QCentroid: Shaping the Future of Using Quantum Algorithms
Quantum computing is moving out of university labs into the real world. Both startups and corporations are pushing the envelope to build large-scale, useful quantum computers. Yet, it takes smart quantum developers to come up with algorithms geared toward tackling specific computational problems using these newly emerging quantum hardware platforms.
Founded by Carlos Kuchkovsky, Sergio Gago, and Antonio Peris, QCentroid develops a quantum-as-a-service platform to connect the best quantum startups and companies to the best quantum hardware providers. Industry customers will be able to submit their tough computational problems, quantum developers can submit quantum algorithms for solving those, and QCentroid’s platform will benchmark the solutions.
It will open up the creator economy to mathematicians and physicists. Through API and smart contract integrations, traditional applications, blockchain, and decentralized protocols will be able to embed the best quantum algorithms in decentralized applications, making quantum computing widely available.
Learn more about the future of using quantum algorithms from our interview with the CEO, Carlos Kuchkovsky:
Why Did You Start QCentroid?
In my previous corporate life, I was part of a team experimenting with blockchain and quantum computing technology for finance applications. I got really excited about the results and the possible impact of these technologies on our future. I didn’t want to watch this happen from the sidelines, but instead, I wanted to lead the industry to what I think could be one of the biggest business opportunities in the next 20 years.
As a citizen, I love combining technology with impact. While quantum computing will be our best tool for solving important computational problems, using blockchain and Web3 will help us design better products for society, with smart contracts and DAOs providing the interface to access quantum computing.
How Does Your Quantum Algorithm Platform Work?
Our long-term vision is for businesses to solve problems through our platform without even knowing they are using quantum computing, regardless of whether it’s designing logistic systems or developing a new catalyst for carbon capture. We provide a catalog of algorithms running in the background, helping technical and non-technical teams benchmark their results and execution times. And we provide an interface to run these algorithms on different quantum hardware platforms and embed quantum algorithms in an organization’s workflows. Therefore, we’re enabling startups to work with tier-1 quantum hardware providers.
Quantum computing is moving out of research labs into the real world, getting enterprise-ready within the next few years. There are two important concepts: One is obtaining a quantum advantage, solving a computational problem faster or better than any classical computer could. We might achieve this within the next decade.
The other concept is obtaining a quantum business advantage: gaining business value from using a quantum computer and making this value accessible to more companies. Not every company has access to its own high-performance computing center.
Many applications, especially in finance, don’t require exact solutions but need approximate solutions that even today’s noisy quantum computers could deliver. This is, in particular, relevant to machine learning applications, which, combined with quantum computing, open up the field of quantum machine learning:
a) Quantum-enhanced machine learning, where, e.g., quantum annealing is used to determine which features and variables are most relevant to training a machine learning model, and thus make training faster and more efficient.
b) Pure quantum machine learning, which started around three years ago and implements neural networks using qubits—it’s progressing fast and will eventually kick off just like generative AI did just now.
c) Using machine learning for quantum control and reducing noise levels.
Our unique value proposition involves aggregating different quantum hardware providers, matching business customers with the best quantum algorithms and quantum hardware to run these algorithms and solve their business problems.
We’re looking forward to the Arduino moment for quantum computing! This includes not only general-purpose, universal quantum computers, which may still be far into the future, but also specialized ones, so-called quantum annealers, geared towards solving particular problems. It’s like GPUs being able to perform only certain kinds of operations, but they are much faster and more efficient than CPUs.
It’s a bit like using neural networks and backpropagation for prediction tasks: There is no exact mathematical proof telling you which network architecture you need to pick to solve a particular prediction task. But neural networks turned out to be immensely useful and generated a lot of business value—that’s why they’re now deployed everywhere. The same we think is true for quantum annealers.
Unlike universal quantum computers, there is no mathematical proof that they can solve computational problems faster and more efficiently. But a lot of practical experience shows that they can—for particular problems, especially around optimization and quantum chemistry. Even finding a 1% better solution can lead to massive business value in huge industries like logistics or the chemical industry.
How Did You Evaluate Your Startup Idea?
We started in stealth mode ten months ago. Through partnerships and demos, we tried to figure out which pain points we could address first, which companies could benefit the most from quantum computing, and where quantum business advantage could be achieved. It’s about being part of the community, partnering with good teams, quantum hardware, and quantum algorithm providers. We help both to connect with industry customers, especially tier-1 companies in the finance, logistics, mobility, or sustainability space.
What Advice Would You Give Fellow Deep Tech Founders?
First, focus on developing a solution for a very specific persona. Do your research on the industry, who you are talking to, what the user and buyer are, and why they’re willing to pay. And make sure you’re really solving their problem!
Also, figure out which investors to talk to and create a feedback loop to pick the right investor for your startup as fast as possible. Otherwise, you could lose a lot of time talking to the wrong people.