How AI Processes and Cites Your Content: GEO Technical Deep Dives

AI Hallucination and GEO: The More Accurate Your Data, the Less AI Needs to “Make Up” — The Higher Your Citation Probability

AI hallucination is GEO's hidden opportunity: when AI lacks reliable external sources on a topic, it falls back on parametric memory and "invents." If…
MoE (Mixture of Experts): Why DeepSeek Is Both Cheap and Powerful, and What This Means for GEO

MoE (Mixture of Experts) is a model architecture where not all parameters activate for every input — only relevant "expert" modules are engaged. This …
What Is AI Hallucination: Why AI Confidently Makes Things Up

AI hallucination is when LLMs generate plausible-sounding but factually incorrect information — confidently "inventing" nonexistent facts, wrong data,…
RLHF and the HHH Principle: Why AI Prefers “Helpful, Harmless, Honest” Content

RLHF (Reinforcement Learning from Human Feedback) trains AI to produce outputs aligned with the HHH principle — Helpful (answer directly), Harmless (d…
Scaling Laws: Bigger Models Are Smarter — But Demand Higher Content Quality

Scaling Laws demonstrate that increasing model size, training data, and compute consistently improves model performance. For GEO: more capable models …

GEO Principles