Enable pod-based GPU metrics in Amazon CloudWatch | Amazon Web Services
This post details how to set up container-based GPU metrics and provides an example of collecting these metrics from EKS pods.
Advanced (300)
Run multiple generative AI models on GPU using Amazon SageMaker multi-model endpoints with TorchServe and save up to 75% in inference costs | Amazon Web Services
Recently, generative AI applications have captured widespread attention and imagination. Customers want to deploy generative AI models on GPUs but at the same time are conscious of costs. SageMaker MMEs…
Elevating the generative AI experience: Introducing streaming support in Amazon SageMaker hosting | Amazon Web Services
We’re excited to announce the availability of response streaming through Amazon SageMaker real-time inference. Now you can continuously stream inference responses back to the client when using SageMaker real-time inference…
Deploy self-service question answering with the QnABot on AWS solution powered by Amazon Lex with Amazon Kendra and large language models | Amazon Web Services
Powered by Amazon Lex, the QnABot on AWS solution is an open-source, multi-channel, multi-language conversational chatbot. QnABot allows you to quickly deploy self-service conversational AI into your contact center, websites,…
MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD | Amazon Web Services
In this post, we describe how to create an MLOps workflow for batch inference that automates job scheduling, model monitoring, retraining, and registration, as well as error handling and notification…
Machine learning with decentralized training data using federated learning on Amazon SageMaker | Amazon Web Services
In this post, we discuss how to implement federated learning on Amazon SageMaker to run ML with decentralized training data.
Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift | Amazon Web Services
Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. Many practitioners are extending these…
Intelligent video and audio Q&A with multilingual support using LLMs on Amazon SageMaker | Amazon Web Services
Digital assets are vital visual representations of products, services, culture, and brand identity for businesses in an increasingly digital world. Digital assets, together with recorded user behavior, can facilitate customer…
Zero-shot and few-shot prompting for the BloomZ 176B foundation model with the simplified Amazon SageMaker JumpStart SDK | Amazon Web Services
Amazon SageMaker JumpStart is a machine learning (ML) hub offering algorithms, models, and ML solutions. With SageMaker JumpStart, ML practitioners can choose from a growing list of best performing and…
Build production-ready generative AI applications for enterprise search using Haystack pipelines and Amazon SageMaker JumpStart with LLMs | Amazon Web Services
This blog post is co-written with Tuana Çelik from deepset. Enterprise search is a critical component of organizational efficiency through document digitization and knowledge management. Enterprise search covers storing documents…