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Parameter

Technical

The learnable weights and biases in a neural network that are adjusted during training. Model size is often expressed in parameter count (e.g., 7B, 70B, 405B).

Explained at 5 levels

👶5 Year Old

A tiny knob inside the AI's brain that gets adjusted during learning — billions of these knobs working together make the AI smart.

📚Middle Schooler

The numbers inside a neural network that get tweaked during training. More parameters generally means a more capable model — GPT-4 has hundreds of billions.

🎓College Student

The learnable weights and biases in a neural network that are adjusted during training. Model size is often expressed in parameter count (e.g., 7B, 70B, 405B).

🧑Adult

The trainable scalar values (weights and biases) in a neural network, collectively defining the function the model computes. Parameter count is a primary scaling dimension correlated with model capability.

🧠Genius

The elements of the parameter vector θ ∈ ℝⁿ defining the model's learned function — with scaling laws establishing power-law relationships between parameter count, training compute, dataset size, and loss.