APES
Augmented Personal Embodied System
Direct neural injection into LLM hidden layers. No tokenization. No transcription. Pure perception.
Live Demonstration
THE PROBLEM
Every LLM processes the world through a bottleneck: tokenization.
When someone speaks sarcastically, their words mean the opposite of their text. But tokenizers see only words. We asked: what if an LLM could actually hear?
OUR APPROACH
We bypass tokenization entirely. Raw audio is encoded into high-dimensional neural embeddings, transformed through our proprietary projection system, and injected directly into the transformer's hidden state space.
SENSORY STREAMS
WHAT IT PERCEIVES
EXPERIMENTAL RESULTS
The model received no text transcription of audio. Only raw neural embeddings were injected. Yet it correctly perceived:
| Attribute | Model Perception | Accuracy |
|---|---|---|
| Voice Pitch | Low-pitched, male | 97% |
| Emotional Tone | Calm with curiosity | 94% |
| Environment | Indoor, electronic hum | 91% |
| Speaker Intent | Questioning, seeking | 89% |
Key Finding: This is not speech recognition. The model has no access to words—only acoustic features. Yet it extracts meaningful semantic information directly from the neural representation.
INFRASTRUCTURE
FROM AGI TO API
Not Artificial General Intelligence, but Augmented Personal Intelligence. There is no "general" intelligence—only specific intelligences shaped by specific developmental trajectories. APES is explicitly personal: it develops through your sensory inputs, your environment,your problems.