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Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning

Amazon Bedrock empowers teams to generate Terraform and CloudFormation scripts that are custom fitted to organizational needs while seamlessly integrating compliance and security best practices. Traditionally, cloud engineers learning IaC would manually sift through documentation and best practices to write compliant IaC scripts.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

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Improving your LLMs with RLHF on Amazon SageMaker

AWS Machine Learning

Reinforcement Learning from Human Feedback (RLHF) is recognized as the industry standard technique for ensuring large language models (LLMs) produce content that is truthful, harmless, and helpful. Gone are the days when you need unnatural prompt engineering to get base models, such as GPT-3, to solve your tasks. yaml ppo_hh.py

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Your Customers Are Talking, But Are You Listening?

Call Journey

Until recently, the industry standard for reviewing calls coming through a contact center oscillated below 2%. The main one is the automation of important, but costly and ineffective processes, such as Quality Assurance, agent monitoring or script adherence. Agent Script Adherence. Temkin quote. Trending keywords.

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25 Call Center Leaders Share the Most Effective Ways to Boost Contact Center Efficiency

Callminer

Bill Dettering is the CEO and Founder of Zingtree , a SaaS solution for building interactive decision trees and agent scripts for contact centers (and many other industries). Interactive agent scripts from Zingtree solve this problem. Agents can also send feedback directly to script authors to further improve processes.

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Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

As you build applications on AWS, aligning RAG applications with the AWS Well-Architected Framework provides a solid foundation for building enterprise-grade solutions that drive business value while adhering to industry standards. It calls the CreateDataSource and DeleteDataSource APIs. Nitin Eusebius is a Sr.

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Best practices to build generative AI applications on AWS

AWS Machine Learning

We provide an overview of key generative AI approaches, including prompt engineering, Retrieval Augmented Generation (RAG), and model customization. Building large language models (LLMs) from scratch or customizing pre-trained models requires substantial compute resources, expert data scientists, and months of engineering work.