Background : For years, I had a habit of writing whenever I traveled. No laptop, no apps, just a pen, a notebook, and pages of cursive observations about airports, flights, fellow travelers, and the emotions that come with being away from home. Two decades later, I decided to digitize those notebooks and make them available on Kindle, eventually publishing them as Transit Tales: Between Airports and Emotions: Travel Blog 20 Years Too Late (View on Amazon). As a first step, I assumed modern LLM-powered handwriting recognition would effortlessly convert the pages into text. Instead, the journey led to an unexpected discovery: handwriting recognition is still far from "solved." The apparent success of modern handwriting recognition is increasingly a combination of imperfect OCR and powerful language-model reconstruction. What users see is often not what the system read, but what the system inferred. Handwriting Recognition: Better Than It Looks, But Not For The Reason You Think ...
Finding Signals in the Noise From hidden patterns to usable systems Sunil Kumar Kopparapu Much of science is the art of finding signal in noise. Looking back, that idea connects every stage of this journey, from algebra and signal processing to neural networks , computer vision, and speech technologies. Looking back, the journey was never driven by a grand plan. Rather, it unfolded through a series of small discoveries, each opening a door to a larger world. One of the earliest lessons was that aptitude is often acquired rather than inherited. As a schoolboy, mathematics did not come naturally. It was only around Class V or VI that algebra began to make sense, thanks to my father. What had first appeared to be a collection of mysterious symbols revealed an underlying logic. There was a quiet satisfaction in realizing that abstract notation could describe concrete relationships. In retrospect, this may have been the first encounter with a recurring theme: hidd...