2 minute read | June.27.2023
Databricks has entered into a definitive agreement to acquire MosaicML, a leading generative AI platform for approximately $1.3 billion. MosaicML relied on Orrick as its counsel – a role the firm has played through the entire lifecycle of the company.
The merger is one of the five largest announced in the AI & Machine Learning space in the first half of 2023.
MosaicML is known for its state-of-the-art MPT large language models, with over 3.3 million downloads of MPT-7B and the recent release of MPT-30B. MosaicML has showcased how organizations can quickly build and train their own state-of-the-art models using their data in a cost-effective way.
Databricks is a data and AI company, with more than 10,000 organizations worldwide relying on the Databricks’ Lakehouse Platform to unify their data, analytics and AI.
Together, Databricks and MosaicML will make generative AI accessible for every organization, enabling them to build, own and secure generative AI models with their own data. MosaicML’s platform will be supported, scaled, and integrated over time to offer customers a seamless unified platform. Databricks and MosaicML will give customers greater choice in building their own models, training models with their own unique data, and creating differentiating IP for their businesses.
“At MosaicML, we believe in a world where everyone is empowered to build and train their own models, imbued with their own opinions and viewpoints — and joining forces with Databricks will help us make that belief a reality,” said Naveen Rao, Co-Founder and CEO, MosaicML in a press release.
The Orrick team that advised MosaicML was led by Scott Iyama and Mark Seneca and included Justin Montis, Derek Jones, Eric Citizen, Yuan Tian, Melita Chan, Michael Ruiz, Sabrina Benyammi, Ewa Mykytyn, Craig Falls, Jennifer Clarke-Smith, Christy Matelis, Kristin Petersen, Steve Malvey, Kimberly Loocke, Daniel Yost, Jennifer Criss, Noa Dreymann, Adam Zuro, Jayla Goodloe, Shannon Yavorsky, Tori Downey, Michael Yang, Katherine Hogan, Lauren Guilford, Harry Clark, Maria Sergeyeva, Gregory Hume, Laura Becking, and Dina Dalessandro.