Build a foundation model (FM) powered customer service bot with agents for Amazon Bedrock

Favorite 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

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Shared by AWS Machine Learning November 18, 2023

Retrieval-Augmented Generation with LangChain, Amazon SageMaker JumpStart, and MongoDB Atlas semantic search

Favorite Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. The Retrieval-Augmented Generation (RAG) framework augments prompts with external data from multiple sources, such as

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Shared by AWS Machine Learning November 18, 2023

Moderate your Amazon IVS live stream using Amazon Rekognition

Favorite 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

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Shared by AWS Machine Learning November 18, 2023

Fine-tune Whisper models on Amazon SageMaker with LoRA

Favorite 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 its limitations is the low-performance on low-resource languages such as Marathi language and Dravidian languages, which can be remediated

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Shared by AWS Machine Learning November 17, 2023

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

Favorite This is a joint blog with AWS and Philips. Philips is a health technology company focused on improving people’s lives through meaningful innovation. Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to

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Shared by AWS Machine Learning November 17, 2023

Foundational vision models and visual prompt engineering for autonomous driving applications

Favorite Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention. Visual prompts can include bounding boxes or masks that guide

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Shared by AWS Machine Learning November 16, 2023

Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights

Favorite 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

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Shared by AWS Machine Learning November 16, 2023

Best prompting practices for using the Llama 2 Chat LLM through Amazon SageMaker JumpStart

Favorite 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 both the commercial and research domains with English as the primary linguistic concentration. Its model parameters scale from an

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Shared by AWS Machine Learning November 16, 2023