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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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Member of the Band – Manuel Rodriguez, Senior Software Quality Assurance Consultant

Gorilla Logic

Manuel Rodriguez — Senior Software Quality Assurance Consultant. Manuel is a Senior Software Quality Assurance Consultant here at Gorilla Logic. He has been working in Development and Quality Assurance for over 10 years. The moment you realize they look up to you as an example, you feel terrified!

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12 AI predictions for 2025

CIO

For example, the previous best model, GPT-4o, could only solve 13% of the problems on the International Mathematics Olympiad, while the new reasoning model solved 83%. Take for example the use of AI in deciding whether to approve a loan, a medical procedure, pay an insurance claim or make employment recommendations.

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How BQA streamlines education quality reporting using Amazon Bedrock

AWS Machine Learning - AI

BQA oversees a comprehensive quality assurance process, which includes setting performance standards and conducting objective reviews of education and training institutions. You can process and analyze the models response within your function, extracting the compliance score, relevant analysis, and evidence.

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Case in point: taking stock of the CrowdStrike outages

CIO

Akamai, for example, uses tools that audit the configuration of cloud software solutions, as well as run other security checks. Immediately after the CrowdStrike outage happened, for example, Akamai ran a tabletop exercise. Were still in the process of looking at everything, Prouty says. Prouty asks.

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Beyond automation: Realizing the full potential of agentic AI in the enterprise

CIO

We then explore design and orchestration strategies, discuss human oversight and governance, and outline practical examples to illustrate deployment and scaling. Use cases and early lessons learned These examples describe some cases where agentic AI can automate workflows and augment human effort.

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Everything you know about computer vision may soon be wrong

TechCrunch

Think about autonomous driving, for example, as a system where it is about pedestrian recognition. Other examples are cameras for industrial sorting, inspection and quality assurance. All these cameras are being used for automated decision-making.

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