AWS Machine Learning Blog

Category: Artificial Intelligence

Amazon Personalize launches new recipes supporting larger item catalogs with lower latency

We are excited to announce the general availability of two advanced recipes in Amazon Personalize, User-Personalization-v2 and Personalized-Ranking-v2 (v2 recipes), which are built on the cutting-edge Transformers architecture to support larger item catalogs with lower latency. In this post, we summarize the new enhancements, and guide you through the process of training a model and providing recommendations for your users.

Get started with Amazon Titan Text Embeddings V2: A new state-of-the-art embeddings model on Amazon Bedrock

Embeddings are integral to various natural language processing (NLP) applications, and their quality is crucial for optimal performance. They are commonly used in knowledge bases to represent textual data as dense vectors, enabling efficient similarity search and retrieval. In Retrieval Augmented Generation (RAG), embeddings are used to retrieve relevant passages from a corpus to provide […]

Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker

Large language models (LLMs) are making a significant impact in the realm of artificial intelligence (AI). Their impressive generative abilities have led to widespread adoption across various sectors and use cases, including content generation, sentiment analysis, chatbot development, and virtual assistant technology. Llama2 by Meta is an example of an LLM offered by AWS. Llama […]

Fine-tune and deploy language models with Amazon SageMaker Canvas and Amazon Bedrock

Imagine harnessing the power of advanced language models to understand and respond to your customers’ inquiries. Amazon Bedrock, a fully managed service providing access to such models, makes this possible. Fine-tuning large language models (LLMs) on domain-specific data supercharges tasks like answering product questions or generating relevant content. In this post, we show how Amazon […]

Improving inclusion and accessibility through automated document translation with an open source app using Amazon Translate

Organizations often offer support in multiple languages, saying “contact us for translations.” However, customers who don’t speak the predominant language often don’t know that translations are available or how to request them. This can lead to poor customer experience and lost business. A better approach is proactively providing information in multiple languages so customers can […]

Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

Numerous customers face challenges in managing diverse data sources and seek a chatbot solution capable of orchestrating these sources to offer comprehensive answers. This post presents a solution for developing a chatbot capable of answering queries from both documentation and databases, with straightforward deployment. Amazon Bedrock is a fully managed service that offers a choice […]

Build private and secure enterprise generative AI apps with Amazon Q Business and AWS IAM Identity Center

As of April 30, 2024 Amazon Q Business is generally available. Amazon Q Business is a conversational assistant powered by generative artificial intelligence (AI) that enhances workforce productivity by answering questions and completing tasks based on information in your enterprise systems. Your employees can access enterprise content securely and privately using web applications built with […]

Enhance customer service efficiency with AI-powered summarization using Amazon Transcribe Call Analytics

In the fast-paced world of customer service, efficiency and accuracy are paramount. After each call, contact center agents often spend up to a third of the total call time summarizing the customer conversation. Additionally, manual summarization can lead to inconsistencies in the style and level of detail due to varying interpretations of note-taking guidelines. This […]

Develop and train large models cost-efficiently with Metaflow and AWS Trainium

This is a guest post co-authored with Ville Tuulos (Co-founder and CEO) and Eddie Mattia (Data Scientist) of Outerbounds. To build a production-grade AI system today (for example, to do multilingual sentiment analysis of customer support conversations), what are the primary technical challenges? Historically, natural language processing (NLP) would be a primary research and development […]