Why Balanced Ternary {-1, 0, +1} Could Be the Future of AI Hardware**
For 70 years, computing has been binary: 0 or 1. But AI workloads are fundamentally different from traditional computing — and they might need a different number system.
Balanced ternary uses three states: -1, 0, and +1. The zero state is transformative: it means "this weight is unimportant — skip it entirely." That's pruning and quantization combined into one step.
Why this matters now:
Modern LLMs are hitting hardware walls. A 1 trillion parameter model requires 4 TB in FP32 — far beyond any single device's memory. Ternary quantization reduces that to ~200 GB. That's the difference between needing 50 GPUs and fitting on one accelerator.
