artificial intelligence
Articles
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These Challenges Should Not Be an Issue for QA Teams Anymore QA teams play a vital role in ensuring software quality, customer satisfaction, and efficient development. However, challenges such as limited testing talent, poor documentation, and lack of automation persist. AI-powered tools can address these issues by automating repetitive tasks, generating documentation, and improving test efficiency. By leveraging AI, QA teams can enhance their effectiveness and contribute to the success of software development projects. |
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Sponsored Content—SecOps: Streamlining Security with Script Standardization and Automation Writing scripts for security tasks can sometimes cause SecOps teams some difficulty. StackSpot AI, an AI assistant for software development, helps by creating scripts faster and more securely. It simplifies script creation for non-developers, automates updates, and helps maintain consistent security configurations across teams. This improves efficiency and reduces errors in security operations. |
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Artificial Intelligence for Object Detection and Its Metadata Deep learning, particularly Convolutional Neural Networks (CNNs), has transformed object detection in computer vision. These AI models excel at identifying and pinpointing objects in images and videos with high accuracy. However, integrating metadata like object class, location, and time with AI object detection unlocks even greater potential. This enriched data provides valuable insights for applications in autonomous vehicles, healthcare, retail, and manufacturing. |
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AI/ML Testing and Your Test Future (Part 2) AI, AI, AI—it is everywhere. We all read this in the news, see it in politics, in our web traffic, and now it’s coming to our tools. Interestingly, testing has been identified as one of the most essential areas for AI as well as for the safety of the public. This article considers references to start you on your AI test journey, "classic AI" problem areas, and identifies possible concepts to use when testing AI. As usual, it comes down to a willingness to learn new things or apply historical ideas to advance your test career. |
Interviews
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Examining the Impact of AI on Software Testing: A Conversation with Jeff Payne and Jason Arbon
Video
In the software community, the emergence of AI has stoked thoughts of both possibility and concern about its impact. For software testers, the critical questions swirling around AI are: “What is the future of testing in a world of AI? Will testers become obsolete?” Coveros CEO Jeff Payne talked with testing and AI expert and CEO of TestersAI, Jason Arbon, to find out what the emergence of AI means for the testing and software community. |
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From NPR to AI: An Interview with Davar Ardalan Davar Ardalan, founder and storyteller-in-chief of IVOW, talks about how her experience working at NPR helped her launch an AI and storytelling startup. She also discusses how testers, QA analysts, and software engineers are on the front lines of working with users and understanding user engagement, and she explains the importance of finding ways to collaborate with them. |
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Testing in an AI World: A Conversation with Raj Subramanian Raj Subramanian, developer evangelist at Testim.io, talks about artificial intelligence; the differences between AI, machine learning, and deep learning; and what AI means for the future of software testing. |
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Why Testers Should Take Control of the AI Narrative: An Interview with Tariq King and Jason Arbon
Video
In this interview, Tariq King, the senior director and engineering fellow for quality and performance at Ultimate Software, and Jason Arbon, the CEO of test.ai, explain the role artificial intelligence plays in modern testing and why you should establish a foundation right now. |
Conference Presentations
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What’s Our Job When the Machines Do Testing?
Slideshow
The engineering community is beginning to explore the exciting capabilities of AI in order to remove even more mundane and manual tasks from our jobs. Join Geoff Meyer as he provides a framework for organizations to use when considering the application of AI to tasks within their SDLC. |
Geoff Meyer
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Smart Testing with AI Using Data Mining
Slideshow
The approaches to testing are continuously evolving as we try to keep up with the application needs of today’s users. Our industry is facing a new paradigm where AI is helping achieve scale, coverage, and business impact for many organizations. |
Lorna Smyth
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Storytelling in the Age of AI
Slideshow
People are actively engaging in civic tech, social robots are tweeting, and veteran storytellers are capturing stories in new ways using virtual and augmented reality. This explosion of tools, sources, voices, and data is indicative of a new, more collaborative era for storytelling. |
Davar Ardalan
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Improve Testing of AI Systems with "Grey-Box" Testing Technique
Slideshow
There are two main challenges to testing systems that incorporate elements of artificial intelligence. First, the same input can trigger different responses as an AI system learns and adapts to new conditions, and second, it is difficult to understand what the correct response really should.. |
Yury Makedonov
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