
The question in our headline is posed by Barry Sanders, PhD, scientific director of Quantum City, in a recent Nature Electronics , "The Success and Failure of Quantum Computing Start-Ups."
Quantum computing was first proposed over 40 years ago, and by 1994, researchers had developed algorithms showing its potential. In 1999, Canada’s D-Wave Systems became the first quantum computing startup.
Today, numerous quantum startups operate alongside major tech firms like AWS, Google, IBM, and Microsoft. The focuses of these startups include hardware, software, or cloud services, with some achieving billion-dollar "unicorn" status.
Despite recent successes, the future of quantum computing remains uncertain due to challenges in scaling and proving quantum advantage. Sanders notes in the paper, "That scientific outcomes are not predictable is unsurprising, but creating a successful business in an unpredictable area requires an approach that goes beyond the standard."
Key considerations for quantum startups and investors
Success in quantum startups requires more than viable technology - it demands smart strategy. Founders must carefully plan fundraising, balancing cash burn rate and runway. They must also decide whether to stay the course or pivot, though pivoting is often difficult for hardware companies.Quantum tech’s dual-use nature (civilian and military) adds complexity, with potential restrictions on talent and exports. However, it can also attract government investment, providing non-dilutive funding. While valuable, such funding may come with conditions that could divert focus, so founders should evaluate it carefully.
Quantum City initiative at the University of Calgary is dedicated to bridging the gap between quantum research and real-world applications by supporting startups, industry partnerships, and talent development. Through initiatives like the QAI Ventures Accelerator, Quantum City is helping companies in this space navigate the complexities of scaling, securing funding, and achieving market impact and the key challenges identified by Sanders.
The bigger picture: What’s next?
Patience is key. Emerging technologies like quantum computing offer no guarantees - scaling challenges and viable use cases are still unfolding. AI’s history, with its cycles of hype and "AI winters," reminds us that progress isn’t always linear. Quantum computing is likely to follow a similar path.The lesson? Stay informed, stay engaged, and be ready for the long game.
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