Wikipedia notes that Artificial Intelligence is often described as machines (or computers) that mimic “cognitive” functions that humans associate with the human mind, such as “learning” and “problem solving”
Algorithms that have been around for a long time like OCR (Optical Character Recognition), by definition, are AI. While this may be true, modern technology trends raise the bar on what is considered AI. Today, the usage of machine learning (ML) and deep learning (DL) models is what is typically accepted as AI.
Applitools Visual AI is made up of a network of hundreds of algorithms implemented using different tools and approaches ranging from hand-coded rule based algorithms to deep learning. Complex algorithms automatically clean up and tag data which is then used for training the machine learning and deep learning models. Since launching the Visual AI engine has analyzed over 1 billion images and has access to an endless supply of diverse data that has been collected over many years from tens of thousands of different products that is uniquely available to us.
AI powered accuracy
One example of this network of AI algorithms is the ‘Layout Match’, a complex algorithm that utilizes dozens algorithms to accurately compare the layout and structure of a screen. These algorithms are task specific, so you might have one that separates the foreground from the background, another that looks closely at images to determine if it’s a photo or icon, one that handles tables – and so on. Some of these algorithms leverage deep learning and machine learning, while others do not. Our philosophy is using the most suitable approach to solve each sub-problem.
Through the use of the above described approach, Applitools Visual AI has achieved 99.9999% accuracy and continues to be evolved to address new use cases such as accessibility testing and more.