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Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

AWS Machine Learning

Before you get started, refer to Part 1 for a high-level overview of the insurance use case with IDP and details about the data capture and classification stages. In Part 1, we saw how to use Amazon Textract APIs to extract information like forms and tables from documents, and how to analyze invoices and identity documents.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

Organizational resiliency draws on and extends the definition of resiliency in the AWS Well-Architected Framework to include and prepare for the ability of an organization to recover from disruptions. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

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Reduce cost and development time with Amazon SageMaker Pipelines local mode

AWS Machine Learning

One of the main drivers for new innovations and applications in ML is the availability and amount of data along with cheaper compute options. To follow along in this post, you need the following: An AWS account. Register model step (model package). Fail step (run failed). The following diagram illustrates our pipeline. Prerequisites.

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Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM).

APIs 71
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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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Exploring The Restaurant of Tomorrow at FSTEC

Interactions

In 2013, Aloha (NCR) and MICROS (Oracle) accounted for about 43% of the restaurant POS market; by 2017, that number was down to about 30% and continues to fall. A big point of discussion during breakout sessions and over drinks (yes, really!) was the concept of standardized APIs across multiple technologies.

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