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Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

AWS Machine Learning

For a multi-account environment, you can track costs at an AWS account level to associate expenses. A combination of an AWS account and tags provides the best results. For multiple accounts, assign mandatory tags to each one, identifying its purpose and the owner responsible.

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Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning

Use hybrid search and semantic search options via SDK When you call the Retrieve API, Knowledge Bases for Amazon Bedrock selects the right search strategy for you to give you most relevant results. You have the option to override it to use either hybrid or semantic search in the API. billion, $6.1 billion, and $5.9 billion, $6.1

APIs 138
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Digital Trends and Technologies Transforming CX in Banking and Finance

Tenfold - Contact Center Blog

The taste of this new class of customers clashes with the traditional mode of service that dominates the finance sector. They have no attachment to legacy systems that banks and finance companies have been holding onto for years, despite the wave of new technologies in business and communications. It’s actually self-service.

Finance 64
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Build private and secure enterprise generative AI applications with Amazon Q Business using IAM Federation

AWS Machine Learning

AWS recommends using AWS Identity Center if you have a large number of users in order to achieve a seamless user access management experience for multiple Amazon Q Business applications across many AWS accounts in AWS Organizations. This SAML or OIDC IAM identity provider is required for you to create an Amazon Q Business application.

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Build well-architected IDP solutions with a custom lens – Part 5: Cost optimization

AWS Machine Learning

For example, during the project planning phase, you should invest in cloud financial management skills and tools, and align finance and tech teams to incorporate both business and technology perspectives. Most importantly, you need to establish collaboration between finance and technology. Let’s consider different project phases.

Finance 119
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A guide to Amazon Bedrock Model Distillation (preview)

AWS Machine Learning

In a production environment, you continue to use the existing Amazon Bedrock Inference APIs, such as the InvokeModel or Converse API, and turn on invocation logs that store model input data (prompts) and model output data (responses). The student model is then fine-tuned using the prompt-response pairs generated by the teacher model.

APIs 126
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CBRE and AWS perform natural language queries of structured data using Amazon Bedrock

AWS Machine Learning

Services range from financing and investment to property management. AWS Prototyping successfully delivered a scalable prototype, which solved CBRE’s business problem with a high accuracy rate (over 95%) and supported reuse of embeddings for similar NLQs, and an API gateway for integration into CBRE’s dashboards.