Exploring AI Learning, the specifics of Large Language Models, including architecture, prompt engineering, fine-tuning, RAG, and their application in text-based tasks.
Watch or Listen on YouTube General Intelligence vs Universal Intelligence Debate Breakdown Introduction People love the idea of a single finish line called “AGI.” One morning you wake up, open your laptop, and the machine on the other side has “arrived,” it writes proofs, plans projects, designs hardware, and stays useful without constant babysitting. That … Read more
Watch or Listen on YouTube Chain of Thought Monitorability: Panopticon Or Protection? Introduction Reasoning models did something quietly radical. They turned “thinking” into an explicit artifact. Instead of jumping straight to an answer, they often generate an internal chain-of-thought and only then produce the user-facing output. That shift is exciting, and it’s also a new … Read more
Watch or Listen on YouTube Nvidia H200 vs B200: The Practical 2025 Guide To Specs, Price, And What Changes Introduction GPU shopping used to be simple. You picked the fastest card you could afford, shoved it into a server, and tried not to think about power bills. Now it’s weirder. Peak FLOPS are still up … Read more
Watch or Listen on YouTube Google Titans AI: Inside “Miras” Introduction If you have ever tried to make a large language model reason over an entire codebase, legal case, or weeks of logs, you know the feeling. Context windows grow, prompts get longer, costs explode, and yet the model still forgets something important halfway through. … Read more
Watch or Listen on YouTube AI Efficiency Analysis: Did We Really Gain 22,000x Speed, or Is It Just Brute Force 1. Introduction There is a number floating around the industry that feels almost magical. You have likely seen it cited in slide decks or enthusiastic Twitter threads. The claim is that between 2012 and 2023, … Read more
Watch or Listen on YouTube TPU vs GPU: The Ultimate Guide to the AI Hardware War Introduction News that Meta is exploring Google’s TPUs sent a quiet shockwave through the tech industry. For years the narrative was simple. If you wanted to do serious AI work you bought NVIDIA. You paid the “green tax.” You … Read more
Watch or Listen on YouTube LLM Inference Explained: How AI Predicts Tokens and How to Make It Faster 1. Introduction A trained model is just a static file. It sits on your hard drive, a massive binary blob of weights and biases, doing absolutely nothing. It is potential energy waiting for a kinetic trigger. LLM … Read more