Category: Amazon Machine Learning

Foundational models (FMs) are trained on large volumes of data and use billions of parameters. However, in order to answer customers’ questions related to domain-specific private data, they need to reference an authoritative knowledge base outside of the model’s training data sources. This is commonly achieved using a technique known as Retrieval Augmented Generation (RAG). […]

Amazon Titan foundation models (FMs) offer a comprehensive suite of pre-trained image, multimodal, and text models accessible through a fully managed API. They’re designed for a range of applications while adhering to responsible AI practices.

* 20 August: Code snippet in the post has been updated * In November 2023, we made two new Cohere models available in Amazon Bedrock (Cohere Command Light and Cohere Embed English). Today, we’re announcing the addition of two more Cohere models in Amazon Bedrock; Cohere Command R and Command R+. Organizations need generative artificial […]

This was a busy week for Amazon Bedrock with many new features! Using GitHub Actions with AWS CodeBuild is much easier. Also, Amazon Q in Amazon CodeCatalyst can now manage more complex issues. I was amazed to meet so many new and old friends at the AWS Summit London. To give you a quick glimpse, […]

The instruction-tuned large language models have been pre-trained on over 15 trillion tokens of data—a training dataset seven times larger than that used for Llama 2 models.

With Guardrails for Amazon Bedrock, you can implement safeguards in your generative artificial intelligence applications that are customized to your use cases and responsible AI policies.

May 8, 2024: Post updated with a link showing how to handle return of control in code. With Agents for Amazon Bedrock, applications can use generative artificial intelligence (generative AI) to run tasks across multiple systems and data sources. Starting today, these new capabilities streamline the creation and management of agents: Quick agent creation – […]

This new capability helps you to incorporate generative AI into your application by letting you select the foundation model that gives you the best results for your particular use case.