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Digital Transformation in Retail Banks: Potential Impact on Brand Equity, Customers, and Employees

Beyond Philosophy

I’m capitalizing the first letter of each word because the pervasiveness of digital transformation has all the feel of Big Data a few years ago and Reeingineering in the 1990’s. Digital innovation in banking can be seen in the transformative way people transact and organize their finances.

Banking 225
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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Retrieval Augmented Generation (RAG) techniques help address this by grounding LLMs in relevant data during inference, but these models can still generate non-deterministic outputs and occasionally fabricate information even when given accurate source material.

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Build a self-service digital assistant using Amazon Lex and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Prerequisites To implement this solution, you need the following: An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. For Data source name , Amazon Bedrock prepopulates the auto-generated data source name; however, you can change it to your requirements.

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Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker

AWS Machine Learning

This framework addresses challenges by providing prescriptive guidance through a modular framework approach extending an AWS Control Tower multi-account AWS environment and the approach discussed in the post Setting up secure, well-governed machine learning environments on AWS.

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MLOps foundation roadmap for enterprises with Amazon SageMaker

AWS Machine Learning

After the data scientists have proven that ML can solve the business problem and are familiarized with SageMaker experimentation, training, and deployment of models, the next step is to start productionizing the ML solution. In the same account, Amazon SageMaker Feature Store can be hosted, but we don’t cover it this post.

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AI-based call center: How do they work?

NobelBiz

This evolution has been driven by advancements in machine learning, natural language processing, and big data analytics. Balto’s technology is particularly important in industries with stringent regulatory requirements, such as finance and healthcare, where compliance is closely scrutinized.

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AI-based call center: How do they work?

NobelBiz

This evolution has been driven by advancements in machine learning, natural language processing, and big data analytics. Balto’s technology is particularly important in industries with stringent regulatory requirements, such as finance and healthcare, where compliance is closely scrutinized.