Category: Technical How-to

In this post, the AWS and Cisco teams unveil a new methodical approach that addresses the challenges of enterprise-grade SQL generation. The teams were able to reduce the complexity of the NL2SQL process while delivering higher accuracy and better overall performance.

In this post, we discuss how you can build an AI-powered document processing platform with open source NER and LLMs on SageMaker.

In this post, we explore how Low-Rank Adaptation (LoRA) can be used to address these challenges effectively. Specifically, we discuss using LoRA serving with LoRA eXchange (LoRAX) and HAQM Elastic Compute Cloud (HAQM EC2) GPU instances, allowing organizations to efficiently manage and serve their growing portfolio of fine-tuned models, optimize costs, and provide seamless performance for their customers.

This post demonstrates how to deploy and serve the Mixtral 8x7B language model on AWS Inferentia2 instances for cost-effective, high-performance inference. We’ll walk through model compilation using Hugging Face Optimum Neuron, which provides a set of tools enabling straightforward model loading, training, and inference, and the Text Generation Inference (TGI) Container, which has the toolkit for deploying and serving LLMs with Hugging Face.

In this post, we demonstrate how to elevate business productivity by leveraging HAQM Q to provide insights that enable research, data analysis, and report potential fraud cases within HAQM Connect.

This post demonstrates how to integrate open-source multi-agent framework, LangGraph, with HAQM Bedrock. It explains how to use LangGraph and HAQM Bedrock to build powerful, interactive multi-agent applications that use graph-based orchestration.

This post demonstrates how enterprises can implement a scalable agentic text-to-SQL solution using HAQM Bedrock Agents, with advanced error-handling tools and automated schema discovery to enhance database query efficiency.

In this post, we demonstrate how you can use custom plugins for HAQM Q Business to build a chatbot that can interact with multiple APIs using natural language prompts. We showcase how to build an AIOps chatbot that enables users to interact with their AWS infrastructure through natural language queries and commands. The chatbot is capable of handling tasks such as querying the data about HAQM Elastic Compute Cloud (HAQM EC2) ports and HAQM Simple Storage Service (HAQM S3) buckets access settings.

The introduction of HAQM Nova models represent a significant advancement in the field of AI, offering new opportunities for large language model (LLM) optimization. In this post, we demonstrate how to effectively perform model customization and RAG with HAQM Nova models as a baseline. We conducted a comprehensive comparison study between model customization and RAG using the latest HAQM Nova models, and share these valuable insights.

In this post, we demonstrate how to use HAQM Personalize and HAQM Bedrock to generate personalized outreach emails for individual users using a video-on-demand use case. This concept can be applied to other domains, such as compelling customer experiences for ecommerce and digital marketing use cases.