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Three cards labeled QUERY, KEY, VALUE — the three projections every transformer attention layer computes.

What is attention? The mechanism behind every modern LLM

The mechanism every modern LLM is built on, explained from scratch. Q/K/V, the scaled dot-product formula walked through term by term, multi-head attention, positional encoding, and the engineering variants that show up in 2026. With a live interactive lab.

Diagram contrasting total parameters with active parameters in a mixture-of-experts AI model.

What is mixture-of-experts? The architecture behind cheaper trillion-parameter AI

Mixture-of-experts is how a 671-billion-parameter model can cost less per token than a 70-billion-parameter one. A plain-English guide to MoE, active vs total parameters, routers and experts, and why open-weights frontier labs picked the architecture first.

An editorial infographic showing generated examples moving through seed, generate, filter, evaluate, and train stages.

What is synthetic data? The training material AI is starting to make for itself

Synthetic data is generated training material. It can teach models faster, protect privacy, and also cause model collapse when used badly. Here is the practical version.

The official Nightshade illustration of AI training data poisoning: a model trained on subtly modified images learns to associate words with wrong concepts.

What is dataset poisoning? The supply-chain risk inside every model

Dataset poisoning happens when AI training data is deliberately contaminated. Here's what the research proves, what may be happening in practice, and what remains uncertain.

Diagram of the full RLHF pipeline: an initial language model and a tuned policy generate responses; a reward model scores them; PPO updates the policy while a KL term keeps it from drifting t

What is RLHF? The training trick that made ChatGPT useful

RLHF is the three-stage recipe — supervised fine-tuning, reward modelling, RL — that turned big base models into chatbots people actually use. Here's how it works and what it doesn't fix.