en English
ar العربيةzh-CN 简体中文en Englishfr Françaisde Deutschko 한국어es Españolvi Tiếng Việt

Build a contextual chatbot for financial services using Amazon SageMaker JumpStart, Llama 2 and Amazon OpenSearch Serverless with Vector Engine

Favorite 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 select the most performant and cost-effective machine learning (ML) model and the ability to perform necessary customization (fine-tuning) to

Read More
Shared by AWS Machine Learning November 23, 2023

Amazon Textract’s new Layout feature introduces efficiencies in general purpose and generative AI document processing tasks

Favorite 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 automatically extract layout elements such as paragraphs, titles, subtitles, headers, footers, and more from documents. Layout extends Amazon Textract’s

Read More
Shared by AWS Machine Learning November 22, 2023

Text embedding and sentence similarity retrieval at scale with Amazon SageMaker JumpStart

Favorite Text vectors or embeddings are numerical vector representations of text that are generated by large language models (LLMs). After LLMs are fully pre-trained on a large dataset or fine-tuned from different tasks, including text completion, question answering, and translations, text embeddings capture semantic information of the input text. Different

Read More
Shared by AWS Machine Learning November 22, 2023

Machine Learning with MATLAB and Amazon SageMaker

Favorite This post is written in collaboration with Brad Duncan, Rachel Johnson and Richard Alcock from MathWorks. MATLAB  is a popular programming tool for a wide range of applications, such as data processing, parallel computing, automation, simulation, machine learning, and artificial intelligence. It’s heavily used in many industries such as

Read More
Shared by AWS Machine Learning November 22, 2023

Use Amazon SageMaker Studio to build a RAG question answering solution with Llama 2, LangChain, and Pinecone for fast experimentation

Favorite 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 to fine-tune it. When using generative AI for question answering, RAG enables LLMs to answer questions with the most

Read More
Shared by AWS Machine Learning November 21, 2023