writing your first application, and optimizing the policy using offline optimization. Workshop Details |
| 12pm-1:00pm | lunch break and networking |
1:00pm - 4:00pm | |
| Track 1 | AI and Machine Learning at Any Scale with Ray Robert Nishihara, UC Berkeley *hands-on workshop, with lectures, demo, and code labs. Workshop Details |
9am - 12pm | |
| Track 1 | Serverless Machine Learning with TensorFlow 2.0 (1) by Google Team *7 modules with lectures, live demo, and hands-on code labs. Course Outline |
| 12pm-1pm | lunch break |
1pm - 4pm | |
| Track 1 | Serverless Machine Learning with TensorFlow 2.0 (2) by Google Team *7 modules with lectures, live demo, and hands-on code labs. Course Outline |
50+ tech lead speakers from Engineering Teams at Microsoft, Google, Amazon, Facebook, Uber, Linkedin, Pinterest, Nvidia, Twitter, and more.
60+ deep dive tech topics and practicial experiences in machine learning, deep learning, computer vision, speech reconginition, NLP, data science and analytics. specially geared to tech engineers who want to grasp AI tech applied to their daily project.
Connect with 500+ tech engineers, developers, data scientists; learn from peers, small-group discussions, office-hour, and lunch with speakers, happy hours.
Continue to learn and practice AI post conference, join our free online AI learning group with 400+ tech speakers, 85,000+ tech engineers. Learn more.
The speakers and sponsors teams are hiring tech engineers, developers, data scientitst, machine learning engineers and algorithm engineers. Come to talk and connect to the hiring manager and tech lead of the teams.
