MosaicML is a software company that helps customers train neural networks more easily, accurately, and efficiently.
According to our top-down research, the total addressable market for AI compute could scale from $25B today to $678B by 2030. However, training neural networks is currently inefficient, complex, and requires deep domain expertise.
Building on its popular MosaicML composer open-source project, the MoasicML Cloud abstracts away the complexity of resource orchestration and applies a variety of speedup methods to improve the efficiency of training neural networks. With the MosaicML Cloud, customers can train models up to 7x more efficiently, and the team believes they can further improve training efficiency by 4x annually. Customers such as the Stanford Center of Research on Foundation Models use MosaicML Cloud to train large models across a range of use cases. The company continues to push technical boundaries, recently setting a record for the fastest training run of ResNet-50 on MLPerf.
Founder and CEO Naveen Rao previously sold an AI startup to Intel for $400 million, scaled the Intel AI team from 50 to 1,300 people, and served on the Board of Directors at Block (Square).
We believe MosaicML could capture a significant share of AI compute spend as an AI training software layer that sits between customers and compute resources.
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