Willing to Be Wrong | Rebecca Krauthamer at Quantum

In the first part of my conversation with Rebecca Krauthamer, the co-founder and CEO of Quantum Thought, she discussed the real-world applications of quantum computing she’s helping organizations implement today.

In this second part of our conversation, Rebecca talks about her transition from studying symbolic systems at Stanford to the pioneering field of quantum computing, a sector very few have breached. She also shares her thoughts on how running a successful company means being willing to be wrong.

More information:

Rebecca is the founder and Head of Engineering for QuSecure, a post-quantum cyber security company located in Palo Alto, California. QuSecure works with both government and enterprise clients to protect their digital assets from today’s and tomorrow’s security threats. Their software products can plug directly into an organization’s existing infrastructure, can be deployed in the cloud or on premise, and comply with NIST post quantum standards. 

Rebecca earned her degree in Symbolic Systems from Stanford University, and went on to build cutting edge applications in Machine Learning, Natural Language Processing, and Computer Vision for various companies. After several years working in AI, she began to get frustrated with the growing gap between the potential to build advanced models and the limitations of today’s computing hardware. She turned to quantum computing and hasn’t looked back. She was named to the Forbes 30 Under 30 List in 2020 for her work in quantum computing, and was recently listed as one of the 12 Women in the World Shaping Quantum Computing.

Rebecca serves on the World Economic Forum’s Global Future Council on Quantum Applications. A passionate proponent of ethical AI, she serves on the advisory board of the AI Ethics Journal, and as a subject matter expert for the first Coursera certification for Ethical Technologists. 

DISCLAIMER: Below is an AI generated transcript. There could be a few typos but it should be at least 90% accurate. Watch video or listen to the podcast for the full experience!

Rebecca Krauthamer 0:00
So quantum computing is this, you know, it’s very, very early days. But that’s also extremely exciting because it’s kind of like we’re in the, you know, the 1960s, or 1970s, of the classical computing world where all this innovation was possible.

Alexander Ferguson 0:23
Rebecca, I’m excited to continue our conversation and now hear more about your journey. This is an exciting field to be in. But tell me like, how did you get to where you are right now, leading being founding of this, this new quantum, a concept of a focus on quantum security? What’s your journey been like?

Rebecca Krauthamer 0:43
My background, I didn’t, I didn’t come from a quantum physics background, I came from an AI background. So I started at Stanford, I got the opportunity to study something called symbolic systems, which is sort of it’s an artificial, intelligence, focused, focused field of study. And just got intrigued by the world of AI. Because it’s, I mean, I don’t have to convince anybody that AI is such a huge, a huge thing right now. So, you know, I went into it, I dove in really, after studying, I worked on a bunch of independent projects. So I worked for different companies building things, because I really wanted to, you know, I knew I wanted to sort of lead lead some kind of charge in the AI space. But at first, I thought it was important to really get hands on experience and build things myself, so I could really know what I was talking about. And so I ended up building a lot of really cool things in computer vision, in natural language processing, in machine learning, different predictive pricing tools, all of this cool stuff. And one thing that really struck me as I was building, you know, you go from academia, where you have your very, typically very clean datasets and like sterile problems that you’re solving that have been solved before. And then you go into enterprise, or you go into the the business world, and you’re looking at these problems where things are not exactly, you have to be creative in making them. Them tackle problems, you’re dealing with messy data you’re dealing with not super well defined problem statements. And that, for me, that was fun. But one thing that really stuck out to me in all these projects was, there’s this theoretical, there’s these these theoretical kind of level that we can achieve in AI. All these cool ideas that, you know, in theory, we know how to do, but the limiting factor for a lot of these is computing power. And that’s why we’ve seen GPUs really come into into style over the last several years, because they, they’ve allowed us to parallelize a lot of this and amplify our deep learning capabilities. When quantum computing came on my radar a few years ago, it was kind of this, like, I hit this point of no return, or it’s like, I can’t, I can’t go back to this world where we talk about all these cool things, but they were limited, right, we’re limited by what we can, what we can do on classical computing power. So quantum computing is this, you know, it’s very, very early days. But that’s also extremely exciting, because it’s kind of like we’re in the, you know, the 1960s or 1970s, of the classical computing world where all this innovation was possible. And we have to think about these big problems that are gonna, that are going to emerge, AI big opportunities, and big problems that are gonna emerge just like cybersecurity risks,

Alexander Ferguson 3:47
any thoughts you can share of Okay, now it’s been a year, little over with quantum thought a bit more in place, bringing the team together used to do to co founders had the technical ideas and new bringing the the concept together, be able to move forward and find the clients and bring clarity. What was it like any things you can share as far there as far as fundraising as far as bringing the team together and getting the first couple clients that you can share?

