LIFT fine-tunes LLMs without labels using reinforcement learning, boosting performance on enterprise tasks.

Fine-tune embedding models on Databricks to enhance retrieval and RAG accuracy with synthetic data—no manual labeling required.

Meta rarely invests in startups, but it works with Databricks on the Llama open-source models that Meta trains.

Contribute to databricks/Compose-RL development by creating an account on GitHub.

Funding led by new investor Thrive Capital Company expects to cross $3B in revenue run rate and achieve positive free cash flow in fourth quarter

Building benchmarks is important because they shine a spotlight on the weaknesses of existing language models and so can guide the community on how to improve them.