P015Filed

Cybersecurity Threat Detection via Ternary Networks

Generative AI runs on edge — diffusion models in your pocket.

AU Application
2023900015
Filing Date
25 March 2023
Index Number
P015
Figures
10 figures
Batch / Category
Applications

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.

Generative AI runs on edge — diffusion models in your pocket.

What It IS

Technical Vision

The architectural essence — what makes this technology work

A mobile device generating photorealistic images in real-time. Inside, a diffusion model's denoising steps execute entirely in ternary — each step a compare-and-select cascade rather than a floating-point avalanche. Images bloom from noise on a device that fits in a palm.

1/5
Explore the buyer's journey across 5 perspectives

Abstract

Real-time anomaly detection in network traffic using ternary neural networks, enabling on-device security processing without cloud offloading.

Visual Essence

A mobile device generating photorealistic images in real-time. Inside, a diffusion model's denoising steps execute entirely in ternary — each step a compare-and-select cascade rather than a floating-point avalanche. Images bloom from noise on a device that fits in a palm.

Visual Family:edge-bloom

Technology Domains

Related Patents

From the edge-bloom visual family