Quantum Isn’t Next. It’s Now.

In the early 2000s, it was a common joke in the tech world that “next year is the year of the smartphones.” People kept saying it over and over for almost a decade. It became a punchline. The industry nearly lost its credibility.

Until the iPhone launched. “Next year is the year of the smartphones” finally became true.

The same joke has followed quantum for the past ten years: next year is the year of quantum.

Except it hasn’t been. Not yet.

And yet, quietly, the foundations have been built. We’re not there, but we’re far from where we started.

We’re getting closer. Much closer. I can smell it. I can hear it. I can sense it.

Right now, without getting into too much technical detail, we’re still at a small scale: fewer than 100 usable qubits. Commercial viability likely requires thousands, if not millions. The systems are still too error-prone, and hosting your own quantum machine is wildly impractical. They’re expensive, fragile, and noisy.

At this stage, quantum is mostly limited to niche or small-scale applications. But step by step, quantum is inching closer to broader utility.

And while these things don’t progress in straight lines, the momentum is real and accelerating.

Large-scale, commercially deployable, fault-tolerant quantum computers accessed through the cloud are no longer science fiction. They’re within reach.

I spent a few of my academic years in signal processing and error correction. I’ve also spent a bit of time studying quantum mechanics. I understand the challenges of cloud-based access to quantum systems, and I’ve been following the field for quite a while, mostly as a curious science nerd.

All of that gives me reason to trust my sixth sense. Quantum is increasingly becoming a reality.

Nobody knows exactly when the iPhone moment or the ChatGPT moment of quantum will happen.
But I’m absolutely sure we won’t still be saying “next year is the year of quantum” a decade from now.

It will happen, and it will happen much sooner than you might think.

At Two Small Fish, our thesis is centred around the next frontier of computing and its applications.

This is an exciting time and the ideal time to take a closer look at quantum, because the best opportunities tend to emerge right before the technology takes off.

How can we not get excited about new quantum investment opportunities?

P.S. I’m excited to attend the QUANTUM NOW conference this week in Montreal. Also thrilled to see Mark Carney name quantum as one of Canada’s official G7 priorities. That short statement may end up being a big milestone.

P.P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!

This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.


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4 thoughts on “Quantum Isn’t Next. It’s Now.

  1. Hi Allen,
    Thanks for the insightful blog post—really enjoyed reading it. I’m Abhinav, a PhD student in Computer Science at the University of Toronto. I agree with your assessment that quantum is increasingly becoming a reality.

    In addition to experimental breakthroughs, there has been steady progress in quantum algorithms research over the past decade. For instance in a recent paper of mine, we demonstrated an exponential speedup in simulating a broad class of physical systems using quantum algorithms. You can check it out here: arXiv:2505.17170. I’d love to hear your thoughts!

    Abhinav

    1. Hi Abhinav,

      Thanks for reaching out and for your kind words. I studied quantum mechanics briefly during my electrical engineering degree, so I took a moment to skim through your paper. If I understand correctly, your method involves a linearization approach to approximate nonlinear dynamics, which offers speed improvements but likely introduces some tradeoff in accuracy.

      I’m curious to know. Have you quantified this tradeoff in a specific example? Seeing how the approximation performs in practice would help ground the theoretical benefits.

      Looking forward to hearing more!

      Best,
      Allen

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