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How to Prepare for CMS Test Call Season

CSM Magazine

Train teams to recognize the signs that a call is actually a test call—for example, overly scripted language or formulaic questions. Furnish agents with informational scripts. Kristin joined the company in 1999, rising to CEO in 2006. Ensure that agents can quickly identify a CMS test call. Collect and share past questions.

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There’s No I in Team, but What About AI?

CSM Magazine

While we are happy to chat to friends and colleagues using messaging, text, social media and email, when it comes to contacting our bank, insurance company or healthcare provider, we’re often sent to the back of the phone queue. Voice from the past. Weathering the storm. million Euros in 2014.

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Fine-tune Llama 2 for text generation on Amazon SageMaker JumpStart

AWS Machine Learning

Despite the great generalization capabilities of these models, there are often use cases that have very specific domain data (such as healthcare or financial services), because of which these models may not be able to provide good results for these use cases. The following table compares different methods with the three Llama 2 models.

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Fine-tune and deploy Llama 2 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

AWS Machine Learning

Fine-tune Llama 2 models on Trainium instances using the SageMaker Studio UI and SageMaker Python SDK Generative AI foundation models have become a primary focus in ML and AI, however, their broad generalization can fall short in specific domains like healthcare or financial services, where unique datasets are involved.