Amazon Bedrock, a fully managed service from Amazon Web Services, is designed for building, deploying, and scaling generative AI applications. It offers a catalog of foundation models, implements retrieval-augmented generation (RAG) and vector embeddings, hosts knowledge bases, allows fine-tuning of models, and enables continued pre-training of selected models. With almost 30 other machine learning services available on AWS, Amazon Bedrock stands out with its unique features.
The service offers six major features, including the ability to experiment with different models, integrate external data sources, develop customer support applications, customize models for specific tasks or domains, boost application efficiency, and choose the most suitable model for a particular application. Amazon Bedrock competes with other services like Azure AI Studio and Google Vertex AI’s Generative AI Studio, offering similar capabilities for generative AI application building.
Setting up a model in Amazon Bedrock involves requesting access to models and configuring the API. The service uses parameters like temperature, top K, top P, response length, penalties, and stop sequences to control model responses. Users can explore different models and configurations using examples and playgrounds within the service, experimenting with tasks like summarization, question answering, code generation, text generation, and image generation.
Examples in Amazon Bedrock showcase various tasks and supported models, allowing users to see prompts and responses for different scenarios. One example demonstrates arithmetic word problem-solving using the Llama 2 Chat 70B v1 model, while another shows contract entity extraction using Cohere’s Command text generation model. The service also supports image inpainting, allowing users to generate new images based on reference images and prompts.
Overall, Amazon Bedrock offers a comprehensive platform for building and deploying generative AI applications, with a range of features and capabilities to support various tasks and domains.
Source link
