Remove 2013 Remove Artificial Intelligence Remove AWS
article thumbnail

Your guide to generative AI and ML at AWS re:Invent 2023

AWS Machine Learning Blog

Yes, the AWS re:Invent season is upon us and as always, the place to be is Las Vegas! are the sessions dedicated to AWS DeepRacer ! Generative AI is at the heart of the AWS Village this year. You marked your calendars, you booked your hotel, and you even purchased the airfare. And last but not least (and always fun!)

AWS 139
article thumbnail

Learn how to assess the risk of AI systems

Flipboard

Artificial intelligence (AI) is a rapidly evolving field with the potential to improve and transform many aspects of society. Source: “Information technology – Artificial intelligenceArtificial intelligence concepts and terminology”. When it comes to stakeholders, it’s easy to overlook some.

AWS 173
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Build a multi-interface AI assistant using Amazon Q and Slack with Amazon CloudFront clickable references from an Amazon S3 bucket

AWS Machine Learning Blog

Click here to open the AWS console and follow along. Developed by Todd Gamblin at the Lawrence Livermore National Laboratory in 2013, Spack addresses the limitations of traditional package managers in high-performance computing (HPC) environments. About the Authors Nick Biso is a Machine Learning Engineer at AWS Professional Services.

AWS 75
article thumbnail

Reinventing the data experience: Use generative AI and modern data architecture to unlock insights

AWS Machine Learning Blog

Overall, implementing a modern data architecture and generative AI techniques with AWS is a promising approach for gleaning and disseminating key insights from diverse, expansive data at an enterprise scale. AWS also offers foundation models through Amazon SageMaker JumpStart as Amazon SageMaker endpoints.

Database 101
article thumbnail

Designing generative AI workloads for resilience

AWS Machine Learning Blog

Consider the following picture, which is an AWS view of the a16z emerging application stack for large language models (LLMs). This includes native AWS services like Amazon OpenSearch Service and Amazon Aurora. Is your vector database highly available in a single AWS Region? Vector database features built into other services.

AWS 138
article thumbnail

How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

Database 158
article thumbnail

Navigating tomorrow: Role of AI and ML in information technology

Dataconomy

Artificial intelligence and machine learning are no longer the elements of science fiction; they’re the realities of today. Microsoft has reported a 27 percent increase in profit due to its focus on cloud computing and investments in artificial intelligence.

ML 121