Hello World! Let's talk quantum computing business cases.

Hello (quantum) world, let's talk about being useful.

One of the challenges I had when I joined Quantum Brilliance as the first product manager was something that anyone on the business side of the industry will relate to. And that was being able to answer "what could a quantum computer be useful for?".

It sounds so simple, doesn't it? The very reason that commercial risk capital is invested into quantum computing is the chance of a commercially viable outcome. We should be able to answer this question with confidence and in step with the progress being made from the R&D side of the industry.

In reality we can't. And we don't.

Thinking about quantum utility

Have you ever seen that Bell Curve meme? I can picture our version of it, with a title of "what is a quantum computer good for?", and either extreme simply saying "I don't know".

Whats in the middle? A whole lot of increasingly AI-written chatter about the power of quantum computing to revolutionise this or that. By the time this narrative filters through scientific papers, texts, technology media coverage and hits the social consciousness (via social media), it's all just a bit... too much.

Like most AI slop on the topic of Deep Tech in practical terms, these definitions and descriptions are directionally correct, but are substantively empty. And we don't really, truly, know if the various systems we are developing, across the various modalities and via various methods, are practically useful when it comes to the actual performance of our chosen algorithms in the intended problem spaces.

The work of finding this out is hard and rewarding and engaging and what many of us do week to week. And I can only speak for myself here, but it's not always easy to keep up with what's happening and changing across the various quantum fronts. The reason for that is often a result of the actual work veering towards a hyper-specialised exploration, even for those of us pulled in via relatively generalist roles. Diving deep and then coming up for air sounds poetic, but can be an exhausting context switch for various roles straddling both the business and technology of quantum computing.

And spare a thought for the newcomers, be they business decision makers or domain experts, looking to understand where things are at right now, without having to sit through the same stories about cats, slits, or spooky this-or-that. "What can a QPU do for me", is a valid question. We need to be able to better answer that in ways that shorten the distance between question and contextual answer.

Working the problem

So let's experiment with that idea. There ARE some great business intelligence services catering to quantum computing, such as data platform from The Quantum Insider and Resonance, research groups like Futurum and Hyperion Research, and individuals like Dr Bob Sutor.

I like these and the people working on them a great deal. But coming from a major open source company, and being influenced directly by my time with the founding CEO, I keep thinking that the kind of information I wish I had access to when I joined Quantum Brilliance wasn't nuanced business analysis, collated and synthesised by domain experts.

All I really wanted was a general overview of the market at the moment, what led to this point in time, and how everything related. I just needed the "wikipedia level" of quantum business landscape. And if that resource could THEN help point to the experts in various areas of interest, then this wouldn't be a hurdle to the other specialised industry observers, but a resource. To educate the wider market more easily doesn't detract from the analysts with deep insights. It brings more people with more specific questions (and ideally budgets) to work on more specific things.

Turning theory into action

So that's the theory. Now what might that look like? I'm not sure, but I'm going to experiment with this problem space, and see what we come up with. I don't just want to make "yet another directory". Nor step on the toes of the experts on the analyst side of things. But I do know this is a real problem I've felt, my various teams have felt, and has enough commonality in the community around me that it's worth exploring. Ideally as an open source project. Let's see how we go.