Venture Insights: Demystifying Quantum: The Next Computing Revolution

Just as classical computing gave rise to pioneers like Microsoft and Apple, quantum computing is poised to mint the next generation of tech titans. With the potential to tackle problems that overwhelm today’s powerful supercomputers, quantum could unlock breakthroughs in drug discovery, material science, and AI. In a recent analysis, Boston Consulting Group reaffirmed its projection that quantum computing could generate $450B to $850B in economic value, supporting a hardware and software market worth $90B to $170B by 2040.

In this primer, we explore what quantum computing is, why it matters now, and why investors and innovators — including Alumni Ventures — are paying attention. As Chintan Mehta, CIO and Head of Digital Technology and Innovation at Wells Fargo, put it: quantum “could be exponentially faster than anything we have today — if we reach there, it will blow up everything else in terms of speed and efficiency.”

What is Quantum Computing?

Think of a quantum computer as a fundamentally different kind of calculator — one that uses the rules of physics, not just logic, to perform computations. While classical computers process bits (0s and 1s), quantum computers use qubits.

Contrast this to traditional CPUs that chug through possibilities one at a time. Because quantum computers can an evaluate many potential solutions in parallel, they are exponentially faster as solving specific problems in chemistry, logistics, and optimization. The math is wild. The potential is wilder.

Companies like Xanadu (an AV portfolio company) and Google have demonstrated quantum supremacy — solving a problem that would take a classical supercomputer millions of years to solve.

What Can Quantum Computing Actually Do?

Quantum computing is not currently seen as a general-purpose replacement for the classical computer, but instead as a specialized tool for tackling problems that are too complex for today’s machines. The first breakthroughs are likely to emerge in fields where vast numbers of variables interact in ways classical systems can’t easily simulate, such as these examples.

While full-scale impact is still years away, even incremental progress in these domains could create compounding advantages — and entire new industries.

It’s similar to the early days of the internet or the PC revolution in the 70s. At that time, no one really knew what these technologies would be used for. For instance, the Apple II was marketed in 1975 or 1976 as a tool for housewives to use in the kitchen for recipes. It wasn’t until later that decade that spreadsheets, word processing, and other business applications emerged. Quantum computing will likely follow a similar trajectory.

— Christian Weedbrook, Founder and CEO of Xanadu

How Are Quantum Computers Built?

There’s no single blueprint for building a quantum computer. Instead, researchers and startups are exploring several competing architectures — each with its own physics, promise, and pitfalls. Below are the major approaches, including Alumni Ventures portfolio companies pioneering each path.

Quantum + AI: A Parallel Revolution

Quantum computing and AI are often viewed as separate technological frontiers, but they may end up being deeply intertwined. While AI is transforming how we interact with software, quantum computing could reshape the foundation beneath it. Each is powerful on its own; together, they might unlock entirely new modes of problem-solving.

A Shared Foundation: Linear Algebra

At their core, both quantum computing and AI rely on vectors, matrices, and tensors. Neural networks are built on linear algebra — and so is quantum computing. This mathematical overlap suggests a natural synergy: quantum processors could one day perform some of AI’s heaviest lifting far more efficiently than classical systems.

Reducing the Cost of Training

AI models today are compute- and energy-intensive — training large foundation models requires massive clusters of GPUs running for days or weeks. Quantum computing holds the potential to drastically reduce the time and resources needed to train future models, especially those involving high-dimensional optimization.

Quantum-Native AI Models

In the long term, researchers envision entirely new kinds of AI – models that are designed from the ground up to run on quantum processors. These “quantum-native” models might learn and generalize in ways that aren’t possible with classical hardware, opening the door to new forms of intelligence.

A Path Toward AGI?

Some believe that Artificial General Intelligence (AGI) — a system that can reason and learn like a human – may require the kind of parallelism and complexity that only quantum systems can offer. While speculative, the intersection of AI and quantum computing could be essential to achieving breakthroughs in cognition, creativity, or understanding.

The bottom line: AI and quantum are not competing revolutions. They’re parallel ones – and together, they may reshape not only what we build, but how we think.

Why Quantum Demands A Full-stack Approach

In classical computing, software and hardware are often developed independently — your operating system or apps can run across a wide range of processors. But in quantum computing, that separation doesn’t hold. Every layer of the system — hardware, firmware, compilers, algorithms, and error correction – must be tightly integrated. Without harmony across the stack, the system won’t function, let alone scale.

This is why leading companies like Xanadu are taking a full-stack approach – developing everything from the physical hardware to the developer-facing software.

Hardware Layer: Building With Light

Xanadu’s platform is built on photonic quantum computing, using lasers, beam splitters, detectors, and waveguides to create and manipulate qubits encoded in light. Unlike some other quantum approaches, photonics avoids cryogenics for most components, enabling easier networking and room-temperature operation.

Software Layer: PennyLane

To make this hardware usable, Xanadu developed PennyLane, an open-source quantum software framework written in Python. It allows researchers to write quantum algorithms in a high-level language and run them on Xanadu’s chips — or other quantum hardware. PennyLane functions as both a programming interface and operating system for quantum devices.

Control Stack: Classical Systems in the Loop

Even in a quantum computer, classical systems play a crucial role. Real-time control systems – built with GPUs and FPGAs – handle signal processing, run error correction protocols, and stabilize fragile quantum states on the fly. The orchestration between classical and quantum components is one of the hardest engineering challenges in the field.

Quantum systems don’t just require innovation at the hardware level – they demand co-design across the entire stack. The future of quantum computing will be built by those who can integrate physics, math, and software into one coherent machine.

Conclusion: A New Computing Paradigm

From simulating molecules to optimizing supply chains to reimagining AI, quantum has the potential to unlock breakthroughs that classical systems simply can’t reach. While many challenges remain – scalability, error correction, developer tooling – the progress over the past five years has been rapid and real.

As with the early days of classical computing, we’re watching the foundation of an entirely new stack emerge. But this time, it’s not just about silicon – it’s about physics, information theory, and the convergence of disciplines. And just as Microsoft, Intel, and Apple defined the personal computing era, a new class of companies will define the quantum era.

Quantum computing isn’t just a faster computer – it’s a fundamental rethinking of how we solve complex problems

Alumni Ventures and The Deep Tech Frontier

At Alumni Ventures, we believe that paradigm-shifting technologies don’t just create companies – they create entirely new markets. Through our Deep Tech Fund, we invest in visionary founders building at the edge of science and engineering: from quantum to AI, robotics to synthetic biology, and beyond.

We’re proud to back companies like the ones mentioned in this article – startups that are not only pushing quantum computing forward but reimagining what full-stack innovation can look like in this space.

If you’re an investor interested in shaping the next wave of technological progress, we invite you to explore how you can get involved.