QCentroid – Shaping the Future of Using Quantum Algorithms

QCentroid – Shaping the Future of Using Quantum Algorithms

Quantum computing is moving out of university labs into the real world. Both startups and corporates are pushing the envelope on building 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 will be able to 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. And by using traditional applications, blockchain and decentralized protocols through API and smart contract integrations, it will be possible 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 past corporate life, I was part of a team experimenting with technology in blockchain and quantum computing for finance applications. And 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 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 accessing quantum computing. 

How does it work?

Our long-term vision is that businesses can solve problems through our platform without even knowing that 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 that run in the background, helping both technical and non-technical teams to 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. Thereby, we’re enabling especially 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. 

But the other concept is obtaining a quantum business advantage: Getting business value out of 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 is implementing 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 is aggregating different quantum hardware providers: Matching business customers with the best quantum algorithms and quantum hardware to run these algorithms to 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 at it. 

And 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 actually can – for particular problems, especially around optimization and quantum chemistry. And 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. 

Advice for fellow deep tech founders: At first, focus on developing a solution first for a very specific persona. Do your research on the industry, who you are talking to, what’s the user, the buyer, 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. 

Who should contact you? 

Whether you have a question about our platform or want to join our mission to open the creator community to quantum scientists – feel free to contact us through our website.

Further Reading

Connecting Quantum computing to Web3. A tech approach. – Blog post by QCentroid about how their QCentroid Quantum Solutions Platform connects to the Ethereum blockchain. 

DeSci Rising Ep. 15 – QCentroid – Recording of a Twitter Space conversation with Carlos Kuchkovsky on decentralized science and opening the creator economy to mathematicians and physicists.