Merry Christmas, everyone! Between juggling a full-time job as a data scientist and pursuing my computer science graduate degree part-time, I didn’t think I’d have much bandwidth for extracurricular projects. But when the holidays rolled around, I found myself itching to step away from data engineering and machine learning modeling—and dive headfirst into the world of low-level programming. Surprising? Maybe. But it’s been a thrilling journey so far. Stepping Out of the AI/ML Bubble I love AI/ML. But one thing I’ve realized is that constantly working at a high level (think PyTorch, scikit-learn, XGBoost, etc.) can sometimes obscure what’s really happening under the hood. Sure, I can engineer data, develop models, and conduct data experiments all day long. But when something breaks at a deep level—like in a CUDA kernel, or even just the memory management within my Python environment—I’m reminded there’s a whole world of “lower-level” knowledge I’ve yet to fully explore. ...