The Historical Context of Analogue Computing

In 1901, divers stumbled upon an ancient shipwreck near the Greek island of Antikythera, uncovering what is considered the oldest known analogue computer—the Antikythera mechanism. This hand-operated model of our solar system allowed ancient Greeks to calculate and forecast celestial movements, including eclipses, long before they occurred. What motivated the ancients to create such an extraordinary device?

Humans have an inherent tendency to reason through analogy. When observing patterns in nature, we often simplify these patterns into manageable models to predict future occurrences. This tendency is reflected in children's play with miniature versions of real-world objects, demonstrating our intrinsic need to translate complex phenomena into simplified, graspable models.

Everyday Analogue Computers

Fast forward to today, where digital devices dominate our landscape, we often overlook the analogue systems that are integral to our daily lives. For instance, a thermometer serves as a basic analogue computer by translating temperature into a measurable scale. Similarly, a car's speedometer converts the rotational speed of wheels into a readable speed in kilometers per hour. These devices exemplify how analogue computers effectively convert sensory information into quantifiable data.

Another example is the seismometer, which quantifies seismic activity into a comprehensible format. Analogue computers can be found in various medical instruments, voltmeters, and other devices where physical measurements are transformed into understandable models.

Understanding the Distinction: Analogue vs. Digital

Digital computers operate with discrete inputs and outputs, handling symbols to produce results—often represented as binary code (1s and 0s). In contrast, analogue computers process continuous information, producing outputs that vary over time. Consider a speedometer: it measures the motion of an object and displays it on a moving dial.

Digital systems possess fixed architectures that can run various algorithms, making them versatile for problem-solving. For instance, a smartphone can stream videos or perform calculations due to its adaptable architecture. Analogue computers, however, excel at solving specific problems quickly and efficiently, although they lack the versatility of digital systems. Their inherent imperfections can lead to variability in outputs; a minor mechanical issue can significantly affect results.

The Limits of Digital Computing

Despite their superiority in general applications, why aren't digital computers seen as the future? The answer lies in the approaching limits of digital technology. Claude Shannon's groundbreaking work on applying Boolean algebra to information processing has propelled digital computing forward, yet we are nearing a plateau. Over the years, advancements in transistor technology have led to increasingly compact integrated circuits, encapsulated in Moore's Law, which predicts the doubling of transistors approximately every two years.

As we reach atomic scales in transistor design, we confront physical limitations that hinder further densification of circuits. Consequently, future digital computers may not experience significant speed enhancements.

The Potential of Analogue Computing

Real-world challenges often involve complex differential equations, such as the Navier-Stokes equations used to describe fluid dynamics. These equations typically require numerical solutions, which can be computationally intensive. With the rapid advancement of machine learning techniques, the demand for faster and more effective computational models is critical. Analogue computers remain unmatched in speed for solving certain differential equations.

Since Shannon's era, society has largely embraced digital computing. As the limitations of this approach become apparent, interest in analogue computing—once set aside—has rekindled. The pressing question now is whether we can develop general-purpose analogue systems capable of dynamically adapting to solve various problems, or if a hybrid model, integrating both digital and analogue methods, is the way forward. Researchers and startups are actively exploring these possibilities, suggesting that analogue computing holds significant promise for the future.

A Thoughtful Reflection

Robert Fishell shared an insightful perspective after the publication of this article, recalling his engineering studies in the 1970s where he experimented with operational amplifiers—key components of analogue computers. He noted their ability to perform complex calculations with minimal components and expressed optimism about the potential for hybrid digital-analogue systems to tackle a broader range of challenges.

As we navigate this new frontier, only time will reveal the trajectory of analogue computing and its role in the future of technology.

References include works by Sven Köppel et al., research from infinityq, Zhang et al., and startups like Mythic and Analog AI from IBM. For further reading, consider exploring topics such as the physics of mirrors and the significance of pi.