No
Yes
View More
View Less
Working...
Close
OK
Cancel
Confirm
System Message
Delete
My Schedule
An unknown error has occurred and your request could not be completed. Please contact support.
Scheduled
Scheduled
Wait Listed
Personal Calendar
Speaking
Conference Event
Meeting
Interest
There aren't any available sessions at this time.
Conflict Found
This session is already scheduled at another time. Would you like to...
Loading...
Please enter a maximum of {0} characters.
{0} remaining of {1} character maximum.
Please enter a maximum of {0} words.
{0} remaining of {1} word maximum.
must be 50 characters or less.
must be 40 characters or less.
Session Summary
We were unable to load the map image.
This has not yet been assigned to a map.
Search Catalog
Reply
Replies ()
Search
New Post
Microblog
Microblog Thread
Post Reply
Post
Your session timed out.
This web page is not optimized for viewing on a mobile device. Visit this site in a desktop browser to access the full set of features.
2019 GTC San Jose
Add to My Interests
Remove from My Interests

S9810 - Machine Learning @ Bloomberg: Building on Kubernetes

Session Speakers
Session Description

The Bloomberg Terminal provides data, analytics, news, information, and communication for professionals in business, finance, government, and philanthropy. We'll discuss how we're using our internal machine learning platform to apply advanced AI and GPU-Accelerated compute to dozens of domains such as NLP, computer vision, time-series analysis, and personalization. We'll tackle the challenges involved in building a machine learning platform from scratch, and we'll introduce several machine learning projects at Bloomberg. We'll also explain how we convinced management to invest in scaling our ML infrastructure and how we evaluated and designed the core components of our ML platform. In addition, we'll review how our ML platform has changed our developer workflows and helped them solve real-world problems.


Additional Information
Finance - Deep Learning
AI Application Deployment/Inference, Finance - Deep Learning
General
All technical
Talk
50 minutes
Session Schedule