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Business Messaging 101: Best Practices by Channel

Quiq

We’ve created a best practices guide to help you embark on your business messaging initiative. Continue reading for business messaging best practices. Some businesses write chatbot scripts to be overly formal: avoiding contractions, using proper English, and completing their thought in one long sentence.

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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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Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

This post shows how companies can use infrastructure as code (IaC) with the AWS Cloud Development Kit (AWS CDK) to accelerate the creation and replication of highly transferable infrastructure and easily compete for AWS DeepRacer events at scale. The steps are as follows: Open AWS Cloud9 on the console.

Scripts 74
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Build custom code libraries for your Amazon SageMaker Data Wrangler Flows using AWS Code Commit

AWS Machine Learning

Therefore, organizations have adopted technology best practices, including microservice architecture, MLOps, DevOps, and more, to improve delivery time, reduce defects, and increase employee productivity. This post introduces a best practice for managing custom code within your Amazon SageMaker Data Wrangler workflow.

Scripts 62
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Introducing an image-to-speech Generative AI application using Amazon SageMaker and Hugging Face

AWS Machine Learning

The DescribeForMe web app invokes the backend AI services by sending the Amazon S3 object Key in the payload to Amazon API Gateway Amazon API Gateway instantiates an AWS Step Functions workflow. A pre-signed URL with the location of the audio file stored in Amazon S3 is sent back to the user’s browser through Amazon API Gateway.

APIs 89
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Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Scripts 104
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Use Amazon SageMaker Data Wrangler in Amazon SageMaker Studio with a default lifecycle configuration

AWS Machine Learning

Lifecycle configurations (LCCs) are shell scripts to automate customization for your Studio environments, such as installing JupyterLab extensions, preloading datasets, and setting up source code repositories. LCC scripts are triggered by Studio lifecycle events, such as starting a new Studio notebook. Solution overview.

Scripts 80