Alexa von Tobel is fully aware that her big bet on quantum computing may never pay off. “The risk of being too early is a real risk,” she says. She’s speaking to me via Zoom from the New York City office of Inspired Capital, the early-stage venture capital firm she runs with former US commerce secretary Penny Pritzker.
In addition to personally investing in blue-chip brands like Uber and Airtable, von Tobel has backed a number of AI startups through Inspired Capital, including BrightAI (a platform that monitors critical infrastructure) and PreemptiveAI (a startup building a foundation model to map human physiology and predict health outcomes). In total, the firm manages nearly $1 billion in assets.
In 2023, the Harvard-dropout-turned-founder-turned-VC and podcast host started studying quantum computing. In an interview with WIRED, she makes the case that this field will unlock the scientific discoveries more often associated with artificial general intelligence. Inspired Capital recently invested in a quantum startup called Logiqal, which is seeking to build the world’s first scaled quantum computer.
I suspect you knew about quantum computing for years before you decided to invest. What changed?
A few months before ChatGPT came out, Penny Pritzker and I went on a listening tour around AI where we connected with dozens of experts in the category. I came up for air after that and said, “What’s the next innovation horizon after AI?” Because we’re in AI. Everything is AI, there’s nothing that we’re touching that isn’t AI anymore. It became clear to me—and I could always be wrong—that one of the next innovation curves very clearly could be quantum. AI’s compute demands are going to reshape infrastructure, which means quantum has a greater likelihood of success.
If you talk to some of the best experts in the field, they would tell you there’s only hundreds of quantum experts in the world. So it’s kind of an amazing category to go learn about because actually you can’t pretend to be a quantum expert. Quantum experts are PhDs with decades of work. So you can really put your hands around the talent in a way where you can really learn from them.
Today, we see a potential path toward building one of the first quantum computers. 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.
Where did you ultimately decide to invest?
So I really focused on hardware, meaning we have to first build the first quantum computer before we can do anything else.
In many ways, we think of quantum unfolding in phases, and today it’s really a hardware play. We need to get to a point where we can build successfully tens of thousands of qubits that fire and work successfully. So [then the question was] who is the most talented person that I could find in the hardware category? And it became very clear to me, it’s this professor named Jeffrey Thompson at Princeton. And he was working on a breakthrough approach called erasure conversion in building one of the first quantum computer companies focused on the neutral atom using ytterbium.
Depending on how you think about it, there’s half a dozen or more approaches to the hardware. And I became excited that within the hardware approach, the neutral atom approach was high potential. So we backed [Thompson’s] company called Logiqal.
What happens if you’re right?
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.
It’s a real earth-moving innovation if there’s a chance that quantum computers find the path toward success. 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.
The way you talk about quantum computing sounds a lot like how many AI enthusiasts talk about artificial general intelligence.
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.
You mentioned that it’s hard to fake being a quantum expert. I would posit that it is not as hard to fake being an AI expert. How do you decide who to back?
There are so many companies that are being built and born in AI that when you extrapolate them 5, 10 years will not have a true genuine moat outside of brand or speed. Brand and speed are rarely strong enough moats to build a generational company.
I’ll give you an example. BrightAI creates stickers that are roughly this big [she makes a circle with her fist]. The company puts a sticker on every telephone pole, on every HVAC system, on every water line system, and then observes it for long periods of time, 5, 10, 15, 20 years [and flags potential issues]. That’s a pretty good moat. You’re not ripping all those stickers off.
For the most part, the value in AI accrues to the incumbents. Penny, my cofounder, is on the board of Microsoft. If you think about it, Microsoft and Google—Google has 3 billion users. Microsoft has a billion users. They can launch a product that is OK, not excellent, and they still have a pricing power, a distribution power. And so we very much think about the world where when the elephants dance. Don’t be an ant.
How do you use AI?
For everything. There’s nothing you don’t use AI for, nothing. From every question, I mean, today I probably used it 25 times.
It’s replaced Google for you?
Everything. Everything. Deep research, sourcing. Today I was looking up what jobs are declining fastest in the world. Truly, I would say it’s not a dozen times a day. It’s dozens of times a day.
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