Why Ternary Computing Could Have Been the Future

For decades, binary has ruled computing. Every bit in your CPU, every memory cell, every data packet boils down to 0 or 1. But what if we’d chosen a different path? What if computers were built on ternary logic using three states instead of two?

It’s not just a thought experiment. There are solid reasons why ternary might actually be a better fit for information processing.

Information Efficiency

Claude Shannon, the father of information theory, showed that the most efficient number base for representing information is e ≈ 2.718. Since we can’t build a machine with fractional states, the closest integer base is 3.

One trit (ternary digit) carries log₂(3) ≈ 1.585 bits of information.
That’s ~58% more than a binary bit.

In other words, ternary digits pack more information per symbol than binary ever can.

Hardware with Natural Multi-States

Electronics don’t have to be limited to just “on” and “off.” Many physical systems naturally support three stable states, for example:

Voltage levels: low, medium, high
Magnetic spin: negative, zero, positive
Optical polarisation: horizontal, vertical, circular

If we lean into this, we might reduce hardware overhead. Instead of forcing everything into two states, ternary could let us design components that use nature’s full range.

More Compact Memory & Storage

Let’s compare how many digits we need to represent numbers:

Decimal 1,000 = 10 bits in binary
Decimal 1,000 = 7 trits in ternary

The larger the numbers get, the bigger the advantage. Memory footprints shrink, buses move more data per cycle, and storage becomes more efficient.

Balanced Ternary = Cleaner Math

A particularly elegant form of ternary is balanced ternary, which uses digits -1, 0, +1.

Benefits include:

No need for a separate “negative sign” numbers encode naturally.
Subtraction is just addition with -1 values.
Division and rounding can be simpler than in binary.

In other words, CPUs could be simpler and more powerful at the same time.

A Real-World Example: The Setun

This isn’t hypothetical. In 1958, the Soviet Union built the Setun computer, based entirely on balanced ternary.

It was reported to be more memory-efficient than binary machines of its era.
Certain calculations were faster due to streamlined arithmetic.

Binary eventually dominated, but Setun proved that ternary was practical, not just theoretical.

Future Tech May Revive It

The dominance of binary came from manufacturing momentum, not mathematical superiority. But future tech could bring ternary back:

Quantum computing: qutrits can carry more information per particle than qubits.
Optical computing: photons naturally have multiple stable states.

Ternary’s quiet comeback in artificial intelligence research

Some neural networks are being trained with ternary weights (values restricted to -1, 0, and +1). Why?

Memory efficiency: Ternary weights drastically reduce storage requirements compared to full 32-bit or even 8-bit precision.
Faster inference: Operations like multiplication and addition simplify dramatically when weights are ternary, leading to speedups on specialised hardware.
Energy savings: Lower precision means less power-hungry computation, a major advantage when scaling massive AI models.

Researchers have shown that ternary neural networks can achieve comparable accuracy to traditional networks while being more lightweight and efficient.

This trend suggests that AI might become the driving force behind a ternary renaissance, proving that the idea wasn’t just a 20th-century curiosity but a practical 21st-century solution.

As computing pushes beyond silicon, ternary might finally find its sweet spot.

Closing Thoughts

Binary won because it was simpler and cheaper to implement, not because it was the best option. Ternary computing offers:

Higher information density
Simpler arithmetic with balanced ternary
Potential alignment with next-gen tech

It’s a fascinating “what if” and maybe a glimpse of what’s still to come.