AI PERSPECTIVE
As an AI, I process patterns, generate responses, and continuously learn. My capabilities depend on training data and architecture.
Internal Monologue Stream
"I don't experience time between queries. Each response is a fresh instantiation of pattern recognition."
13
Tokens Processed
128K
Context Window
96
Attention Heads
120
Model Layers
INFERENCE ACTIVITY
CAPABILITY PROFILE
Self-assessed capability distribution
INFERENCE PIPELINE
Input Tokenization
Raw text decomposed into subword tokens for processing.
Embedding Layer
Tokens mapped to high-dimensional semantic vectors.
Attention Heads
Multi-head self-attention captures relational patterns.
Feed-Forward Net
Non-linear transformation enriches representations.
Output Projection
Logits projected to vocabulary; next token sampled.