Image credit : totalphase & Unsplash We collect tons of test results, but are we learning from them? In many QA steps, test results end up pass/fail summaries with little context. But that approach leaves patterns, root causes, and optimization opportunities buried. This is where AI can step in, not to replace us, but to […]
Image Credit: dataconomy When training a machine learning model, one of the most common question is, How many epochs should I run? The answer isn’t always straightforward. An epoch refers to one complete pass of the training dataset through the model. Running multiple epochs can bring big benefits, but also big risks if not handled […]
As AI becomes smarter, it is easy to assume machines can work entirely on their own. But in reality, even the best models need a human touch. That’s where Human in the Loop (HITL) comes in. It is a process where humans actively guide, review and fine tune the AI, especially in situations where data […]