To create a deep feature—essentially a high-level representation of a subject like "Strange"—you must move beyond surface-level descriptions and layer multiple conceptual "primitives". In both data science and creative writing, this involves stacking simple attributes to reveal a hidden, complex pattern. ⚛️ Step 1: Define the Base Entity
If you were building this feature for an AI model or a narrative, you might define it as: Strange
Start with the subject "Strange" as your core object. Identify its "shallow" attributes—the immediate, literal qualities. Distorted, uncanny, or out-of-place. Emotional: Unsettling, curious, or eerie. 🧬 Step 2: Apply Feature Primitives 🧬 Step 2: Apply Feature Primitives Track if
Track if the strangeness is a single flash (Zen-like) or a sustained transformation (Grokking). Identify its "shallow" attributes—the immediate
"It is an AI-generated portrait where the technical fidelity is high, but the 'strangeness' stems from a societal bias hidden in its training data". 💡 Example Deep Feature: "The Glitch in the Familiar"
For a visual example of how 'deep features' are identified in complex subjects like human facial structures, watch this explanation: Stop Drawing Noses Tony Swaby YouTube• Apr 23, 2026 If you want to refine this further, tell me:
Are you building a (technical) or a character/story (creative)?