How DataBricks' $1.3B acquisition of MosaicML reveals the latest trend in Generative AI : Co-Piloting for the Enterprises

MosaicML CTO Hanlin Tang, left, with CEO Naveen Rao, founding adviser Michael Carbin and Jonathan Frankle, chief scientist. Photo Credit: MosaicML

All enterprises would like to have their own version of ChatGPT where their employees for example could ask questions and get answers. That’s where all the actions are right now. Every enterprise would buy that tomorrow.

Every employee in the company could ask questions to the AI model the way you can ask ChatGPT questions and it would have all the enterprise data and it would also understand their permissions and have all the security settings so that only there I feel I could get the right information. That’s the kind of intelligence they want to unlock. 

The new AI capabilities are becoming the co-pilots for CEOs. The sales team is gonna have their own co-pilot. I think the marketing team’s gonna have their own co-pilot. Customer support will have it

David Sacks ( Craft Ventures ) explained the catalyst behind the DataBricks/MosaicML deal in the All-In Podcast

On June 26, 2023, Databricks announced an agreement to acquire generative AI startup MosaicML in a deal valued at roughly $1.3 billion, a move aimed at capturing the fast-growing demand from businesses to build their own ChatGPT-like tools.

With such acquisition, Databricks, a San Francisco-based data storage and management startup, can now combine its AI-ready data-management technology with MosaicML’s Large Language Models (LLMs) platform, enabling businesses to build low-cost language models themselves with proprietary data. 

Currently, most businesses rely on third-party language models trained on troves of publicly available data accessed online. Those who desire to build their generative AI apps on top of these ready-made language models would license from companies such as OpenAI. Driven by strong commercial demand for these models, the generative AI market has expanded dramatically—creating openings for startups like MosaicML which can offer similar AI models, but at lower cost and customized with a company’s data.

The Generative AI Toolset for the Enterprise

Before using the language models, enterprises first need to capture and label the data so that they can be classified for model training. When the data is ready, the developers would need to look for the best language models for their needs. Many of these models are open-sourced and can be found on sites such as Hugging Face. MosaicML provides an end-to-end toolchain solution where businesses can capture, customize, store, label, and train their data at a low cost. Using MosaicML’s inference, enterprises can now build Generative AI apps for their various departments. With such Co-Pilots at their disposal, everyone can now ask questions about their businesses in the same way that we ask questions to ChatGPT.

Credit: Craft Ventures’ investment memo for MosaicML

Co-Pilot for the Healthcare Enterprises

Witnessing the power of ChatGPT through its ingestion of publicly available data, we realize that there will be tremendous untapped opportunities for different vertical industries. As shown in the ChatGPT-Patient exchanges, the chatbot, when built with all the various sources of data, can help prescribe a very personalized treatment plan, delivering great value to the healthcare industry.

Good AI’s blog post “From ChatGPT to Precision Medicine, improving lives one neuron at a time”

With the marriage between Databricks and MosaicML, we are one step closer to a world where enterprises can fully unlock the power of Generative AI.  As a healthcare investor, Good AI is very excited that healthcare organizations such as hospitals and clinics can now build an aggregate foundation model from the various sources of patient data, enabling physicians to prescribe personalized treatment for their patients.