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 TTT E2E: 128K Context Without the Full KV Cache Tax Introduction Long prompts feel like a superpower right up until you pay for them. You paste in 80K tokens of logs, code, or chat history, and the model spends the next few seconds doing what looks like “thinking,” but is … Read more
Watch or Listen on YouTube AI Accelerators: What They Are, How They Work, and Which Ones Matter in 2026 Introduction If you’ve ever watched your laptop’s fan spin up while a “simple” AI feature runs, you’ve met the real villain of modern computing: math at industrial scale. Neural networks don’t think in sentences. They think … Read more
Watch or Listen on YouTube Next Embedding Prediction (NEPA): Introduction A lot of self-supervised vision feels like an elaborate workaround. Two crops, three heads, four losses, and a decoder you throw away the moment you start fine-tuning. This paper tries something refreshingly blunt. It asks: what if we just did prediction, the way language models … Read more
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