Today is Pi Day, and it feels like a good excuse to reflect on an old friend.

Most people say goodbye to our friend π after school. I’ve been lucky enough to stay in touch. The relationship has evolved over the years, from a childhood friendship in math class to something that followed me into engineering school and later into my work. It is a good reminder that the academic foundations we build early do not stay behind. They continue to shape how we see the world and how we build what comes next.

At Two Small Fish, the next frontier of computing is our investment thesis. We see it taking shape across five areas: Vertical AI Platforms, Physical AI, AI Infrastructure, Advanced Computing Hardware, and Smart Energy. For Pi Day, I thought it would be fun to pick one equation I learned along the way for each of these five areas, and reflect on how it still connects to the technologies shaping this next frontier.

For Vertical AI Platforms, I think of the Gaussian distribution: f(x) = 1/(σ√(2π)) · e^(-(x-μ)^2 / 2σ²), which is foundational in probability and statistics. Even as AI becomes more vertical and more embedded in real workflows, it still rests on probability, statistics, and uncertainty. π is there too.

In Physical AI, the equation I think of is ω = 2πf, which defines angular frequency. I studied control systems and, one summer during my junior year at university, wrote software to control a robotic arm. That was an early lesson that once software meets motion, π becomes part of how the physical world is described.

In AI Infrastructure, I think of the Fourier transform: X(f) = ∫ x(t)e^(-j2πft) dt. I studied signal processing, my bachelor’s thesis was in image processing, and my master’s thesis was on noisy CDMA wireless networks. That math shaped how I thought about signals, images, noise, and communication then, and Fourier shows up in modern LLMs now.

In Advanced Computing Hardware, my equation is ℏ = h/2π. I studied optics in communications, which included a lot of quantum mechanics, so Planck’s constant was part of the vocabulary of the field. What stayed with me is that π shows up at the quantum level as part of the structure, not just the math.

In Smart Energy, the equation I would use is Xₗ = 2πfL, which calculates inductive reactance. It is a simple reminder that in AC systems, frequency directly shapes behaviour. As energy systems become smarter and more dynamic, π remains embedded in the physics underneath.

That may be why Pi Day still resonates with me. π is one of those rare constants that keeps reappearing across disciplines, from robotics to quantum mechanics, from signal processing to energy systems, and now across the next frontier of computing.

P.S. I also realized I missed mentioning my other friend Euler back on February 7. Next time!