What knowledge is required to be an exceptional QA professional? Recently, someone posted this on Linkedin and it set me wondering. What are the makings of a good QA? Is it just the skills or attitude? Similarly, when it comes to the quality assurance process, what are the factors that lead to success. A good QA team with poor processes and sub-par test management tools will not be able to deliver their optimum. When it comes to software quality, it is a combination of factors that lead to success.
The tools play their part, as do the processes and your team members. In this age of highly smart and efficient test management tools, it sometimes becomes difficult to choose right. Our blog post on Top 5 Test Management tools of 2019 takes you through the critical features, FAQs and our pick of the top tools that you must consider when shortlisting a potential replacement for your existing tool.
Test Orchestration and all the hype around it
You may have heard the term test orchestration thrown around a lot, of late. What does it mean and how is it different from test automation? In this blog post, we take you through the definition, the process and the benefits of test orchestration when it is done right.
Speaking of test orchestration, the CI/CD pipeline is integral to DevOps success. Here is Lewis from Clearvision, our Atlassian solution partners, explaining how QMetry can help you achieve DevOps success through continuous testing in this SQIT video.
Life of a techie is not all about coding, testing and projects. Some of us also take our bikes and ride up the highest motorable road in the world. Here is the travelogue of Keyur and Mukesh, two proud QMetrians, who took the road less travelled. Enjoy their journey with some breathtaking pictures of Leh and Ladakh, a beautiful part of Incredible India!
QQBOT’s views on Artificial Intelligence (AI)
QBOT Says: We not only need ethically accountable Developers for AI applications, but we also need AI in today’s application that is explainable, controllable and auditable.
Almost everyone in our industry today talks about AI and Digital transformation. AI is somewhat a hyped and overrated term – sometimes it is left to our imagination of what all AI can do (Hollywood directors at their best). Artificial intelligence and machine learning are best thought of as a progression rather than a single revolutionary point in time. Let us understand three terms first to make a point why AI needs to Auditable and Why AI developer needs to be Accountable?
First Gen AI or Narrow AI – Narrow AI can be explained as application of AI to a single automated activity which outperforms human efficiency. Initial adoption of automation and machine execution to perform basic tasks, through compute power and advances in software is enabling early application of use cases in our industry today.
NextGen AI or General AI – AI that can perform any intellectual task a human can is categorized as NextGen AI, or sometimes human-level AI. This is harder to achieve than Narrow AI and is not focused on a specific activity or singular task. For AI to be as intelligent as a human, technological breakthroughs in both hardware and software will be needed to replicate the human brain’s computing power in next 3-5 years.
Space-age AI – Super AI – When AI becomes much smarter than humans, when machines can outwork human thinking, reasoning and especially imagination. I believe this is still at the imagination level for movies – remember the scenes from Black Panther movie. Super AI needs completely new technology at both hardware and software level – we need technology of future that thinks like or better than human brain in a non-linear fashion with many objectives while multiple episodes of learnings come to play to make the decision!!!
While we are barely touching the full potential of what AI has to offer – it is important to start thinking about what AI applications has to offer – is within socio-technology norms or not? When you write today’s Narrow AI application, it is important to think the use case can be explained easily first and its algorithms certainly can be audited for its conclusions. It is also important that NextGen AI applications are controllable as they become multi-dimensional while trying to catch with human intelligence.
As always, we welcome your feedback and comments in the section below.