Gemma is now available in Amazon SageMaker JumpStart
Today, we’re excited to announce that the Gemma model is now available for customers using Amazon SageMaker JumpStart. Gemma is a family of language models based on Google’s Gemini models,…
Amazon SageMaker
Set up cross-account Amazon S3 access for Amazon SageMaker notebooks in VPC-only mode using Amazon S3 Access Points
Advancements in artificial intelligence (AI) and machine learning (ML) are revolutionizing the financial industry for use cases such as fraud detection, credit worthiness assessment, and trading strategy optimization. To develop…
Efficiently fine-tune the ESM-2 protein language model with Amazon SageMaker
In this post, we demonstrate how to efficiently fine-tune a state-of-the-art protein language model (pLM) to predict protein subcellular localization using Amazon SageMaker. Proteins are the molecular machines of the…
Automate Amazon SageMaker Pipelines DAG creation
Creating scalable and efficient machine learning (ML) pipelines is crucial for streamlining the development, deployment, and management of ML models. In this post, we present a framework for automating the…
Supercharge your AI team with Amazon SageMaker Studio: A comprehensive view of Deutsche Bahn’s AI platform transformation
AI’s growing influence in large organizations brings crucial challenges in managing AI platforms. These include developing a scalable and operationally efficient platform that adheres to organizational compliance and security standards.…
How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker
This is a guest post written by Axfood AB. In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence…
Streamline diarization using AI as an assistive technology: ZOO Digital’s story
ZOO Digital provides end-to-end localization and media services to adapt original TV and movie content to different languages, regions, and cultures. It makes globalization easier for the world’s best content…
Run ML inference on unplanned and spiky traffic using Amazon SageMaker multi-model endpoints
Amazon SageMaker multi-model endpoints (MMEs) are a fully managed capability of SageMaker inference that allows you to deploy thousands of models on a single endpoint. Previously, MMEs pre-determinedly allocated CPU…
Code Llama 70B is now available in Amazon SageMaker JumpStart
Today, we are excited to announce that Code Llama foundation models, developed by Meta, are available for customers through Amazon SageMaker JumpStart to deploy with one click for running inference.…
Detect anomalies in manufacturing data using Amazon SageMaker Canvas
With the use of cloud computing, big data and machine learning (ML) tools like Amazon Athena or Amazon SageMaker have become available and useable by anyone without much effort in…