Post by Pallav Sharda

Three years ago, my curiosity was sparked by a fantastic book: 'The Alignment Problem'. A year later, it caught fire thanks to a weirdly smart chatbot: #ChatGPT. Since then, it feels like I’ve been quietly going to “school,” spending time reading, coding, watching lectures, and retraining my 30+ year-old student brain to grasp the elegant ideas behind #LLMs. Most recently, I spent seven months working through 'Why Machines Learn' by Anil Ananthaswamy—a slow but rewarding read that turned out to be a fitting capstone to this informal journey. All this made me realize something: #ComputerScience might be the most accessible self-taught #STEM field out there. If you can follow your own curiosity, tolerate confusion, and chase down good resources, you can build useful intuition. In the article linked below, I share the books, videos, and turning points that shaped my understanding of large language models—from Brian Christian and Melanie Mitchell to 3Blue1Brown and CS50. If you’re starting your own journey, maybe it’ll help you shortcut a few detours.