MLSys: The New Frontier of Machine Learning Systems

TL;DR

MLSsys introduces a new conference to advance research at the intersection of systems and machine learning, addressing practical deployment challenges and fostering collaboration between the two fields.

Contribution

It establishes MLSys, a dedicated conference, to promote research on hardware, software, and metrics for ML systems, bridging the gap between systems and ML communities.

Findings

New conference MLSys launched to focus on ML systems.

Encourages collaboration between systems and ML researchers.

Highlights practical challenges in deploying ML models.

Abstract

Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains a significant obstacle, in large part due to the radically different development and deployment profile of modern ML methods, and the range of practical concerns that come with broader adoption. We propose to foster a new systems machine learning research community at the intersection of the traditional systems and ML communities, focused on topics such as hardware systems for ML, software systems for ML, and ML optimized for metrics beyond predictive accuracy. To do this, we describe a new conference, MLSys, that explicitly targets research at the intersection of systems and machine learning with a program committee split evenly between experts in systems and ML, and an explicit focus on topics at the intersection of the two.