Exploring AI Learning, the specifics of Large Language Models, including architecture, prompt engineering, fine-tuning, RAG, and their application in text-based tasks.
Self-Distillation Fine-Tuning (SDFT): The On-Policy Trick That Makes Continual Learning Finally Work Play Introduction Fine-tuning an LLM feels like doing surgery with oven mitts. You make one clean cut, the patient learns a shiny new skill, then you check the vitals and realize it forgot its own name. That is the default behavior of supervised … Read more
TTT-Discover Explained: Why Test-Time RL Outruns Best-of-N Sampling Play Introduction You have seen this movie. A model tackles a hard problem, fails, tries again, fails differently, then repeats the same mistake with fresh confidence. You can sample more. You can crank temperature. You can run best of n sampling until the GPU fans sound like … Read more
D4RT By DeepMind, Real-Time 4D Scene Reconstruction From One Video Play Introduction There’s a small magic trick your brain pulls off every time you watch a video. You do not just see pixels. You infer a world. You know what’s behind the mug when a hand passes in front of it. You keep track of … Read more
Mechanistic Interpretability (2026): Reverse-Engineering LLMs Play Introduction Mechanistic interpretability is the “take it apart and see how it works” branch of AI interpretability: instead of treating a model as a black box and correlating inputs to outputs, you try to recover the internal computations that produce behavior, down at the level of activations, learned features, … Read more
Watch or Listen on YouTube Anthropic Assistant Axis, Persona Drift, Jailbreak Defense Claude resources page 1. Introduction: The Mask Everyone Has Felt Spend a few evenings with chat models and you start noticing the costume changes. Most of the time the model sits in a familiar groove, helpful, tidy, a little polite. Then the conversation … Read more
Watch or Listen on YouTube Meta Dr. Zero Explained: Self-Evolving Search Agents Without Human Data Introduction Everyone wants “agents” that can look things up, chain multiple steps, and feel like a junior researcher who never sleeps. The annoying part is what it takes to get there: piles of hand-curated instruction data, constant refresh cycles, and … Read more
Watch or Listen on YouTube The AI Brain Anatomy: How The Synergistic Core Killed The Stochastic Parrot Hajra, A clinical psychologist research scholar reads the paper, then squints at our favorite arguments. 1. Introduction: The Ghost In The Machine “Stochastic parrot” used to be the healthiest two word reply on the internet. It was a … Read more