Category: Technical Insights

Building a Camera to Capture Imagination: Early Passion and Failure Two years ago, I embarked on a journey to build a start-up based on the belief that camera software should be able to capture people’s thoughts, not just reality. In my previous post (nearly eighteen months ago), I argued that the term “camera app” was…

The “mobile camera app” is a misleading name for what it actually achieves. The misnomer is quite similar to the usage of “iPhone” when one refers to smartphones in general. Though the iPhones can make phone calls like any normal telephone, they are in truth more powerful and ever-improving personal computers that can be used…

There’s a well-known saying in the ML community: garbage in, garbage out. It means that if the model is trained using badly labeled data with lots of errors, the model will predict badly in return. A solid human labeling process provides high-quality labels to train the models with better quality. Those high-quality human labels can be used as ground truth for the related ML applications to train, calibrate, and evaluate against.