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Build and train ML models using a data mesh architecture on AWS: Part 1

AWS Machine Learning

Typically, large financial services organizations have multiple LoBs, such as consumer banking, investment banking, and asset management, and also one or more analytics and ML CoE teams. Allow the consumer banking LoB to share data products into the central governance layer. Consumer banking LoB (data producer).

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The 2021 Caller Authentication Guide for Contact Centers

pindrop

From email to bank logins, many companies have employed tools like two-factor verification to make their services more secure. SYMPTOMS” OF BAD CALLER AUTHENTICATION PRACTICES. Keep things simple with API integration whenever possible. Pindrop’s APIs are straightforward – the footprint is small, they’re effortless to use.

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

Generative AI definitions and differences to MLOps In classic ML, the preceding combination of people, processes, and technology can help you productize your ML use cases. If an organization has no AI/ML experts in their team, then an API service might be better suited for them. Only prompt engineering is necessary for better results.

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Information extraction with LLMs using Amazon SageMaker JumpStart

AWS Machine Learning

As a starting point, you can refer to the model documentation which typically includes recommendations and best practices for prompting the model, and examples provided in SageMaker JumpStart. To deploy a model from SageMaker JumpStart, you can use either APIs, as demonstrated in this post, or use the SageMaker Studio UI.

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Integrate QnABot on AWS with ServiceNow

AWS Machine Learning

The workflow includes the following steps: A QnABot administrator can configure the questions using the Content Designer UI delivered by Amazon API Gateway and Amazon Simple Storage Service (Amazon S3). The Content Designer Lambda function saves the input in OpenSearch Service in a question’s bank index. Choose Create function.

Chatbots 102
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Welcome to a New Era of Building in the Cloud with Generative AI on AWS

AWS Machine Learning

They want to be able to easily try the latest models, and also test to see which capabilities and features will give them the best results and cost characteristics for their use cases. With Amazon Bedrock, customers are only ever one API call away from a new model. Meta Llama 2 70B, and additions to the Amazon Titan family.

APIs 125
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Accelerate client success management through email classification with Hugging Face on Amazon SageMaker

AWS Machine Learning

MLOps – Because the SageMaker endpoint is private and can’t be reached by services outside of the VPC, an AWS Lambda function and Amazon API Gateway public endpoint are required to communicate with CRM. The function then relays the classification back to CRM through the API Gateway public endpoint.