Databricks' ML stack includes: MLflow (the most popular open-source ML experiment tracking tool, created by Databricks), Unity Catalog (data governance and model registry), Mosaic ML's training infrastructure (used to train DBRX), and model serving endpoints. The platform handles the full workflow from raw data in a lakehouse to a deployed model, which is its key differentiator from point solutions.
DBRX is Databricks' open-weight LLM, using a Mixture of Experts architecture (132B total, 36B active). It was competitive with Llama 2 70B and Mixtral 8x7B at release. More than the model itself, DBRX demonstrated Databricks' ability to train frontier-scale models in-house, validating their Mosaic ML acquisition and positioning them as a credible AI lab alongside their platform business.
