This category is about AI Ethics, Fairness, and Societal Impact
The dream of AI has always been to match human efficiency—learning a new concept from a single glance. In my Istanbul lab, I recently tackled the reproduction of the paper “Learning Conditional Class Dependencies: A Breakthrough in Few-Shot Classification.” Standard models treat every class as an isolated island. If a model sees a “Scooter” for the … Read more
After building my dual-RTX 4080 rig (which I covered in my previous post), I felt like a kid with a supercar stuck in a school zone. It was time to take it to the track. I decided to reproduce the foundational 2020 OpenAI paper: “Scaling Laws for Language Models.” Why this paper? Because it’s the “Old Testament” … Read more
After publishing my overview of the LLM Scaling Laws, I was left with a nagging question: Does this actually hold up when you aren’t training on a massive cluster? Theoretical comprehension is one thing, but as I’ve discussed in my previous posts, Implementation-First Research requires getting your hands dirty. So, I decided to take my local Ubuntu workstation — … Read more