Your guide to generative AI and ML at AWS re:Invent 2023 | Amazon Web Services
Yes, the AWS re:Invent season is upon us and as always, the place to be is Las Vegas! You marked your calendars, you booked your hotel, and you even purchased…
Generative AI
Build a contextual chatbot for financial services using Amazon SageMaker JumpStart, Llama 2 and Amazon OpenSearch Serverless with Vector Engine | Amazon Web Services
The financial service (FinServ) industry has unique generative AI requirements related to domain-specific data, data security, regulatory controls, and industry compliance standards. In addition, customers are looking for choices to…
Amazon Textract’s new Layout feature introduces efficiencies in general purpose and generative AI document processing tasks | Amazon Web Services
Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. AnalyzeDocument Layout is a new feature that allows customers to…
Use Amazon SageMaker Studio to build a RAG question answering solution with Llama 2, LangChain, and Pinecone for fast experimentation | Amazon Web Services
Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories, databases, and APIs without the need…
Build a foundation model (FM) powered customer service bot with agents for Amazon Bedrock | Amazon Web Services
From enhancing the conversational experience to agent assistance, there are plenty of ways that generative artificial intelligence (AI) and foundation models (FMs) can help deliver faster, better support. With the…
Fine-tune Whisper models on Amazon SageMaker with LoRA | Amazon Web Services
Whisper is an Automatic Speech Recognition (ASR) model that has been trained using 680,000 hours of supervised data from the web, encompassing a range of languages and tasks. One of…
Best prompting practices for using the Llama 2 Chat LLM through Amazon SageMaker JumpStart | Amazon Web Services
Llama 2 stands at the forefront of AI innovation, embodying an advanced auto-regressive language model developed on a sophisticated transformer foundation. It’s tailored to address a multitude of applications in…
Improve LLM responses in RAG use cases by interacting with the user | Amazon Web Services
One of the most common applications of generative AI and large language models (LLMs) is answering questions based on a specific external knowledge corpus. Retrieval-Augmented Generation (RAG) is a popular…
Build trust and safety for generative AI applications with Amazon Comprehend and LangChain | Amazon Web Services
We are witnessing a rapid increase in the adoption of large language models (LLM) that power generative AI applications across industries. LLMs are capable of a variety of tasks, such…
Harnessing the power of enterprise data with generative AI: Insights from Amazon Kendra, LangChain, and large language models | Amazon Web Services
Large language models (LLMs) with their broad knowledge, can generate human-like text on almost any topic. However, their training on massive datasets also limits their usefulness for specialized tasks. Without…