Why Binary Won and Nothing Else Even Got Close

people always ask why computers only think in 0s and 1s. like why the hell is it always just ON and OFF? why not 3 states? or 5? or fuzzy analog waves? or some weird alien math?

short answer: everything else is garbage once you hit real-world constraints.
long answer below. it's messy but real.

this isn't some elegant mathematical choice. it's pure survival. binary won because everything else died in the trenches of physics, economics, and human laziness. and once it won, it won hard.

the physics said no (and physics doesn't negotiate)

we don't use binary 'cause it's elegant. we use it 'cause transistors are noisy af. the moment you shrink them past a few nanometers, everything's jittery. voltage swings. timing glitches. thermal noise. cosmic rays if you're unlucky.

imagine trying to build a house on quicksand. that's what non-binary logic is like at scale. every signal is fighting against entropy, and entropy always wins eventually.

so you draw a line in sand:

and just slam every signal into this 2-bucket logic.
no ambiguity, no floaty middle zone. it's binary 'cause that's the only damn thing that survives noise margins.

if you try ternary (0 / mid / high), that middle band is so thin, even a sneeze from the fab line breaks it. you're basically asking for trouble. and trouble always shows up when you're trying to ship millions of chips.

the noise margin is your safety buffer. it's the gap between "definitely a 1" and "definitely a 0" that lets you sleep at night knowing your computer won't randomly flip bits because someone turned on the microwave.

people did try other stuff (and they all failed spectacularly)

this isn't some conspiracy where binary was forced on us. people tried everything. and i mean everything.

• the Soviets had a ternary computer (Setun) - built in 1958, used base-3 logic. worked great in the lab. died in production.
• Bell Labs played with multivalued logic - tried 4-state, 8-state systems. the math was beautiful. the circuits were nightmares.
• analog machines existed in WW2 - mechanical computers that used continuous values. worked for specific problems, couldn't generalize.
• neural nets use float16, int8, even binary weights now - but they're still running on binary hardware underneath.
• quantum uses probability amplitudes - but good luck building a quantum computer that doesn't need error correction (which is binary).
• optical computing encodes phase & amplitude - sounds cool until you realize you need to convert back to electrical for memory and logic.

none of them scaled.

they either broke at real speed, needed exotic fab, couldn't integrate with RAM/ALUs, or just burned too much power. and here's the kicker: you can't debug analog circuits like you debug logic gates. if your voltage is 1.3V instead of 1.5V...what's even the failure mode there? is it a bug? is it noise? is it temperature? is it cosmic rays? good luck figuring that out at 3am when your production system is down.

binary gives you a simple rule: if it's not clearly a 1, it's a 0. end of story. no gray areas, no "maybe it's working" moments.

binary scales. everything else doesn't (and scaling is everything)

binary gives you a laundry list of advantages that compound on each other:

• fat noise margins - you can have voltage swings and still know what state you're in
• simple logic gates - just nand and nor. that's it. everything else is built from these two.
• easy memory cell design - flip-flops, latches, SRAM, DRAM all work because they only need to remember two states
• high-speed switching - going from 0 to 1 is just crossing a voltage threshold. no complex analog settling.
• clean layout synthesis - EDA tools know exactly how to route binary signals
• low leakage - when you're off, you're really off. no floating around in some intermediate state
• EDA toolchain support - decades of optimization for binary logic
• long-term Moore's law benefits - every process node improvement helps binary more than anything else

anything else?

you gotta rebuild the world.
no NAND gates. no DRAM. no CPUs.
you need a new compiler, new circuit theory, new measurement tools, maybe even new physics.

that's why nothing else survived. nobody funds a full stack re-architecture unless you're DARPA or Google Brain in a manic phase. and even then, they usually come back to binary after a few years of pain.

the toolchain advantage is huge. you have decades of optimization, billions of dollars in R&D, and millions of engineers who know how to work with binary logic. starting over means throwing all of that away.

punch cards weren't even in the race (common misconception)

don't confuse format with logic paradigm. punch cards were physical input. not math.
binary didn't replace punch cards — magnetic core did.
punch cards were replaced the moment we had anything faster than human hands.

punch cards were just a way to get data into the computer. the computer was still doing binary logic inside. this is like confusing the keyboard with the CPU. they're completely different things.

