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Quality Assurance, Errors, and AI

O'Reilly Media - Ideas

Generative AI will be used to create more and more software; AI makes mistakes and it’s difficult to foresee a future in which it doesn’t; therefore, if we want software that works, Quality Assurance teams will rise in importance. Security is yet another issue: is an AI system able to red-team an application?

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

Recently, we’ve been witnessing the rapid development and evolution of generative AI applications, with observability and evaluation emerging as critical aspects for developers, data scientists, and stakeholders. In this post, we set up the custom solution for observability and evaluation of Amazon Bedrock applications.

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Evaluating RAG applications with Amazon Bedrock knowledge base evaluation

AWS Machine Learning - AI

Organizations building and deploying AI applications, particularly those using large language models (LLMs) with Retrieval Augmented Generation (RAG) systems, face a significant challenge: how to evaluate AI outputs effectively throughout the application lifecycle.

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Containerization: Better Quality Assurance Through Automation

Datavail

Quality assurance” (QA) refers to the procedures for verifying that a software application meets the defined standards, auditing, and evaluation of a product at each stage of development—from requirements gathering all the way through testing and maintenance. Do you even have what could be described as a “QA organization”?

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Application security platform NeuraLegion raises $4.7 million seed led by DNX Ventures

TechCrunch

Application security platform NeuraLegion announced today it has raised a $4.7 It currently offers NexDAST for dynamic application security testing, and NexPLOIT to integrate application security into SDLC (software development life-cycle). A video call group photo of NeuraLegion’s team working remotely around the world.

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5 dead-end IT skills — and how to avoid becoming obsolete

CIO

CIOs and other executives identified familiar IT roles that will need to evolve to stay relevant, including traditional software development, network and database management, and application testing. In software development today, automated testing is already well established and accelerating.

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World Quality Report: Turn Quality Assurance into Quality Engineering

TechBeacon

In the last several years, organizations have been forced to evolve their IT solutions at breakneck speed. Regardless of industry, IT developments such as cloud migration, digital platform enhancement, and data-management tools have become necessities—not options. in a matter of around eight weeks.".