Scaling Thomson Reuters Language Model Research and Training with Amazon SageMaker Hyperpod
Thomson Reuters is a leader in business information services. They empower legal, government, tax, accounting, and compliance professionals worldwide. 2023 proved to be a generative AI inflection point, prompting Thomson Reuters to consider how their high-value, curated, data could improve on language models for customer-specific tasks. This compute-intensive research required specialized hardware, posing resource challenges. Enter Amazon SageMaker Hyperpod. Hyperpod allowed Thomson Reuters to scale to large clusters of NVIDIA A100 GPUs in a reliable and predictable manner. In this talk, we explore the journey Thomson Reuters took to enable their cutting edge research tasks and training of their foundational LLMs with Hyperpod.
ABOUT AWS
Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.
