Ternary Model Compression via Knowledge Distillation
Memory redesigned from the ground up for three-valued data.
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.
Memory redesigned from the ground up for three-valued data.
What It IS
Technical VisionThe architectural essence — what makes this technology work
A memory hierarchy — L1, L2, HBM — where every level speaks ternary natively. Data enters compressed, travels compressed, and computes compressed. No translation layer, no decompression penalty. Memory that thinks in the same language as the compute.
Abstract
Knowledge distillation techniques for compressing large teacher models into small ternary student models with <2% accuracy loss.
Visual Essence
A memory hierarchy — L1, L2, HBM — where every level speaks ternary natively. Data enters compressed, travels compressed, and computes compressed. No translation layer, no decompression penalty. Memory that thinks in the same language as the compute.
Technology Domains
Related Patents
From the silicon-blueprint visual family
Ternary NPU Compiler Optimization Passes
The ternary chip itself — a complete microarchitecture specification.
Ternary Batch Matrix Multiplication (GEMM)
One execution unit handles both ternary and conventional — switchable precision in a single core.
Hardware-Aware Ternary Network Architecture Search
Ternary data streams through dataflow hardware — bandwidth-optimal inference.
Ternary Tensor Decomposition and Factorization
The compiler knows the hardware — scheduling ternary execution across heterogeneous cores.