Splice Machine to Present on Feature Stores and Unified MLOps at Two Upcoming Virtual Conferences: QCon Plus and Data + AI Summit 2021

May 13, 2021

Founder and CEO, Monte Zweben, will discuss how feature stores and other MLOps advancements allow for scale-up ML models without increasing latency

San Francisco, CA, May 13, 2021 — Splice Machine, a real-time machine learning and AI solution provider, today announced that co-founder and CEO, Monte Zweben, will discuss the innovative new approaches to MLOps that feature stores have created at the QCon Plus virtual conference, May 17-May 28, 2021, and at Data + AI Summit 2021, being held virtually May 24-28, 2021.

“There’s a real challenge deploying multiple machine learning (ML) models into production. Managing multiple data sets, feature engineering pipelines, and models is incredibly complicated and takes considerable amounts of time and resources. By merging a scale-out hybrid OLAP/OLTP database, a feature store, and an evaluation store, companies can successfully scale models without the problems of inconsistency, poor accuracy, lack of transparency, and low productivity. It’s a new approach to MLOps that will help enterprises finally unlock the potential of their investment in ML,” said Zweben.

QCon Plus
Track: State of ML/AI Union
Unified MLOps: Feature Stores & Model Deployment
Monte Zweben, Co-Founder and CEO, Splice Machine
Wednesday, May 26, 2021
10:10 AM – 10:50 AM EDT

Data + AI Summit 2021
Unified MLOps: Feature Stores & Model Deployment
Monte Zweben, Co-Founder and CEO, & Jack Ploshnick, Customer Data Scientist, Splice Machine
Thursday, May 27, 2021
11:35 AM – 12:05 PM PDT

If you’ve brought two or more ML models into production, you know the struggle that comes from managing multiple data sets, feature engineering pipelines, and models. This talk will propose a whole new approach to MLOps that allows you to successfully scale your models, without increasing latency, by merging a database, a feature store, and machine learning.

Splice Machine is a hybrid (HTAP) database built upon HBase and Spark. The database powers a one of a kind single-engine feature store, as well as the deployment of ML models as tables inside the database. A simple JDBC connection means Splice Machine can be used with any model ops environment, such as Databricks.

The HBase side allows us to serve features to deployed ML models, and generate ML predictions, in milliseconds. Our unique Spark engine allows us to generate complex training sets, as well as ML predictions on petabytes of data.

In this talk, Monte will discuss how his experience running the AI lab at NASA, and as CEO of Red Pepper, Blue Martini Software, and Rocket Fuel, led him to create Splice Machine, while Jack will provide a quick demonstration of how it all works.

To set up a virtual meeting at the Data + AI Summit 2021 or QCon Plus, contact [email protected].

About Splice Machine

Splice Machine helps businesses see around corners by making it fast and easy to deploy AI applications. Our machine learning solutions predict outcomes in real time, enabling better decisions in the moment for industrial, financial, and healthcare companies. Splice Machine’s cutting-edge MLOps capabilities, including the only single-engine Feature Store, powers machine learning at scale. Companies can easily grow from a few models to thousands of models in production to proactively improve business impact. For more information on Splice Machine, visit www.splicemachine.com.