AWS Machine Learning Blog

Tag: Generative AI

Customize small language models on AWS with automotive terminology

In this post, we guide you through the phases of customizing SLMs on AWS, with a specific focus on automotive terminology for diagnostics as a Q&A task. We begin with the data analysis phase and progress through the end-to-end process, covering fine-tuning, deployment, and evaluation. We compare a customized SLM with a general purpose LLM, using various metrics to assess vocabulary richness and overall accuracy.

Automate cloud security vulnerability assessment and alerting using HAQM Bedrock

This post demonstrates a proactive approach for security vulnerability assessment of your accounts and workloads, using HAQM GuardDuty, HAQM Bedrock, and other AWS serverless technologies. This approach aims to identify potential vulnerabilities proactively and provide your users with timely alerts and recommendations, avoiding reactive escalations and other damages.

Text-to-SQL Solution Pipeline

How MSD uses HAQM Bedrock to translate natural language into SQL for complex healthcare databases

MSD, a leading pharmaceutical company, collaborates with AWS to implement a powerful text-to-SQL generative AI solution using HAQM Bedrock and Anthropic’s Claude 3.5 Sonnet model. This approach streamlines data extraction from complex healthcare databases like DE-SynPUF, enabling analysts to generate SQL queries from natural language questions. The solution addresses challenges such as coded columns, non-intuitive names, and ambiguous queries, significantly reducing query time and democratizing data access.

Principal Financial Group uses QnABot on AWS and HAQM Q Business to enhance workforce productivity with generative AI

In this post, we explore how Principal used QnABot paired with HAQM Q Business and HAQM Bedrock to create Principal AI Generative Experience: a user-friendly, secure internal chatbot for faster access to information. Using generative AI, Principal’s employees can now focus on deeper human judgment based decisioning, instead of spending time scouring for answers from data sources manually.

Revolutionize trip planning with HAQM Bedrock and HAQM Location Service

In this post, we show you how to build a generative AI-powered trip-planning service that revolutionizes the way travelers discover and explore destinations. By using advanced AI technology and HAQM Location Service, the trip planner lets users translate inspiration into personalized travel itineraries. This innovative service goes beyond traditional trip planning methods, offering real-time interaction through a chat-based interface and maintaining scalability, reliability, and data security through AWS native services.

Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

In this post, we explore the approach behind building an AWS AI-powered Chrome extension that aims to revolutionize the live streaming experience by providing real-time transcription, translation, and summarization capabilities directly within your browser.

Build a reverse image search engine with HAQM Titan Multimodal Embeddings in HAQM Bedrock and AWS managed services

In this post, you will learn how to extract key objects from image queries using HAQM Rekognition and build a reverse image search engine using HAQM Titan Multimodal Embeddings from HAQM Bedrock in combination with HAQM OpenSearch Serverless Service.

Fine-tune Meta Llama 3.2 text generation models for generative AI inference using HAQM SageMaker JumpStart

In this post, we demonstrate how to fine-tune Meta’s latest Llama 3.2 text generation models, Llama 3.2 1B and 3B, using HAQM SageMaker JumpStart for domain-specific applications. By using the pre-built solutions available in SageMaker JumpStart and the customizable Meta Llama 3.2 models, you can unlock the models’ enhanced reasoning, code generation, and instruction-following capabilities to tailor them for your unique use cases.

Integrate foundation models into your code with HAQM Bedrock

The rise of large language models (LLMs) and foundation models (FMs) has revolutionized the field of natural language processing (NLP) and artificial intelligence (AI). These powerful models, trained on vast amounts of data, can generate human-like text, answer questions, and even engage in creative writing tasks. However, training and deploying such models from scratch is […]

Unlock organizational wisdom using voice-driven knowledge capture with HAQM Transcribe and HAQM Bedrock

This post introduces an innovative voice-based application workflow that harnesses the power of HAQM Bedrock, HAQM Transcribe, and React to systematically capture and document institutional knowledge through voice recordings from experienced staff members. Our solution uses HAQM Transcribe for real-time speech-to-text conversion, enabling accurate and immediate documentation of spoken knowledge. We then use generative AI, powered by HAQM Bedrock, to analyze and summarize the transcribed content, extracting key insights and generating comprehensive documentation.