Artificial Intelligence
Category: Amazon Machine Learning
Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio
This post is co-written with Marc Neumann, Amor Steinberg and Marinus Krommenhoek from BMW Group. The BMW Group – headquartered in Munich, Germany – is driven by 149,000 employees worldwide and manufactures in over 30 production and assembly facilities across 15 countries. Today, the BMW Group is the world’s leading manufacturer of premium automobiles and […]
Automating product description generation with Amazon Bedrock
In today’s ever-evolving world of ecommerce, the influence of a compelling product description cannot be overstated. It can be the decisive factor that turns a potential visitor into a paying customer or sends them clicking off to a competitor’s site. The manual creation of these descriptions across a vast array of products is a labor-intensive […]
How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action
This post was co-written with Greg Benson, Chief Scientist; Aaron Kesler, Sr. Product Manager; and Rich Dill, Enterprise Solutions Architect from SnapLogic. Many customers are building generative AI apps on Amazon Bedrock and Amazon CodeWhisperer to create code artifacts based on natural language. This use case highlights how large language models (LLMs) are able to […]
Your guide to generative AI and ML at AWS re:Invent 2023
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 the airfare. Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. And although generative AI has appeared in previous events, this year we’re taking it to the next level. In addition to several exciting announcements during keynotes, most of the sessions in our track will feature generative AI in one form or another, so we can truly call our track “Generative AI and ML.” In this post, we give you a sense of how the track is organized and highlight a few sessions we think you’ll like. And although our track focuses on generative AI, many other tracks have related sessions. Use the “Generative AI” tag as you are browsing the session catalog to find them.
Build a contextual chatbot for financial services using Amazon SageMaker JumpStart, Llama 2 and Amazon OpenSearch Serverless with Vector Engine
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 fit their business use cases. Amazon […]
Geospatial generative AI with Amazon Bedrock and Amazon Location Service
Today, geospatial workflows typically consist of loading data, transforming it, and then producing visual insights like maps, text, or charts. Generative AI can automate these tasks through autonomous agents. In this post, we discuss how to use foundation models from Amazon Bedrock to power agents to complete geospatial tasks. These agents can perform various tasks […]
Use Amazon SageMaker Studio to build a RAG question answering solution with Llama 2, LangChain, and Pinecone for fast experimentation
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 relevant, up-to-date information and optionally cite […]
Moderate your Amazon IVS live stream using Amazon Rekognition
Amazon Interactive Video Service (Amazon IVS) is a managed live streaming solution that is designed to provide a quick and straightforward setup to let you build interactive video experiences and handles interactive video content from ingestion to delivery. With the increased usage of live streaming, the need for effective content moderation becomes even more crucial. […]
Build a foundation model (FM) powered customer service bot with Amazon Bedrock agents
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 increasing availability and diversity of FMs, it’s difficult to experiment and keep up-to-date with the latest model versions. Amazon Bedrock is a fully managed service […]
Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights
An established financial services firm with over 140 years in business, Principal is a global investment management leader and serves more than 62 million customers around the world. Principal is conducting enterprise-scale near-real-time analytics to deliver a seamless and hyper-personalized omnichannel customer experience on their mission to make financial security accessible for all. They are […]









