Title

AWS re:Invent 2022 - Train ML models at scale with Amazon SageMaker, featuring AI21 Labs (AIM301)

Summary

• Gal Oshry, a product manager at AWS, and Emily Weber, Principal ML Specialist SA at AWS, discuss the benefits and challenges of large-scale machine learning and how Amazon SageMaker accelerates training.
• They highlight the evolution of machine learning models, particularly in NLP and computer vision, and the improvements due to algorithmic advancements, larger datasets, and increased compute power.
• SageMaker's capabilities in distributed training, infrastructure management, and cost-effectiveness are emphasized.
• A case study of training a stable diffusion model on SageMaker is presented, showcasing the platform's ability to handle large-scale jobs efficiently.
• Dan Padnos from AI21 Labs shares how their large language models are transforming reading and writing experiences and the development of their Jurassic-1 models.
• AI21 Labs utilized SageMaker for training their mid-size model, Jurassic-1 Grande, which offers a balance between cost and performance.
• The session concludes with resources for getting started with SageMaker and an announcement of AI21's Jurassic-1 models being available on SageMaker Foundation Model Jumpstart.

Insights

• Large-scale machine learning models have seen significant improvements in recent years, with generative AI creating near-realistic outputs.
• The scaling laws suggest that increasing the size of data and models can lead to better results, but challenges such as hardware limitations, orchestration, big data management, algorithm scaling, and costs need to be addressed.
• Amazon SageMaker provides a comprehensive solution for these challenges, offering the latest hardware, managed infrastructure, and optimized frameworks and libraries for distributed training.
• The case study of training stable diffusion on SageMaker demonstrates the platform's ability to handle large-scale jobs, with features like job parallelism, data parallelism, and model parallelism.
• AI21 Labs' experience with SageMaker shows that it is possible to train large language models efficiently and cost-effectively, with their Jurassic-1 Grande model being a testament to this.
• The availability of AI21's Jurassic-1 models on SageMaker Foundation Model Jumpstart opens up opportunities for organizations to integrate large language models into their workflows while maintaining data security within their SageMaker environment.