AI NEXTCon '19

SEATTLE | JAN. 23-26

register now
Meydenbauer Convention Center, Bellevue
For developers, by developers, AI NEXTCon is one of largest AI community-driven technology event specially geared to tech engineers, developers, data scientists to share, learn, and practice AI technology and how applying AI to solve engineering problems. The conference features a blend of inspirational keynotes, deep dive tech talks, hands-on workshops, tools/framework live demo, networking opportunity with like minded developers.

Speakers

Michael Jordan
Distinguished Professor
UC Berkeley
Swami Sivasubramanian
VP of AI
Amazon
Sumit Chauhan
CVP
Microsoft
Anima Anandkumar
Director of Machine Learning
NVIDIA
Danny Lange
VP of AI
Unity
Rajat Monga
Engineering Director
Google Brain
Luna Dong
Principal Scientist
Amazon
Peter Vajda
Research Manager
Facebook
Jonathan Huang
Research Scientist
Google Brain
Chester Chen
Head of Data Science
GoPro
Suqiang Song
Director of AI Platform
Mastercard
Yifeng Lu
Staff Engineer
Google Brain
Sujatha Sagiraju
Group Program Manager
Microsoft
Martin Gorner
Software Engineer
Google
Amy Unruh
Software Engineer
Google
Yuan Shen
CEO
Oneclick.ai
Andrew Ferlitsch
Engineer
Google AI
Chris Rawles
Machine Learning Engineer
Google
Yingnong Dang
Principal Data Scientist Manager
Microsoft
Miro Enev
Machine Learning Engineer
NVIDIA
Huaixiu Zheng
Senior Data Scientist
Uber
Jonathan Peck
Engineer
Algorithmia
Veda Shankar
Sr. Developer Advocate
OmniSci
Giorgio Natili
Engineering Lead
Amazon
Jason Arbon
CEO
test.ai
Denny Lee
Technical Product Manager
Databricks
Alexander Sergeev
Senior Engineer
Uber
Siyu Yang
Data Scientist
Microsoft
Bin Fan
Founding Member
Alluxio
Anoop Deoras
Lead AI Researcher
Netflix
Anish Das Sarma
Engineering Manager
Airbnb
Anand Raman
Director PM
Microsoft
Abhishek Singh
Staff Engineer
LinkedIn
Mohammad Rastegari
CTO
XNOR.ai

Topics

Computer Vision
Apply deep learning to understand images and videos
Speech Recognition
The breakthrough on speech recognition, voice input control, NLP
Deep Learning
Deep learning algorithms on CNN, RNN, RL and frameworks
Data Science/Analytics
Information retrieval, personal recommendation, training models
AutoML
Automatic machine learning and practical use cases
Machine Learning
Machine learning algorithms, how to scale machine learning.

