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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.

Scripts 97
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Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

By performing operations (applications, infrastructure) as code, you can provide consistent and reliable deployments in multiple AWS accounts and AWS Regions, and maintain versioned and auditable infrastructure configurations. For latest information, please refer to the documentation above.

APIs 98
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25 Call Center Leaders Share the Most Effective Ways to Boost Contact Center Efficiency

Callminer

Training documentation needs to be updated regularly, and on-going training is important for improving efficiency. 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). Bill Dettering. Jeff Greenfield.

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

AWS Machine Learning

In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

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18 Contact Center Strategies That Actually Work

JustCall

Look at the product from the customers’ point of view to better model your contact center scripts. Leverage Successful Call Scripts Every call center has a list of calls that were extremely successful, some that were okay, and quite a few that failed at closing a deal. How will this product improve their quality of life?

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Best practices to build generative AI applications on AWS

AWS Machine Learning

RAG and agents are methods to connect these generative AI-powered applications to enterprise datasets, empowering them to give responses that account for organizational information and enable running actions based on requests. The retrieved information provides useful context and ideas. This specializes the model for that particular task.

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Gemma is now available in Amazon SageMaker JumpStart 

AWS Machine Learning

. * The `if __name__ == "__main__"` block checks if the script is being run directly or imported. estimator.set_hyperparameters(chat_dataset="True", peft_type="lora", max_input_length="2048", epoch="3") estimator.fit({"training": }) Underlying the training scripts, JumpStart uses HuggingFace SFTTrainer with QLoRA and FlashAttention.

Benchmark 100