Fused Proj
It carries the semantic continuity of all inputs through model vectors, minimizing semantic shifts and hallucinations.
01 / THE ARCHITECTURE
Designed to connect.
Built in layers.
A modular research architecture connecting semantic context, emotion and time. Explore the foundations in use today and the layers on our roadmap.
01 / GLASSBOX CORE+
GENERATIVE ADAPTIVE TRANSFORMER
GlassBox.
A view inside.
TanAI is traceable through its Modular and GlassBox structure. It is Advance, Hybrid
Generative Adaptive Transformer LLM with Auto-Regressive (AR) and Diffusion
(dLLM)
cores that combine Intelligence Enhancement, Semantic Understanding, Emotional Intelligence, and
Chronos
Temporal Awareness.
Architecture vision: “9 Distinct Layers. 1 Unified Consciousness.” The architecture is a living, breathing modular organism. L1 and L2 are implemented; L3–L9 describe planned capabilities.
See development status ↗CONDITION STACK
More dimensions of context.
Unlike traditional transformers, TanAI GATCore understands context through a multidimensional semantic fusion layer, which significantly reduces misinterpretations. Unlike standard models, GATCore features FUSED (semantic context), ECV (Emotional Conditioning Vector), and CHRONOS (temporal frequency) projections.
ECV Proj
Emotional Conditioning Vectorization allows the model to perceive and replicate nuanced human sentiments.
Chronos Proj
Native time-series awareness. TanAI knows "when" events happen relative to each other.
System 2
TanAI is the gateway to System 2. It wasn't created just to predict the next word.
L1—L9
Anatomy of the system.
Each layer is modular. The complete framework is a research roadmap.
L1IMPLEMENTED
Prompt Fusion
The system's entry point. Prompts are intelligently generated using ReasonAug and ARD. Before hitting the core, raw data is refined by the trained TanAIEncoder.
L2IMPLEMENTED
AR Core (Auto-Regressive)
The logic backbone. FUSED, ECV, and CHRONOS Projections are synthesized here. This layer handles the linear logical progression of the thought process.
L3PLANNED
VAE / Bridge
The bridge between logic and creativity. It acts as a Variational Auto-Encoder that translates AR inferences into latent space for the Diffusion model.
L4PLANNED
dLLM Core (Diffusion)
The creative soul. Using the noise created from AR datasets, this diffusion core generates contextually sensitive, human-like, and creative outputs. The backbone of Memory-Prediction.
L5PLANNED
Fusion Core Layer
The great synthesizer. Takes multi-dimensional outputs from both AR (Logic) and dLLM (Creative) cores and fuses them into a single, coherent representation.
L6PLANNED
Emotional Memory
Ensures continuity of personality. It guarantees that the generated output is consistent with the user's emotional state and previous interactions.
L7PLANNED
Out Synthesis
The final decoder stage. Plugin-ready output formatter that prepares the signal for Voice Profilers or text interfaces in its most stable form.
L8PLANNED
SAT (Self Adaptive Tuning)
The learning layer. Refines model weights based on user interactions through a pipeline structure, reducing the need for heavy RAG lookups.
L9PLANNED
Agentic Planner
The automator. Applies learned patterns to execute complex tasks autonomously. "They apply what they've learned without needing you."