Ternary Network Robustness and Adversarial Training
Fleet-scale management of ternary NPUs — predictive maintenance across thousands of chips.
Explore the Vision
Discover this technology through five complementary perspectives — from technical architecture to partnership outcomes. Each layer reveals a different aspect of how this innovation creates value.
Fleet-scale management of ternary NPUs — predictive maintenance across thousands of chips.
What It IS
Technical VisionThe architectural essence — what makes this technology work
A fleet dashboard showing thousands of ternary NPUs deployed across data centres, edge nodes, and devices — each one reporting health, utilisation, and predicted failure through the ternary intelligence that runs on it. The fleet manages itself.
Abstract
Techniques for training ternary networks to be robust against adversarial examples and input perturbations, maintaining accuracy under attack.
Visual Essence
A fleet dashboard showing thousands of ternary NPUs deployed across data centres, edge nodes, and devices — each one reporting health, utilisation, and predicted failure through the ternary intelligence that runs on it. The fleet manages itself.
Technology Domains
Related Patents
From the silicon-constellation visual family
Activation Function Approximation for Ternary Domains
Multiple chips think as one — ternary models spanning beyond a single die.
Measurement and Decoherence in Ternary Qudits
Control signals hide inside the inference stream — zero-state density carries the message.
Ternary Power Quality Monitoring and Prediction
In-band signalling across NPU networks — the zero state is the control plane.
Quantum Error Correction for Ternary Systems
Swarm inference — edge devices collaborating to run models larger than any one of them.