Join us in San Francisco on September 26th for a Meetup

Hi Vespa Community,

Several members from our team will be traveling to San Francisco on September 26th for a meetup and we’d love to chat with you there.

Jon Bratseth (Distinguished Architect) will present a Vespa overview and answer any questions.

To learn more and RSVP, please visit:

https://www.meetup.com/SF-Big-Analytics/events/254461052/

Hope to see you!

The Vespa Team

Join us at the Machine Learning Meetup hosted by Zillow in Seattle on November 29th

Hi Vespa Community,

If you are in Seattle on November 29th, please join Jon Bratseth (Distinguished Architect, Oath) at a machine learning meetup hosted by Zillow. Jon will share a Vespa overview and answer any questions about Oath’s open source big data serving engine. Eric Ringger (Director of Machine Learning for Personalization, Zillow) will discuss some of the models used to help users find homes, including collaborative filtering, a content-based model, and deep learning.

Learn more and RSVP here.

Hope you can join!

The Vespa Team

Join us at the Big Data Technology Warsaw Summit on February 27th for Scalable Machine-Learned Model Serving

Online evaluation of machine-learned models (model serving) is difficult to scale to large datasets. Vespa.ai is an open source big data serving solution used to solve this problem and in use today on some of the largest such systems in the world. These systems evaluate models over millions of data points per request for hundreds of thousands of requests per second.

If you’re in Warsaw on February 27th, please join Jon Bratseth (Distinguished Architect, Verizon Media) at the Big Data Technology Warsaw Summit, where he’ll share “Scalable machine-learned model serving” and answer any questions. Big Data Technology Warsaw Summit is a one-day conference with technical content focused on big data analysis, scalability, storage, and search. There will be 27 presentations and more than 500 attendees are expected.

Jon’s talk will explore the problem and architectural solution, show how Vespa can be used to achieve scalable serving of TensorFlow and ONNX models, and present benchmarks comparing performance and scalability to TensorFlow Serving.

Hope to see you there!