The first Deterministic Computational Standard based on Fractal Geometry.
Replace probabilistic drift with Geometric Certainty.
One Logic. Three Layers. Infinite Scaling.
import cmfo
from cmfo.core import Tensor7
# 1. High-Level Semantic Mapping
# Maps text 'Entropy' to a 7D geometric coordinate on the manifold
t1 = Tensor7.from_text("Entropy is inevitable")
t2 = Tensor7.from_text("CMFO is order")
# 2. Geometric Resonance (Not MatMul)
# Calculates the 'Interference Pattern' between concepts
result = t1.resonate(t2)
print(f"Coherence: {result.coherence:.12f}")
# Output: 0.99999999824 (Bit-Exact Verified)
Designed for Data Scientists. Integrates seamlessly with PyTorch and NumPy. Provides the ease of Python with the raw power of the underlying C-Bridge.
Transformers (LLMs) scale poorly. CMFO scales infinitely.
Faster than Attention on long contexts.
Memory required to store any context state.
Energy per query. Eco-friendly computing.
Standard AI is Stochastic. It "guesses" the next token based on probability weights.
Probabilistic = Hallucination Risk
We map information to an Octonion Fano Plane. A geometric shape in 7 dimensions.
Geometry = Absolute Truth
The state evolves via the Gamma-Phi Resonance. If a path exists, it is found instantly.
Deterministic = Safety Critical
From Software Axioms to Hardware Reality.
Python SDK release. Validation of Tensor7 mathematical axioms. First successful resonance test.
Consolidated codebase. Native C11 Kernel integration. Soliton Error Correction implementation.
High-Availability API Server. Docker/Kubernetes Orchestration. DO-178C Certification Pack.
FPGA & ASIC Hardware Designs. Running CMFO logic on bare silicon (no OS overhead).