SmartChoices: Augmenting Software with Learned Implementations

We are living in a golden age of machine learning. Powerful models perform many tasks far better than is possible using traditional software engineering approaches alone. However, developing and deploying these models in existing software systems remains challenging. In this paper, we present SmartChoices, a novel approach to incorporating machine learning into mature software stacks easily, safely, and effectively. We highlight key design decisions and present case studies applying SmartChoices within a range of large-scale industrial systems.

PDF Abstract
No code implementations yet. Submit your code now

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here