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Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning

In this blog post, we demonstrate prompt engineering techniques to generate accurate and relevant analysis of tabular data using industry-specific language. This is done by providing large language models (LLMs) in-context sample data with features and labels in the prompt. Arghya Banerjee is a Sr.

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How Human Resources Can Add Value to Customer Experience Excellence

ClearAction

Use group sharing engines to share documents with strategies and knowledge across departments. Propagate thought leadership: blog/wikis/social media are a great way to tap into peers’ expertise. Create CX playbooks & best practice to guide interactions with customers. —@tcrawford. —@EngageGXD.

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How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker

AWS Machine Learning

Our initial ML model uses 21 batch features computed daily using data captured in the past 2 months. This data includes both playback and app engagement history per user, and grows with the number of users and frequency of app usage. Manolya McCormick is a Sr Software Development Engineer for Amp on Amazon. Real-time inference.

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Improve visibility into Amazon Bedrock usage and performance with Amazon CloudWatch

AWS Machine Learning

In this blog post, we will share some of capabilities to help you get quick and easy visibility into Amazon Bedrock workloads in context of your broader application. With over 35 patents granted across various technology domains, she has a passion for continuous innovation and using data to drive business outcomes.

Metrics 119
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What’s All This Fuss About Composability?

ConvergeOne

The purpose of this blog post is to help folks understand why this is important and how it relates specifically to customer experience. This is where we can currently apply some of the remaining components such as AI, machine learning, automation, big data, and analytics. WORKSHOP] CREATE YOUR PATH TO MODERNIZATION.

APIs 79
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How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

Amp wanted a scalable data and analytics platform to enable easy access to data and perform machine leaning (ML) experiments for live audio transcription, content moderation, feature engineering, and a personal show recommendation service, and to inspect or measure business KPIs and metrics. Data Engineer for Amp on Amazon.

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How Patsnap used GPT-2 inference on Amazon SageMaker with low latency and cost

AWS Machine Learning

This blog post was co-authored, and includes an introduction, by Zilong Bai, senior natural language processing engineer at Patsnap. They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. Zilong Bai is a senior natural language processing engineer at Patsnap.

APIs 96