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Generative AI is a type of artificial intelligence (AI), one of many, where it is trained on a very large set of data. After training, if you give it some direction, it generates something for you.

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As the complexity of software systems increases, so does the importance of rigorous testing. Traditionally, crafting test cases has been a manual and time-consuming process, often prone to human error and oversight. However, with generative AI, a new era of automated test case generation is upon us, promising to revolutionize the way we ensure software

Data is the lifeblood of innovation and technology and the need for comprehensive testing strategies has never been more critical. Testing ensures the reliability, functionality, and security of software applications, making it indispensable in the development lifecycle. However, traditional testing methods often face challenges in accessing diverse and realistic datasets for thorough evaluation. Enter generative

The purpose of Multifactor Authentication is to defeat bots. Software test automation solutions look like they are bots. All of the MFA implementations depend on human interaction. To be able to successfully automate testing when MFA is in use usually starts with a conversation with the dev team. The dev team is just as interested

The need for robust testing methodologies in the world of software development has never been more critical. As applications become increasingly complex and interconnected, ensuring their reliability and functionality across diverse environments is a monumental challenge. However, with the advent of Gen AI, a transformative shift is underway in how software testing is approached, promising

Continuous Integration and Deployment (CI/CD) pipelines are the backbone of modern software development, ensuring rapid delivery of high-quality code. As technology advances, so does the need for more efficient and reliable CI/CD processes. Enter Gen AI powered Appvance IQ (AIQ), an AI-native software quality platform that transforms CI/CD optimization by automating testing, identifying bottlenecks, and

When it comes to software development, ensuring the reliability and functionality of applications is paramount. Traditional methods of software testing often rely on manual creation of test cases, a time-consuming process prone to human error and oversights. However, with the advent of AI technologies, particularly generative AI, a new era of test case generation has