I fell in love with coding before university. It started with web development when I was in high school, then evolved into small data apps in college. I’ve been working professionally in data science for the last four years.
Today, I face a problem: I understand the full machine learning pipeline—problem discovery, modeling, deployment, maintenance—but I no longer feel like I’m learning.Yes, I know it sounds like a cringe linkedin post, but not learning something new feels… heavy on the soul.
As LLMs begin to eat software and the economy shifts dramatically, I’ve been asking myself: What do I truly want to do with my life? I realized I still want to work with machine learning — but I don’t want it to stay locked inside a screen. I believe this century will be defined by physical AI. That’s why I’m transitioning from data science to robotics.
My goal is to become a T-shaped AI roboticist—specializing in reinforcement learning, with a working knowledge of neighboring fields like electronics, mechatronics, computer vision and perception systems.
This blog is where I share my beginner steps toward that goal. Feel free to comment! I’m publishing this even though I’m just starting out—because, well, Murphy’s Law: “the best way to get the right answer on the internet is not to ask a question; it’s to post the wrong answer.”
Eren
April 9, 2025
Physical AI is no longer science fiction. 