AWS Machine Learning Blog
Category: Learning Levels
Govern generative AI in the enterprise with Amazon SageMaker Canvas
In this post, we analyze strategies for governing access to Amazon Bedrock and SageMaker JumpStart models from within SageMaker Canvas using AWS Identity and Access Management (IAM) policies. You’ll learn how to create granular permissions to control the invocation of ready-to-use Amazon Bedrock models and prevent the provisioning of SageMaker endpoints with specified SageMaker JumpStart models.
Integrate dynamic web content in your generative AI application using a web search API and Amazon Bedrock Agents
In this post, we demonstrate how to use Amazon Bedrock Agents with a web search API to integrate dynamic web content in your generative AI application.
Build a generative AI assistant to enhance employee experience using Amazon Q Business
In this blog post, we explore how you can use Amazon Q Business to build generative AI assistants that enhance employee experience and boost productivity. Amazon Q Business seamlessly integrates with internal data sources, knowledge bases, and productivity tools to equip your workforce with instant access to information, automated tasks, and personalized support.
Fine-tune Meta Llama 3.1 models using torchtune on Amazon SageMaker
In this post, AWS collaborates with Meta’s PyTorch team to showcase how you can use PyTorch’s torchtune library to fine-tune Meta Llama-like architectures while using a fully-managed environment provided by Amazon SageMaker Training.
Integrate Amazon Bedrock Knowledge Bases with Microsoft SharePoint as a data source
In this post, we show you how to configure Amazon Bedrock Knowledge Bases with SharePoint Online as a data source. By connecting SharePoint Online as a data source, employees can interact with the organization’s knowledge and data stored in SharePoint using natural language, making it straightforward to find relevant information, extract key points, and derive valuable insights.
Revolutionize logo design creation with Amazon Bedrock: Embracing generative art, dynamic logos, and AI collaboration
In this post, we walk through how AWS can help accelerate a brand’s creative efforts with access to a powerful image-to-image model from Stable Diffusion available on Amazon Bedrock to interactively create and edit art and logo images.
Build RAG-based generative AI applications in AWS using Amazon FSx for NetApp ONTAP with Amazon Bedrock
In this post, we demonstrate a solution using Amazon FSx for NetApp ONTAP with Amazon Bedrock to provide a RAG experience for your generative AI applications on AWS by bringing company-specific, unstructured user file data to Amazon Bedrock in a straightforward, fast, and secure way.
Preserve access and explore alternatives for Amazon Lookout for Equipment
In this post we discuss how you can maintain access to Lookout for Equipment after it is closed to new customers and some alternatives to Lookout for Equipment.
CRISPR-Cas9 guide RNA efficiency prediction with efficiently tuned models in Amazon SageMaker
The clustered regularly interspaced short palindromic repeat (CRISPR) technology holds the promise to revolutionize gene editing technologies, which is transformative to the way we understand and treat diseases. This technique is based in a natural mechanism found in bacteria that allows a protein coupled to a single guide RNA (gRNA) strand to locate and make […]
Unlock AWS Cost and Usage insights with generative AI powered by Amazon Bedrock
In this post, we explore a solution that uses generative artificial intelligence (AI) to generate a SQL query from a user’s question in natural language. This solution can simplify the process of querying CUR data stored in an Amazon Athena database using SQL query generation, running the query on Athena, and representing it on a web portal for ease of understanding.