Could Ternary Computing Have Changed the World? A Look Back at a Forgotten Tech Revolution

So I stumbled across this video where YouTuber Codeolences dives into the fascinating world of ternary computing. If you’ve ever wondered why we use binary (zeros and ones) in our computers, or if there was ever an alternative that might have changed the tech landscape forever, this is a must-watch.

The video explores how a small group of Soviet scientists in the 1950s asked the same question: what if instead of zeros and ones, we used zeros, ones, and twos? They invented something groundbreaking that could still revolutionize computing today. Let’s dive into this intriguing topic.

Why This Topic Matters

The binary system has been the backbone of modern computing for decades. But what if it wasn’t the most efficient or effective way to build computers? Ternary computing, which uses three states (-1, 0, and +1), offers intriguing advantages that could potentially lead to more powerful and energy-efficient devices.

Understanding this alternative can provide valuable insights into why things are the way they are in tech today and open our minds to future possibilities.

The History of Binary Computing

Before we dive into ternary computing, let’s briefly recap how binary became the standard. The roots of binary date back to the 16th century, but it wasn’t until the invention of the transistor in 1947 that modern computing truly began.

The transistor allowed for the creation of binary logic circuits. Because bipolar transistors were more convenient and reliable at the time, binary won out over other systems like ternary. This led to a world dominated by binary systems, where every piece of information is represented as a string of zeros and ones.

Introducing Ternary Computing

Now let’s talk about ternary computing. Unlike binary, which uses two states (0 and 1), ternary uses three (-1, 0, +1). This system has some elegant properties that make it more efficient than binary in certain aspects.

The Advantages of Ternary Computing

One significant advantage is its efficiency. In balanced ternary systems, subtraction is as simple as flipping signs, and negative numbers are integrated directly into the number system. This makes calculations cleaner and more robust.

From a mathematical perspective, base 3 might be the most efficient number base. As Brian Hayes pointed out in his paper “The Third Base,” balanced ternary has some surprising efficiencies that could make it an ideal candidate for certain applications, particularly those requiring complex computations with large datasets.

The Soviet Experiment: Setun

In 1958, a team of Soviet scientists at Moscow State University built a working ternary computer called Setun. According to the project director, Nikolai Brusentsov, it was compact, reliable, and consumed far less power compared to its binary counterparts.

Over 50 units were built and used in Soviet research institutions. Its successor, Setun-70, boasted even more advanced features like a stack-based architecture and support for structured programming. But despite these advancements, the project was eventually abandoned due to lack of funding and industry momentum shifting towards binary systems.

Ternary Computing Today

Although ternary computing faced significant challenges in its early days, it’s quietly making a comeback in some cutting-edge fields like artificial intelligence (AI). Modern deep learning models are incredibly powerful but also very resource-hungry. This is where ternary neural networks come into play.

Ternary Neural Networks

In traditional AI models, each weight in a neural network uses floating-point numbers, which require significant computational power and memory. Ternary neural networks simplify this by restricting weights to just three values: -1, 0, and +1.

This simplification reduces energy consumption dramatically while maintaining similar performance levels on tasks like image recognition. In practice, ternary neural networks can be over three times more energy-efficient than traditional approaches, making them ideal for low-power devices such as wearables and drones.

The Future of Ternary Computing

One of the biggest obstacles to adopting ternary computing was hardware limitations. However, recent breakthroughs have made it possible to produce ternary chips using standard CMOS manufacturing processes—meaning ternary logic can now be produced at scale using existing industrial infrastructure while consuming less power and maintaining signal stability.

A design called TCMOS, developed in South Korea, uses quantum tunneling to introduce a third logic state without needing multiple voltage thresholds. This innovation could change the equation entirely, making ternary computing a viable option for future tech developments.

My Take on Ternary Computing

The idea of ternary computing is fascinating and opens up new avenues for improving efficiency in various technological applications. However, in my experience, integrating such a radical shift into existing systems would be challenging due to the enormous investments already made in binary infrastructure.

That said, I believe that exploring alternative number systems like ternary could lead to significant innovations, especially as we push the boundaries of what’s possible with AI and other resource-intensive technologies. It’s an area worth keeping an eye on!

Practical Takeaways

So here are some practical takeaways from this deep dive into ternary computing:

Binary systems have dominated due to historical convenience and reliability, not necessarily because they’re the best.
Ternary computing offers efficiency advantages that could be beneficial for specific applications like AI.
The resurgence of ternary neural networks shows promise in reducing energy consumption without sacrificing performance.

In conclusion, while binary systems have served us well, it’s worth considering alternative approaches as technology continues to evolve. Ternary computing might just be the key to unlocking new levels of efficiency and power in future devices.

Technical Summary

The exploration of ternary computing reveals a potential shift from the binary systems we’re accustomed to. Balanced ternary, with its -1, 0, +1 states, offers mathematical elegance and computational efficiency that could be highly beneficial for AI and other resource-intensive applications.

Historical attempts like Setun showed promise but were sidelined due to industry momentum towards binary systems. However, recent advancements in ternary chip production suggest that this forgotten technology might make a comeback, offering clear advantages in terms of energy efficiency and performance.

The effectiveness of ternary neural networks demonstrates the practical applicability of these concepts, reducing computational costs while maintaining high levels of accuracy in tasks like image recognition.