Foundational machine learning research

Foundational Machine Learning Research is the dedicated core machine-learning research division of Thomson Reuters. We focus on research and development, with a particular emphasis on advanced algorithms and training techniques for large-language models (LLMs). Using a unique combination of algorithms across the entire training spectrum, we build the world’s best legal language models.

We work collaboratively with TR Labs’ — TR’s applied research division — academic partners at world-leading research institutions and domain experts with decades of experience. We experiment, prototype, test, and deliver ideas in the pursuit of smarter and more valuable models trained on an unprecedented wealth of data and powered by state-of-the-art technical infrastructure. Through our unique institutional experience, we have access to an unparalleled number of subject-matter experts involved in data collection, testing, and evaluation of trained models.