Rebecca Krauthamer 4:12
You know, I came from the world where AI is new, but it’s also not new. As well, you know, computer science is sort of the same. So if you’re there well established ideas and ways of going about solving problems. And you know, even even, even just, when you’re coding, you can actually Google most coding issues that people you’re facing, and someone has faced it before. Quantum Computing, is this like, is this total Wild West of what what is it? What what do we do with it? Well, you know, there’s not that same sort of community and I guess, repository of wisdom that exists around it. So I think, you know, when it when it came to quantum thought and QC care, a lot of the the first several months, were really figuring out, I guess, a lot of education. And we had a lot of hypotheses that you know, about where things would play out and where, where we would sit in terms of the technology, and some were some regard. And we definitely disproved a lot of them. And I think that’s, that’s a really valuable experience for any entrepreneur is being willing to be wrong, right. And pivoting fast.

Alexander Ferguson 5:27
What are your thoughts on being able to move forward from here? How are you going to overcome that challenge? What are you looking to do to keep communications flowing and opportunities coming in? In in the enterprise

Rebecca Krauthamer 5:39
world? Right? Um, yeah, so we hold a lot of webinars. So if you are interested in diving a little bit more deeply into into what we’re doing. We do do a lot of webinars that you can I know, most people are exhausted by zoom at this point. But, uh, yeah, webinars. Um, I think, you know, a lot of our efforts have been really focused around implementation at this point. And really getting those those solid proof points in, I guess, support from from our existing customers. But I think, you know, we were definitely hoping that the world opens up soon. And we can tackle this global challenge.

Alexander Ferguson 6:19
What kind of tech innovations do you predict we’ll see in the near term and the long term, so in the next year, so what’s realistically, what can we see? And then the next five to 10 years, what can we expect?

Rebecca Krauthamer 6:31
Last year, we saw the Google was able to achieve quantum supremacy. And what that meant was that they were able to use a quantum computer to solve a, a really hard math problem in about three minutes, that would have taken the world’s most powerful supercomputers something like 10,000 years to solve. And so there’s this really cool inflection point for quantum computing that shows like, hey, this, this is real, this is legit. And so what I’m expecting to see in the quantum space over the next over the next year, is more of these, these, these instances of quantum advantage where we’re solving problems in just in a way that we can’t solve them on classical computers. And if I digress just for a second, one of my favorite visualizations to kind of make this for those of you new to quantum, to wrap your head around it a little bit is if you imagine so this is kind of the way that I visualize quantum computers, if you imagine that you’re trying to solve a maze. And so you you enter into that maze. And we as people, we you hit your first tee, right, you can go right or left. And we have to choose right, we go right or left. So you go right, you hit another tee, you go left, and it’s this getting through the mazes, iterative process, you know, you explore different paths, you go back and forth, and finally find out. And that’s really the same way that a regular computer works is they you know, they choose they iterate, etc. Quantum computer, if a quantum computer is trying to solve a maze, gets to its first tee. Because of the the craziness of the quantum world, instead of having to choose, you can actually sort of take both at the same time. And it’s not just in parallel, it’s not just like you’re you’re running two parallel processes, you’re literally because of the property of superposition. It’s kind of like you’re splitting, splitting the universes in two and one, you’re taking this path and in another you’re taking this path. And you can continue to do that for all of the paths of the maze and, and simultaneously look at all these different paths. And if you’re clever, in setting up your algorithm, you can actually instantaneously find the most optimal path through that maze. And so that’s the power of quantum computing. And so to get back to your question over the next, you know, year, we’re going to see a lot of these these things being a lot of this being applied to real world situations, whether that’s, you know, everything from from cybersecurity to efficient logistics and routing to algorithmic stock trading, etc. And, and I think over the next five to 10 years, a lot of things will look very, very different. We’re quickly approaching this point where quantum computing is powerful enough to do some really, really, really, really exciting things. And it will disrupt a lot of industries, not just in cybersecurity. 10 years is really, you know, I think, maximum estimate for when computers level two will be able to break the encryptions that we rely on today.

Alexander Ferguson 10:00
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