The Wisdom of Crowds
In 1906, Francis Galton discovered something remarkable at a county fair. When he averaged the guesses of 787 people trying to estimate the weight of an ox, the crowd's average was nearly perfect—better than any individual expert.
This "wisdom of crowds" effect has been replicated countless times. Diverse groups consistently outperform homogeneous ones, even when the homogeneous group consists of experts.
AI Models Are Like Thinkers
Each AI model has been trained differently. Claude emphasizes safety and nuance. GPT-4 excels at reasoning and coding. Gemini brings multimodal understanding. Mistral offers efficiency and specific domain strengths.
When you use just one model, you get one "thinker." When you combine them, you get the AI equivalent of a diverse team.
Complementary Blind Spots
Every model has blind spots—topics where it underperforms, biases from its training data, reasoning patterns it defaults to. But crucially, different models have different blind spots.
When Claude misses something, GPT-4 might catch it. When both miss something, Gemini might see it. The combination is more robust than any individual model.
How Big Words Leverages This
Big Words doesn't just run multiple models in parallel—it makes them interact. They challenge each other's assumptions, build on each other's ideas, and arrive at conclusions that no single model would reach alone.
That's the power of multi-agent AI dialog.