I believe that technical learning shouldn't feel like a chore. Paper & Logic was born from a desire to document the intricate dance between raw code and creative problem-solving. As an AI practitioner, I spend my days navigating the intersection of neural architectures and human-centric design, translating complex weights into meaningful experiences.
This space is my digital workbench. It's where I dissect new LLM capabilities, share my struggles with PyTorch gradients, and explore how machine learning can be more like an artisan's tool than an opaque black box. My goal is to curate knowledge that is as beautiful to read as it is functional to implement.