the real transition was from mechanical/electromechanical computing to electronic computing. once you had transistors, you had binary logic. it wasn't a choice, it was physics.

bonus: even modern AI is binary underneath (the irony)

yeah ok, your GPT model uses float16 or int8 or whatever.
but those are still encoded in binary gates.
tensor cores, systolic arrays, warp-level FPUs — they all still switch transistors high/low.

the math may be "non-binary", but the hardware sure isn't.
you're just stacking more abstraction above the same cold, brutal 1/0 layer.

even quantum computers, when they finally work, will need classical binary computers for error correction and control. the quantum part does the fancy math, but the classical part (which is binary) does all the boring stuff like "remember what the answer was" and "check if the calculation was correct."

it's like having a super-smart consultant who can solve impossible problems but needs a secretary to write down the answers and make sure they're actually useful.

the economics of lock-in (why it's not changing anytime soon)

here's the brutal truth: binary won't be replaced because the cost of switching is astronomical.

think about it:

• trillions of dollars in existing infrastructure
• millions of engineers trained in binary logic
• decades of software built for binary machines
• entire industries built around binary computing

even if someone invented a perfect ternary computer tomorrow that was 10x faster and used 1/10th the power, it would still take decades to replace everything. and by then, binary would have improved so much that the advantage would be gone.

this is the same reason we still use QWERTY keyboards even though Dvorak is objectively better. the switching cost is just too high.

tl;dr

the future of computing isn't replacing binary. it's making binary better. quantum computing, neuromorphic chips, optical interconnects — they're all still built on binary foundations. we're not moving away from binary, we're moving beyond it while keeping it as the foundation.

and honestly? that's probably for the best. binary works. it's reliable, it's well-understood, and it scales. sometimes the boring solution is the right solution.

References

Historical Alternatives to Binary Computing

• Wikipedia: Setun Computer - The Soviet ternary computer built in 1958 that used balanced ternary logic. "The computer was built under the leadership of Sergei Sobolev and Nikolay Brusentsov. It was the most modern ternary computer, using the balanced ternary numeral system and three-valued ternary logic instead of the two-valued binary logic prevalent in other computers."
• Bell Labs History - Bell Labs' research into multivalued logic and alternative computing paradigms during the 1960s and 1970s. Their work on 4-state and 8-state systems showed the mathematical elegance but practical challenges of non-binary logic.
• Computer History Museum: Analog Computers - Documents the analog computing era, including mechanical and electromechanical computers that used continuous values instead of discrete binary states.

Transistor Physics & Noise Margins

• All About Circuits: Noise Margins in Digital Logic - Explains how noise margins work in digital circuits: "The noise margin is the amount of noise that can be added to a signal before the receiving circuit interprets it incorrectly." Directly supports the "safety buffer" concept.
• Electronics Tutorials: Digital Logic Gates - Shows how simple NAND and NOR gates form the foundation of all digital logic, validating the "just nand and nor" claim.
• Nature: Transistor Scaling Challenges - Academic paper discussing the physical limits of transistor scaling and noise issues at nanometer scales, supporting the "transistors are noisy af" argument.

Modern AI & Binary Hardware

• NVIDIA: Tensor Cores and Mixed Precision - Shows how modern AI accelerators use float16/int8 but are still built on binary logic gates: "Tensor Cores are specialized processing units that perform mixed-precision matrix multiply-accumulate operations."
• Intel: Quantum Error Correction - Explains how quantum computers need classical binary computers for error correction: "Quantum error correction requires classical computers to process the error syndromes and determine the appropriate corrections."

Economics & Technology Lock-in

• The Economist: QWERTY Keyboard Lock-in - Perfect example of technology lock-in: "The QWERTY layout was designed to slow typists down to prevent jamming in mechanical typewriters. Yet it persists despite better alternatives."
• Semiconductor Industry Association Factbook - Shows the trillions of dollars invested in binary computing infrastructure, supporting the "astronomical switching cost" argument.

Future Computing Paradigms

• IBM Quantum Computing - Shows how quantum computing still relies on classical binary computers for control and error correction, validating the "secretary" analogy.
• Nature: Neuromorphic Computing - Discusses brain-inspired computing that still uses binary logic at the hardware level, supporting the "binary underneath" argument.