Consider how Archimedes had his eureka moment. This is mine. Over time, my learning has become less about accumulation and more about validation, about seeing patterns emerge that I've been sensing but couldn't quite articulate. It all started with a simple observation during a hackathon when I came across a paper on small language models.

Learning is truly a denoising diffusion, an immersion process. Over the last few weeks, it has been a profound denoising—a deep self-retrospection and a humbling experience.

I spent four hours today not writing code. Four hours researching datasets for what should have been a straightforward assignment. And in those four hours, I traveled through molecular biology, pancreatitis research, Van Gogh's artistic portfolio, and back again—all while my actual work sat untouched.

A personal exploration of my evolving relationship with the concept of God—from childhood temple visits to active atheism, and eventually to a more nuanced understanding of belief as a philosophical tool rather than religious submission.

Sometimes I feel like people don't even know what I'm capable of. Sometimes people even try to gaslight me. But this post is really to help me see how far I've come, to articulate my vision for what I need to do, and to lay out the canvas for my thought process and future actions—what I'm planning, what I'm rooting for.(transcribed)

For a long time, I’ve been sharing thoughts and insights here and there—especially on LinkedIn—and many of you know me from those snippets. Now, I’m excited to bring all that informal writing into a more structured and purposeful format. (10-10-2025, Issue:1, Curations and Recommendations done by Human, Editorial : transcribed from Pracha's Voice Notes. )

Navigating AI, ML, and Data Science Careers: My Perspective (transcribed)

I recently read a quote by Confucius—I'm paraphrasing, but the gist is: it's always better to sharpen your tools before getting ready for a competition or task. (transcribed)

I want to quickly add a note here—one particular belief system that's been guiding me for a very long time. I'd like to record it so that people who may not be introduced to it might find it helpful. And honestly, many grad students are studying from no experience, which means they might need some kind of idea about how to tackle things, right? So that's why I wanted to keep this one particular framework.(transcribed)

The Hidden Depths of Linear Regression: A Journey Through Mathematical Foundations and Learning Paradigms (transcribed)