AGENDA

17:00 - 17:05 - Gathering
17:05-17:50 - Big data serving: Processing and inference at scale in real time - Jon Bratseth (VP Architect) @ Verizon Media
17:50-18:00 - Q&A

NOTE: The session will be delivered in English

Abstract:
The big data world has mature technologies for offline analysis and learning from data, but have lacked options for making data-driven decisions in real time.
When it is sufficient to consider a single data point model servers such as TensorFlow serving can be used but in many cases you want to consider many data points to make decisions.
This is a difficult engineering problem combining state, distributed algorithms and low latency, but solving it often makes it possible to create far superior solutions when applying machine learning.
This talk will explain why this is a hard problem, show the advantages of solving it, and introduce the open source Vespa.ai platform which is used to implement such solutions in some of the largest scale problems in the world including the world's third largest ad serving system.

Bio:
Jon Bratseth is a VP architect in the Big Data and AI group of Verizon Media, and the architect and one of the main contributors to Vespa.ai, the open big data serving engine.
Jon has 20 years experience as architect and programmer
on large distributed systems, and a frequent public speaker.
He has a master in computer science from the Norwegian University of Science and Technology.