Schedule

8:00amCheck In
9:20am Keynote
AI Innovation at Microsoft
Erez Barak, Senior Direct of AI, Microsoft
10:15am Coffee break and networking
10:30am Keynote
Ray: A Distributed Framework for Emerging AI Applications
Michael Jordan, UC Berkeley
11:30am Keynote
Trinity of AI: Interplay between data, algorithms and compute infrastructure
Anima Anandkumar, Director of Machine Learning, NVIDIA/Professor of Caltech
12:15pm Lunch break and networking
1:00pm - 1:50pm
Track 1
Efficient Deep Learning for Computer Vision
Peter Vajda, Facebook
Track 2
Uber's Deep-Learning Applications in NLP and Conversational AI
Huaixiu Zheng, Uber
Track 3
A new AI approach to help researchers and real business with AutoML
Yifeng Lu, Google Brain
Track 4
Evolution of GoPro Data Analytics Platform
Chester Chen, GoPro
2:00pm - 2:50pm
Track 1
Object Detection at Google
Jonathan Huang, Google Brain
Track 2
Automated ML at Microsoft
Sujatha Sagiraju, Microsoft
Track 3
Productionizing your Machine Learning Models
Jonathan Peck, Algorithmia
Track 4
Automatic Deep Learning Defines The Future of AI
Yuan Shen, OneClick.ai
2:50pm Coffee break and networking
3:10pm - 4:00pm
Track 1
Computer Vision for Wildlife Conservation
Siyu Yang, Microsoft
Track 2
Building a Broad Knowledge Graph for Products
Luna Dong, Amazon
Track 3
Cloud AutoML: Customize machine learning models with your own data
Andrew Ferlitsch, Google AI
Track 4
AI as a Service -- Build Shared Modern AI Service Platforms
Suqiang Song, MasterCard
4:10pm - 5:00pm
Track 1
AI for Software Testing
Jason Arbon, Test.AI
Track 2
Distributed Deep Learning with Horovod
Alexander Sergeev, Uber
Track 3
Personalizing the Netflix experience with deep learning based recommender systems
Anoop Deoras, Netflix
Track 4
Machine Learning for Digital Identity
Anish Das Sarma, Airbnb
5:30pm - 8:00pm: Evening Session (conference plus, workshop/training tickets holders only)
Dinner Reception with Speakers, Invited Guests.
8:30amCheck In
9:00am Keynote
Advancing Machine Learning in the Cloud
Swami Sivasubramanian, VP of AI, Amazon
9:40am Keynote
Democratizing AI with Tensorflow
Rajat Monga, Google Brain
10:20am Coffee break and networking
10:40am Keynote
On the Road to Artificial General Intelligence
Danny Lange, VP of AI, Unity
11:20am Keynote
Modernizing productivity through AI Infusion
Sumit Chauhan, CVP, Microsoft
12:00pm Lunch break and networking
1:00pm - 1:50pm
Track 1
Developing Intelligent applications with Azure Cognitive Services
Anand Raman & Chris Hoder, Microsoft
Track 2
Tensorflow, deep learning and modern convolutional neural nets
Martin Gorner, Google
Track 3 Moved to Track 4 at 2pm
Track 4
AI at the Edge: Micro-climate anomaly-detection and multi-spectral plant health monitoring
Miro Enev, NVIDIA
2:00pm - 2:50pm
Track 1
Push ML Workloads for Computer Vision to Resource Constrained Edge Devices
Mohammad Rastegari, Xnor.ai
Track 2
AIOps: Challenges and Experiences in Azure
Yingnong Dang, Microsoft
Track 3
GPU-Accelerated Instance for Interactive Exploratory Analysis
Veda Shankar, OmniSci
Track 4
Distributed Machine Learning Service and Android
Giorgio Natili, Amazon
3:00pm - 3:50pm
Track 1
MLflow: Accelerating the End-to-End ML lifecycle
Denny Lee, Databricks
Track 2
Data Highway for Machine Learning on the Cloud
Bin Fan, Alluxio
Track 3
Data and ML in Enterprise: Using Enterprise Search as a Case Study
Abhishek Singh, LinkedIn
9am - 12pm
Track 1
Serverless Machine Learning with TensorFlow (1)
by Chris Rawles, Google
*7 modules with tech talks, demo, and code labs. Course Outline
Track 2
Accelerating AI through Automated ML
by Sujatha Sagiraju, Microsoft
*hands-on workshop, with tech talks, demo, and code labs. Course Outline
12pm-1:30pmlunch break and networking
1:30pm - 4:30pm
Track 1
Serverless Machine Learning with TensorFlow (2)
by Chris Rawles, Google
*7 modules with tech talks, demo, and code labs. Course Outline

9:00am-12:00pm
Fast and lean data science with Tensorflow, Keras and TPUs
by Martin Gorner, Google
**hands-on workshop, with tech talks, demo, and code labs. Course Outline
12:00pm-1:30pmLunch
1:30pm-4:30pm
Build and Manage Machine Learning Pipelines
by Amy Unruh, Google
*hands-on workshop, with tech talks, demo, and code labs. Course Outline
*speakers and schedules are subject to change

Why Attend

Speakers

50+ tech lead speakers from Engineering Teams at Microsoft, Google, Amazon, Facebook, Uber, Linkedin, Pinterest, Nvidia, Twitter, and more.

Topics

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.

Networking

Connect with 500+ tech engineers, developers, data scientists; learn from peers, small-group discussions, office-hour, and lunch with speakers, happy hours.

Continious Learning

Continue to learn and practice AI post conference, join our free online AI learning group with 400+ tech speakers, 70,000+ tech engineers. Learn more.

AI Job Fair

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.

Learn and Play

While immersed with 4 days extensive learning, you will also have opportunity in exploring cool AI products, enjoy the coffee/snacks, lunch. also lucky draw with prize of free air tickets etc..

Sponsors

Venue

DATE:

January 23-26th, 2019

VENUE:

Main Conference (1/23-24):
Meydenbauer Convention Center
11100 NE 6th St, Bellevue, WA 98004
Workshop (1/25-26):
Hilton Garden Inn Bellevue Downtown
10777 NE 10th Street

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