{"id":17345,"date":"2020-04-14T14:39:18","date_gmt":"2020-04-14T14:39:18","guid":{"rendered":"https:\/\/applitools.com\/?p=17345"},"modified":"2023-01-10T14:36:24","modified_gmt":"2023-01-10T22:36:24","slug":"ask-your-peers-about-visual-ai","status":"publish","type":"post","link":"https:\/\/applitools.com\/blog\/ask-your-peers-about-visual-ai\/","title":{"rendered":"Ask 288 Of Your Peers About Visual AI"},"content":{"rendered":"

How do you find out about what works? Ask your peers. So, why not ask your peers about Visual AI?<\/p>\n

It\u2019s a difficult time. We all know why, so I won\u2019t dwell on it other than to wish you and yours health and safety above all else.\u00a0<\/strong>What I will dwell on is the human need to retreat and replenish<\/em>. Trapped at home, I\u2019ve found myself learning to cook with Thomas Keller, exploring the universe with Neil deGrasse Tyson, or entertaining like Usher through Masterclass.com<\/a>. My kids are coding their own games and learning about the history of art at Khan Academy<\/a>. These entertaining explorations not only give us a much-needed break, but they also give us an opportunity to learn and grow even as we struggle with the realities around us. It\u2019s a welcome and much-needed distraction.<\/p>\n

With that sentiment in mind – here\u2019s an idea for you. Why not learn about Visual AI (Artificial Intelligence) from 288 of your fellow quality engineers?<\/p>\n

\"Applitools<\/a><\/p>\n

Each one of them spent 11 hours on average comparing their current test framework of either Cypress<\/a>, Selenium<\/a>, or WebdriverIO<\/a>\u00a0to that same framework modernized through Visual AI. You can get a summary of what they learned here.<\/a>\u00a0Even better, you can take the same free Test Automation University course on Modern Test Automation Through Visual AI<\/a>\u00a0and do it all yourself through video tutorials and hands-on learning. Either way, you will find yourself blissfully distracted while learning a cutting-edge approach to test automation.<\/p>\n

\"VisualAI<\/p>\n

288 Testers. 11 Hours Each. That\u2019s 1.5 Years of Quality Engineering Effort!<\/h2>\n

Yes — we were blown away by the enthusiasm to learn Visual AI among the testing community. It says a lot about this group of individuals who recognize the need to keep pushing themselves. In the end, they ended up creating the industry\u2019s largest, highest quality, and freely available data set for understanding the impact of Visual AI on test automation, and ultimately on the impact on quality management and release velocity for modern applications. It\u2019s an amazing amount of learning highly representative of the world of test automation.<\/p>\n

We had representation from major test frameworks:<\/p>\n

\"VisualAI<\/p>\n

Representation from major languages:<\/p>\n

\"\"\"\"<\/p>\n

Representation from 101 countries around the world<\/p>\n

\"VisualAI<\/p>\n

Why Should You Learn Visual AI? Ask your peers.<\/h2>\n

I get it. Quality engineers always seem to be on a treadmill to learn everything. You have new application development frameworks, new coding structures, new test frameworks, and new tools rumbling your way daily. If you plan to learn one more thing, you need a return on your time.<\/p>\n

But, let\u2019s face it – testing needs to keep up with the pace of the business. Survey data tells us that the majority of software teams are struggling with their quality engineering efforts. In a recent survey, 68% of teams cited quality management as a key blocker to more agile releases and ultimately CI\/CD.<\/p>\n

Why? For every test with a handful of conditions and an action, test writers need to write dozens to hundreds of code-based assertions to validate a single response. Traditional frameworks simply don\u2019t have the technical ability to provide front-end functional and visual test automation coverage with the speed and efficiency you need. You end up writing and maintaining too much test code, only to see bugs still escape. It\u2019s maddening and, even worse, it prevents us from doing our core job of managing app quality.<\/p>\n

Isn\u2019t AI Just Smoke and Mirrors?<\/h2>\n

The answer depends on your application. AI promises to solve many modern technical problems, including testing and quality management problems, but it\u2019s hard to separate the truth from the reality in what really works. Many experiments using AI have failed in testing, or these AI approaches require you to \u201crip and replace\u201d your existing tech stack – a dreaded approach that is unrealistic for most teams.<\/p>\n

Rather than asking you to simply trust that Visual AI is different, we decided to prove it, objectively, using real-world examples, in partnership with real quality engineers at real companies dealing with test automation every day.<\/p>\n

\"VisualAI<\/p>\n

Gathering Learning – The Visual AI Rockstar Hackathon<\/h2>\n

To generate all this learning, we built an application involving five common but complex use cases. In November 2019, we issued a challenge to testers all over the world to compete, and learn, by comparing test approaches side-by-side. The competitors created test suites for each of the five use cases using their preferred code-based approach, including Selenium, Cypress, and WebdriverIO. These same quality engineers then repeated the process for the exact same five use cases using Visual AI from Applitools.<\/p>\n

To make it fun and push people to do their absolute best, testers competed for 100 prizes worth a total of $42,000. We judged their submissions on their ability to:<\/p>\n