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Few-shot prompt engineering and fine-tuning for LLMs in Amazon Bedrock

AWS Machine Learning

Investors and analysts closely watch key metrics like revenue growth, earnings per share, margins, cash flow, and projections to assess performance against peers and industry trends. Draft a comprehensive earnings call script that covers the key financial metrics, business highlights, and future outlook for the given quarter.

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Transitioning off Amazon Lookout for Metrics 

AWS Machine Learning

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning

This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. All of this data is centralized and can be used to improve metrics in scenarios such as sales or call centers.

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning

A reverse image search engine enables users to upload an image to find related information instead of using text-based queries. Solution overview The solution outlines how to build a reverse image search engine to retrieve similar images based on input image queries. Engine : Select nmslib. Distance metric : Select Euclidean.

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Executive Report: The Customer Data Too Often Overlooked by the C-Suite

A recent Calabrio research study of more than 1,000 C-Suite executives has revealed leaders are missing a key data stream – voice of the customer data. Download the report to learn how executives can find and use VoC data to make more informed business decisions.

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Improve LLM performance with human and AI feedback on Amazon SageMaker for Amazon Engineering

AWS Machine Learning

The Amazon EU Design and Construction (Amazon D&C) team is the engineering team designing and constructing Amazon warehouses. The Amazon D&C team implemented the solution in a pilot for Amazon engineers and collected user feedback. of overall responses) can be addressed by user education and prompt engineering.

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How Vericast optimized feature engineering using Amazon SageMaker Processing

AWS Machine Learning

One aspect of this data preparation is feature engineering. Feature engineering refers to the process where relevant variables are identified, selected, and manipulated to transform the raw data into more useful and usable forms for use with the ML algorithm used to train a model and perform inference against it.

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Contact Center Metrics That Matter

Speaker: Nate Brown, Co-Founder, CX Accelerator

Do you have the right metrics in place to assess your true impact? Learn how to round out your CX dashboard with metrics related to the employee experience, the customer journey, and business results. How to move beyond effort using Customer Engagement Score, Customer Growth Engine and more to develop a CX dashboard.

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The Challenges of Omnichannel: Why so Many Contact Centers Struggle with Digital Self-Service

To find how contact centers are navigating the transition to omnichannel customer service, Calabrio surveyed more than 1,000 marketing and customer experience leaders in the U.S. about their digital customer communication strategies. Read the report to find out what was uncovered.