AWS News Blog
Category: Amazon SageMaker
Package and deploy models faster with new tools and guided workflows in Amazon SageMaker
I’m happy to share that Amazon SageMaker now comes with an improved model deployment experience to help you deploy traditional machine learning (ML) models and foundation models (FMs) faster. As a data scientist or ML practitioner, you can now use the new ModelBuilder class in the SageMaker Python SDK to package models, perform local inference […]
Use natural language to explore and prepare data with a new capability of Amazon SageMaker Canvas
Today, I’m happy to introduce the ability to use natural language instructions in Amazon SageMaker Canvas to explore, visualize, and transform data for machine learning (ML). SageMaker Canvas now supports using foundation model-(FM) powered natural language instructions to complement its comprehensive data preparation capabilities for data exploration, analysis, visualization, and transformation. Using natural language instructions, […]
Amazon SageMaker adds new inference capabilities to help reduce foundation model deployment costs and latency
Today, we are announcing new Amazon SageMaker inference capabilities that can help you optimize deployment costs and reduce latency. With the new inference capabilities, you can deploy one or more foundation models (FMs) on the same SageMaker endpoint and control how many accelerators and how much memory is reserved for each FM. This helps to […]
Leverage foundation models for business analysis at scale with Amazon SageMaker Canvas
Today, I’m excited to introduce a new capability in Amazon SageMaker Canvas to use foundation models (FMs) from Amazon Bedrock and Amazon SageMaker Jumpstart through a no-code experience. This new capability makes it easier for you to evaluate and generate responses from FMs for your specific use case with high accuracy. Every business has its […]
Amazon SageMaker Clarify makes it easier to evaluate and select foundation models (preview)
I’m happy to share that Amazon SageMaker Clarify now supports foundation model (FM) evaluation (preview). As a data scientist or machine learning (ML) engineer, you can now use SageMaker Clarify to evaluate, compare, and select FMs in minutes based on metrics such as accuracy, robustness, creativity, factual knowledge, bias, and toxicity. This new capability adds […]
Introducing Amazon SageMaker HyperPod, a purpose-built infrastructure for distributed training at scale
Today, we are introducing Amazon SageMaker HyperPod, which helps reducing time to train foundation models (FMs) by providing a purpose-built infrastructure for distributed training at scale. You can now use SageMaker HyperPod to train FMs for weeks or even months while SageMaker actively monitors the cluster health and provides automated node and job resiliency by […]
AWS Weekly Roundup: AWS Control Tower, Amazon Bedrock, Amazon OpenSearch Service, and More (October 9, 2023)
As the Northern Hemisphere enjoys early fall and pumpkins take over the local farmers markets and coffee flavors here in the United States, we’re also just 50 days away from re:Invent 2023! But before we officially enter pre:Invent season, let’s have a look at some of last week’s exciting news and announcements. Last Week’s Launches […]
AWS Weekly Roundup: R7iz Instances, Amazon Connect, CloudWatch Logs, and Lots More (Sept. 11, 2023)
Looks like it is my turn once again to write the AWS Weekly Roundup. I wrote and published the first one on April 16, 2012 — just 4,165 short day ago! Last Week’s Launches Here are some of the launches that caught my eye last week: R7iz Instances – Optimized for high CPU performance and […]