About Us

MosaicML exists to make ML training more efficient. We believe large scale ML should be available to everyone not just large companies.

The ML community is overwhelmed by the plethora of new algorithms in the literature and open source. It is often difficult to integrate new methods into existing code, due to reproducibility (Pineau et al, 2020) and complexity. In addition, methods should be charaterized according to their effect of time-to-train and interactions with systems.

For more details on our philosophy, see our Methodology and our founder’s blog.

We hope to contribute to the amazing community around ML Systems and ML Training efficiency.

Libraries

We’ve developed several tools to optimize and simplify the ML training process:

Library	Description
Composer	Contains a library of ML training efficiency methods, providing a modular approach to compose them together and train deep neural networks.
YAHP	Hyperparameter management tool