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Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

In this post, we provide an introduction to text to SQL (Text2SQL) and explore use cases, challenges, design patterns, and best practices. Today, a large amount of data is available in traditional data analytics, data warehousing, and databases, which may be not easy to query or understand for the majority of organization members.

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Secure Amazon SageMaker Studio presigned URLs Part 2: Private API with JWT authentication

AWS Machine Learning

In this post, we will continue to build on top of the previous solution to demonstrate how to build a private API Gateway via Amazon API Gateway as a proxy interface to generate and access Amazon SageMaker presigned URLs. The user invokes createStudioPresignedUrl API on API Gateway along with a token in the header.

APIs 79
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10 Best Practices to Develop Your Digital Transformation Framework

aircall

A digital transformation strategy is critical for small businesses for many reasons. By following best practices for your digital transformation framework, you also get the benefit of flexibility so you can add and subtract digital tools as your company’s needs change. Clear strategy. We live and work in the cloud era.

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Designing generative AI workloads for resilience

AWS Machine Learning

If you’re performing prompt engineering, you should persist your prompts to a reliable data store. That will safeguard your prompts in case of accidental loss or as part of your overall disaster recovery strategy. Make sure to use best practices for rate limiting, backoff and retry, and load shedding.

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

AWS Machine Learning

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

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What’s All This Fuss About Composability?

ConvergeOne

The underlying technologies of composability include some combination of artificial intelligence (AI), machine learning, automation, container-based architecture, big data, analytics, low-code and no-code development, Agile/DevOps deployment, cloud delivery, and applications with open APIs (microservices).

APIs 90
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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). Adds an IAM authorizer.

APIs 69