Insider Brief
- Venture capitalist Alexa von Tobel is betting on quantum computing through her firm Inspired Capital, despite acknowledging the technology may take decades to mature and carries a high risk of failure.
- Inspired Capital, which manages nearly $1 billion, has invested in Princeton professor Jeffrey Thompson’s startup Logiqal, focused on building scalable quantum hardware using neutral atoms and error-correction methods.
- Von Tobel told Wired she sees parallels between quantum computing today and AI in 2015, arguing that if the technology succeeds, it could drive transformative advances in pharmaceuticals, materials science, logistics, and finance.
- Image: Photo by geralt on Pixabay
A visionary venture capitalist has staked her venture firm’s capital on quantum computing, aware the technology may take decades to mature — and may never deliver returns.
In an interview with Wired, Alexa von Tobel, the founder of Inspired Capital, said she sees parallels between the state of quantum computing today and artificial intelligence (AI) a decade ago.
“In many ways, quantum is today where AI was back in 2015, which is a lot of really big research and science projects and starting to have practical applications rather than just pure research,” Tobel told Wired.
Just as AI was once dismissed as an academic pursuit before scaling into mainstream business, she believes quantum could follow a similar curve. The risk, she acknowledged, is arriving too early –investing before the technology and markets are ready.
Inspired Capital manages nearly $1 billion in assets and has built a portfolio that leans heavily into artificial intelligence, according to tech magazine. The firm has funded BrightAI, a company that uses sensors to track infrastructure such as water lines and HVAC systems, and PreemptiveAI, which is developing models to anticipate health outcomes. Von Tobel herself has invested in consumer companies like Uber and Airtable.
Quantum, she told Wired, represents a different kind of bet, an unproven technology with few experts and many unanswered questions. Unlike AI, which has seen rapid commercialization, quantum remains largely confined to research labs. Yet she views this as precisely the moment for venture investment: before the field consolidates, and when the upside could be most significant if technical barriers fall.
Hardware First
Her conviction rests on hardware. Quantum machines store and process information in qubits, which are fragile and difficult to scale. Most prototypes today run with only dozens or a few hundred qubits. By comparison, von Tobel said even 10,000 to 100,000 qubits could start producing societal value in areas such as materials science and drug discovery, though the “ideal” system would require far more.
Von Tobel said the industry is moving toward that target, according to Wired.
“Today, we see a potential path toward building one of the first quantum computers,” von Tobel said, as reported by Wired. “And I say quantum computers with an asterisk, because a quantum computer, even a quantum computer with 10,000 qubits, 50,000 qubits, 100,000 qubits, would begin to create a significant amount of value for society, but it wouldn’t hit the bar of a perfect quantum computer, which is ideally hundreds of thousands of qubits.”
Inspired Capital recently backed Logiqal, a startup founded by Princeton professor Jeffrey Thompson. The company is pursuing a “neutral atom” approach, which arranges individual atoms and uses lasers to control them. Logiqal also leverages a method known as erasure conversion, which promises to correct errors in quantum systems more efficiently. Von Tobel said she gravitated toward this path because of its technical promise and the caliber of its founding team.
“Depending on how you think about it, there’s half a dozen or more approaches to the hardware,” said von Tobel. “And I became excited that within the hardware approach, the neutral atom approach was high potential. So we backed [Thompson’s] company called Logiqal.”
Part of the appeal of investing in quantum, she argued in the Wired interview, is that the field is not crowded. There are only a few hundred true experts globally, she said, most of them PhDs with decades of specialized training. That scarcity makes it easier to identify genuine talent and harder for opportunistic founders to stake unearned claims, a contrast with the explosion of AI startups.
Still, this scarcity cuts both ways. With so few specialists, the pace of progress could be slow, and the costs of scaling prototypes into commercial machines are high. She suggested that large incumbents such as IBM, Google and Microsoft already dominate early development, backed by national governments and research consortia. For startups, competing in that environment requires both technical edge and patient capital.
The Convexity of Venture
Von Tobel told Wired her investment thesis relies on convexity — the idea that most bets fail, but the ones that succeed can return hundreds of times the original investment. Quantum fits this pattern, according to von Tobel. If successful, it could inspire massive innovation, reshaping industries from logistics to finance.
“I’m a venture investor, and we believe in convexity — taking risks on things that most likely won’t work, but if they do work could be 500x in value,” von Tobel told Wired.
These benefits of quantum computing remain in the speculative realm, but they illustrate the scale of returns that keep venture investors willing to tolerate the high risk of failure.
Lessons From AI
Her comparison with AI is deliberate. In her view, quantum today resembles the pre-ChatGPT era of AI: a domain of research projects beginning to yield practical results. Back then, machine learning models were confined to labs, only beginning to influence products such as voice recognition and image search. A few years later, AI became the backbone of consumer apps, enterprise software, and now generative models like ChatGPT.
Von Tobel argued that AI’s rise shows how quickly an experimental field can commercialize once core breakthroughs align with compute power and distribution. She also noted that incumbents such as Microsoft and Google captured much of AI’s value, thanks to their user bases and pricing power. For startups, she suggested, competing in AI requires either strong technical moats or long-term embedded infrastructure.
In that sense, her bet on Logiqal mirrors her broader investment philosophy: look for deep infrastructure plays with staying power. She cited BrightAI’s long-term sensor deployments as an example of a moat—once embedded on utility poles or water systems, the devices are unlikely to be removed. Quantum hardware, if it works, could become another kind of infrastructure, powering applications across industries but owned by a handful of foundational players.
AI as a Tool
Although she is increasingly focused on quantum, von Tobel recognizes how important AI has become in her own work. She told Wired she uses AI dozens of times a day, for research, sourcing and market analysis, to the point of replacing Google search for many tasks. To her, AI is a tool that accelerates the present, while quantum represents a bet on the future.
The timing may be uncertain, and quantum science may still be in the experimental stage, but von Tobel said that is the nature of venture investing. Most experiments will not pan out. But if even one company solves the scaling challenge, she argued, it could create not just a successful business but a new era of computation.
That new era of computation could unlock real “earth-moving” benefits that stretch the imagination, according to the venture capitalist.
“It’s a real earth-moving innovation if there’s a chance that quantum computers find the path toward success,” von Tobel said. “You unlock these thinking engines, these computational engines that can run the future of material sciences, the future of pharmaceutical innovation, the future of logistics, the future of financial markets in ways that we’ve never seen before You can see a future where you could create pharmaceutical advancements that could elongate life 20 to 30 years. You could see changes in material sciences where we could invent new products. It could help us get to Mars! That is what quantum computing unlocks.”
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