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Unbelievable Violation By World Renowned Bank – Record Fines!

Beyond Philosophy

Q: What has two Million phony accounts, 5,300 fired employees, a fine of $185 million and a retiring leader enjoying $124 million in stock and options after retirement? However, getting to your goal by opening a fake account in one of your customer’s names is deplorable. She spoke up and both accounts were closed.

Banking 416
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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

AWS Machine Learning

In some use cases, particularly those involving complex user queries or a large number of metadata attributes, manually constructing metadata filters can become challenging and potentially error-prone. The extracted metadata is used to construct an appropriate metadata filter. model in Amazon Bedrock.

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5 rules for building an incredible brand relationship with your customers!

Beyond Philosophy

Forming an attachment is vital, here, establishing an Emotional Bank account. You might remember Stephen Covey, author of The 7 Habits of Highly Effective People, first proposed the concept of the Emotional Bank Account. You have these accounts with people in your lives, and they make deposits and withdrawals in them all the time.

Banking 363
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‘It’s Out of My Control’ Is a Bad Excuse

ShepHyken

I emphasize the word tried because, unfortunately, there was non-stop, 24-hour-a-day road construction outside the hotel, as the city of Las Vegas is preparing for the Formula One race later this year. Last month I was in Las Vegas for a major convention. I stayed at a very nice hotel, and each night I tried to fall and stay asleep.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

AWS Generative AI Constructs Library – This is an open source extension of the AWS Cloud Development Kit (AWS CDK) that offers multi-service, well-architected patterns for quickly defining generative AI solutions. For this post, we use the AWS CDK and the AWS Generative AI Constructs Library to create the Amazon Bedrock agent.

APIs 131
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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM).

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Build end-to-end document processing pipelines with Amazon Textract IDP CDK Constructs

AWS Machine Learning

Orchestration pipelines need to be created to introduce business logic, and also account for different processing techniques depending on the type of form inputted. Install dependencies Now you install the project dependencies: python -m pip install -r requirements.txt Initialize the account and Region for the AWS CDK.