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Read graphs, diagrams, tables, and scanned pages using multimodal prompts in Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API.

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Build verifiable explainability into financial services workflows with Automated Reasoning checks for Amazon Bedrock Guardrails

AWS Machine Learning

An ApplyGuardrail API call is made with the question and an FM response to the associated Amazon Bedrock guardrail. The Automated Reasoning checks model is triggered with the inputs from the ApplyGuardrail API, building logical representation of the input and FM response. To learn more, visit Amazon Bedrock Guardrails.

APIs 80
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Process mortgage documents with intelligent document processing using Amazon Textract and Amazon Comprehend

AWS Machine Learning

The following is a high-level overview of the steps involved: Extract UTF-8 encoded plain text from image or PDF files using the Amazon Textract DetectDocumentText API. For structured and semi-structured documents containing forms and tables, we use the Amazon Textract AnalyzeDocument API. Train a custom classifier using the CSV file.

APIs 107
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Customizing coding companions for organizations

AWS Machine Learning

This benefits enterprise software development and helps overcome the following challenges: Sparse documentation or information for internal libraries and APIs that forces developers to spend time examining previously written code to replicate usage. Inadvertent use of deprecated code and APIs by developers.

APIs 110
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Architecture to AWS CloudFormation code using Anthropic’s Claude 3 on Amazon Bedrock

AWS Machine Learning

The workflow consists of the following steps: The user uploads an architecture image (JPEG or PNG) on the Streamlit application, invoking the Amazon Bedrock API to generate a step-by-step explanation of the architecture using the Anthropic’s Claude 3 Sonnet model. The following diagram illustrates the step-by-step process.

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How to Evaluate Call Center Software Vendors for Customer Data Platform Solutions

NobelBiz

Understanding Customer Data Platforms (CDPs) Although similar tools existed in the past, the term Customer Data Platform was first used in 2010. Ask about their API integrations API integrations are important when a call center looks for a CDP vendor because they allow businesses to connect their existing systems and tools to the CDP.

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Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

AWS Machine Learning

If you need an automated workflow or direct ML model integration into apps, Canvas forecasting functions are accessible through APIs. The SageMaker Canvas UI lets you seamlessly integrate data sources from the cloud or on-premises, merge datasets effortlessly, train precise models, and make predictions with emerging data—all without coding.

Finance 123