Today, I am happy to announce the general availability of Guardrails for Amazon Bedrock, first released in preview at re:Invent 2023. With Guardrails for Amazon Bedrock, you can implement safeguards in your generative artificial intelligence (generative AI) applications that are customized to your use cases and responsible AI policies. You can create multiple guardrails tailored to different use cases and apply them across multiple foundation models (FMs), improving end-user experiences and standardizing safety controls across generative AI applications. You can use Guardrails for Amazon Bedrock with all large language models (LLMs) in Amazon Bedrock, including fine-tuned models. Guardrails for Bedrock offers industry-leading safety protection on top of the native capabilities of FMs, helping customers block as much as 85% more harmful…
Category: AWS
Reposts from Amazon Web Services (AWS).
Agents for Amazon Bedrock: Introducing a simplified creation and configuration experience
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 – You can now quickly create an agent and optionally add instructions and action groups later, providing flexibility and agility for your development process. Agent builder – All agent configurations can be operated in the new agent builder section of the console. Simplified configuration – Action groups can use a simplified schema that just lists functions and parameters without having to provide an API schema. Return of control –You can skip using an AWS Lambda function and return control to the application invoking…
Amazon Bedrock model evaluation is now generally available
The Amazon Bedrock model evaluation capability that we previewed at AWS re:Invent 2023 is now generally available. This new capability helps you to incorporate Generative AI into your application by giving you the power to select the foundation model that gives you the best results for your particular use case. As my colleague Antje explained in her post (Evaluate, compare, and select the best foundation models for your use case in Amazon Bedrock): Model evaluations are critical at all stages of development. As a developer, you now have evaluation tools available for building generative artificial intelligence (AI) applications. You can start by experimenting with different models in the playground environment. To iterate faster, add automatic evaluations of the models. Then,…
Import custom models in Amazon Bedrock (preview)
With Amazon Bedrock, you have access to a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies that make it easier to build and scale generative AI applications. Some of these models provide publicly available weights that can be fine-tuned and customized for specific use cases. However, deploying customized FMs in a secure and scalable way is not an easy task. Starting today, Amazon Bedrock adds in preview the capability to import custom weights for supported model architectures (such as Meta Llama 2, Llama 3, and Mistral) and serve the custom model using On-Demand mode. You can import models with weights in Hugging Face safetensors format from Amazon SageMaker and Amazon Simple Storage Service (Amazon S3). In…