Artificial Intelligence
Author: Yoshitaka Haribara
Yoshitaka Haribara is a Sr. Startup Machine Learning and Quantum Solutions Architect at AWS, working with startup customers to leverage AWS cloud including quantum technologies such as Amazon Braket. He holds a PhD in Mathematical Informatics from the University of Tokyo where he conducted research in the field of combinatorial optimization using quantum optics.
Unlocking Japanese LLMs with AWS Trainium: Innovators Showcase from the AWS LLM Development Support Program
Since its launch, the LLM Program has welcomed 15 diverse companies and organizations, each with a unique vision for how to use LLMs to drive progress in their respective industries. The program provides comprehensive support through guidance on securing high-performance compute infrastructure, technical assistance and troubleshooting for distributed training, cloud credits, and support for go-to-market. The program also facilitated collaborative knowledge-sharing sessions, where the leading LLM engineers came together to discuss the technical complexities and commercial considerations of their work. This holistic approach enabled participating organizations to rapidly advance their generative AI capabilities and bring transformative solutions to market. Let’s dive in and explore how these organizations are transforming what’s possible with generative AI on AWS.
Implementing hyperparameter optimization with Optuna on Amazon SageMaker
Preferred Networks (PFN) released the first major version of their open-source hyperparameter optimization (HPO) framework Optuna in January 2020, which has an eager API. This post introduces a method for HPO using Optuna and its reference architecture in Amazon SageMaker. Amazon SageMaker supports various frameworks and interfaces such as TensorFlow, Apache MXNet, PyTorch, scikit-learn, Horovod, Keras, […]