Amazon Web Services

Since 2008, AWS and SAP have been partnering to help customers migrate to Cloud ERP, innovate faster, and transform their businesses.

This video will comprise a presentation for the first ~7 minutes, then 3 - 4 minutes of demo in VS Code and Visual Studio.

As your AWS cloud footprint expands, implementing a secure and scalable multi-account structure becomes crucial.

AWS Innovation & Transformation Programs, EPIC team sits down with CTO of Equals Group to discuss how emotional inteligence and empathetic leadership were significant drivers of innovation at Equals

Amazon Security Lake is a fully managed security data lake, built on S3, in the customers account.

Amazon Elastic Container Service(ECS) is a fully managed container orchestration service that simplifies your deployment, management, and scaling of containerized applications.

For highly regulated environments, preventing mistakes or malicious behavior within your code reaching production is not negotiable.

AWS WAF is a web application firewall that helps protect your applications or APIs against common web exploits and bots that may affect availability, compromise security, or consume excessive

Welcome to another episode of the AWS for Data Podcast.

This video showcases how manufacturers leverage AWS services and partner solutions to drive digital transformation, improve product quality, and achieve operational excellence across their factories

Explore how AWS and DoiT are pushing the boundaries of human creativity with advanced AI models.

Explore how Mission Cloud pioneers in the realm of AI with Amazon Bedrock, boasting over 50 projects and 15 use cases.

Discover how Slalom, a global consulting company founded in 2001, is helping customers win with cutting-edge Gen AI solutions.

Get a behind-the-scenes look at MAG's journey delivering innovative, human-centered AI solutions for smarter travel in collaboration with the AWS prototyping team.

Learn a well-architected disaster recovery pattern for your Amazon Aurora databases across multiple AWS regions.

While preparing its visual effects assets for Avatar 2: The Way of Water, Wētā FX maxed out its on-premises render capabilities, putting its delivery deadlines in jeopardy.

The Fastest and Easiest Way to Build Applications.

In this video, you will learn how to implement a scalable and reusable framework for RAG-based workflows.

In this video, you will learn how to monitor LLMs, including prompt injections, toxicity, sentiment, and more, to ensure your model is secure, so you can build your generative AI applications

In this video, you will learn how to use Amazon SageMaker to safeguard and run governance controls for your end-to-end generative AI project.

You need scalable and cost-effective ways to serve hundreds of foundation models. In this video, you will learn how to use SageMaker inference components to deploy multiple models at scale.

As the demands for personalized and specialized AI solutions grow, organizations are managing hundreds of fine-tuned models tailored to specific customer needs or use cases.

In this video, you will learn how to enforce responsible AI with a safety guard model LlamaGuard and Llama2-7b on Amazon SageMaker using inference components for cost effective and safe deployment.

Amazon SageMaker makes it easier to deploy FMs to make inference requests at the best price performance for any use case.

Amazon SageMaker makes it easier to deploy FMs to make inference requests at the best price performance for any use case.

Amazon SageMaker makes it easier to deploy FMs to make inference requests at the best price performance for any use case.

To equip the FM with new knowledge not included in the pre-training dataset, you can use RAG, a technique that involves fetching data from company data sources and enriching the prompt with that

In this video, you will learn how to fine-tune foundation models using Amazon SageMaker JumpStart.

In this video, you will learn how to label the data using Amazon SageMaker Ground Truth. You can collect human labeled data through automated workflow or an AWS managed workforce.

Effective prompt engineering is crucial for directing model behavior and achieving desired responses. It helps you to modify the performance of FMs.