Remove APIs Remove Conference Remove industry standards Remove Personalization
article thumbnail

Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

With Knowledge Bases for Amazon Bedrock, you can quickly build applications using Retrieval Augmented Generation (RAG) for use cases like question answering, contextual chatbots, and personalized search. It calls the CreateDataSource and DeleteDataSource APIs.

APIs 103
article thumbnail

Gemma is now available in Amazon SageMaker JumpStartĀ 

AWS Machine Learning

fine_tuned_predictor= estimator.deploy() You can choose to deploy the model fine-tuned on conversation data in SageMaker endpoint with HuggingFace messages API feature as an alternative approach. Set personal goals: Set achievable targets, such as learning five new words per week. user Thank you for recommending these books to me!

Benchmark 106
article thumbnail

Best practices to build generative AI applications on AWS

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon via a single API. This can enable more personalized applications. This specializes the model for that particular task.