Generative Artificial Intelligence (AI) on AWS
Learn, Build, and Explore with Amazon CodeWhisperer, Amazon Bedrock, and more...
Generative AI - A Primer
Generative AI is everywhere now-a-days. But what is it? Well, think of it as a type of AI that can create new content an ideas, including conversations, stories, images, videos, and music. For your gen AI journey with AWS, this video gives a foundational overview of where it came from, where it’s going, how it works, and how to get started.
Build your Generative AI Applications on AWS
To build generative AI applications on AWS, you can start with Amazon Bedrock to choose the right Foundation Model (FM) for your use-case. If you prefer, you can also use Amazon SageMaker JumpStart’s ML Hub to accelerate your model development. The selected model can then be customized with additional training in AWS to suit the application’s needs. And as you program and code, the Amazon CodeWhisperer service can help as your developer coding tool.
Code with Amazon CodeWhisperer
Being trained on AWS data and APIs, Amazon CodeWhisperer analyzes existing code in the IDE (whether generated by CodeWhisperer or written by you), identifies problematic code with high accuracy, and provides intelligent suggestions on how to remediate it. With the customization capability more precise suggestions are generated, by including your organization’s internal APIs, libraries, classes, methods, and best practices. Explore with Amazon CodeWhisperer and get a productivity boost.
Build on Amazon Bedrock
With Amazon Bedrock’s comprehensive capabilities, you can experiment with a variety of Foundation Models (FMs), customize them using your data with techniques such as Fine-Tuning and Retrieval-Augmented Generation (RAG), and create managed agents. Explore now with Amazon Bedrock to execute your complex business tasks—from booking travel and processing insurance claims to creating ad campaigns and managing inventory—all without writing any code.
Train generative AI Models on Purpose-built Accelerators
Whatever customers are trying to do with FMs—running them, building them, customizing them—they need the most performant, cost-effective, purpose-built ML infrastructure. Over the past decade, AWS has been investing with our partners and silicon to offer a broad choice of high-performance, low-cost ML infrastructure chip options. The AWS Trainium and AWS Inferentia chips offer the lowest cost for generative AI training models and running inference in the cloud
Try Some Sample Apps
To build generative AI applications on AWS, you start with Amazon CodeWhisperer as your developer coding tool, and then use Amazon Bedrock to choose the right Foundation Model (FM) for your user-case. If you prefer, you can also use Amazon SageMaker JumpStart’s ML Hub to accelerate your model development. The selected model can then be customized with additional training in AWS to suit the application’s needs.
Build Responsibly with AI
Responsible use of AI and ML is key to tackling some of humanity’s most challenging problems, augmenting human performance, and maximizing productivity. AWS is committed to developing fair and accurate AI and ML services and providing you with the tools and guidance needed to build AI and ML applications responsibly.
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