Interview with Tommaso Demarie, CEO of Entropica Labs

Simulating Nature to Understand it: The Grand Challenge of Quantum Computing.

Tommaso Demarie was born in the capital of the world’s first and original “Silicon Valley” (which was not in California but in Canavese, in Ivrea) and is the co-founder and CEO of Entropica Labs: his story begins with the study of ocean waves in Turin, transits to Sidney, where he obtains a PhD in Physics at Macquarie University, and lands in Singapore, where in 2018 he gave birth to this fascinating reality with Olivettian echoes. Quantum physics has taken him, literally, to every corner of the world, and so he is our ideal Virgil capable of accompanying us inside a complex world bordering on the mystical, in which ultra-technology takes its extreme step: transforming itself (or returning to being?) into nature.

There is a lot of talk about quantum computing. What is your view on this?

“The first thought that comes to mind is one of association, and it concerns computing in general: with the advance of artificial intelligence, the world has an increasing need for computational power. Big companies like Microsoft, Google, and Facebook are building ever-larger data centers, to the point where they have to power them with nuclear power plants. Today, computing power is no longer a luxury, but a necessity, like electricity. We are entering an era in which we cannot afford to live without nearly infinite computational capacity, because this will be the key to developing advanced intelligence and cutting-edge technologies. Here then,” he continued, “quantum computing comes into play precisely to overcome the physical and quantitative limits of traditional data centers. Simulating nature is one of the fundamental capabilities of human beings. Every day we build scenarios about what has happened, what is happening and what will happen. But our brains have limits. That’s why we’ve created machines that help us overcome these barriers.”

But these machines, just like humans, have limitations.

“Exactly. Today with computers we can work on fluid dynamics, chemistry, materials and artificial intelligence, but even these tools have a limitation: the quantum world. To simulate nature in its entirety, we have to go further, to be able to simulate quantum processes, which classical machines cannot do efficiently.”

Are we then facing the advent of a new era for humanity?

“These are definitions we leave to future historians. What is certain is that human history is a history of continuous evolution driven by human intellectual capacity. The advent of classical computers has served, and still serves, the function of aiding and amplifying the capabilities of human beings, but now we are faced with a new need: to simulate natural processes beyond the current limits. And this is something that is only possible with quantum computers: in short, those who control computational power control the future, and it is precisely through quantum computing that we will be able to make accessible a new era of scientific discovery in the service of humanity.

The trajectory you have drawn is very sharp and already discernible, yet operationalizing these projects is neither simple nor quick: what does it take in your opinion to make sure that the world is prepared for the advent of quantum computing, a phenomenon that only a few years ago was absolutely niche?

“Making it suitable for all kinds of computing. In the last few years,” Tommaso explains, “we have reached a turning point in industry and technology: until 2016, quantum computing was a purely academic field, but from 2016 – the date IBM put the first commercially available quantum computer online – to date, instead, we have experienced an experimental phase in which companies, universities, and research institutions have begun to build the foundations for a truly functioning quantum computer. I am referring to the so-called “fault-tolerant” quantum computer, which between last year and this year finally entered an implementation phase. One way to demonstrate this transition is to observe the evolution of computing power over time. For classical computing, reference is made to Moore’s law, which states that the number of transistors in microchips doubles every 18 months, increasing computational capacity. In quantum computing, a proxy for Moore’s law may be the number of quantum bits in processors, which has continued to double every 1 to 2 years over the past decade. Today, the most advanced prototypes of quantum computers are so complex that if we tried to simulate them with the best available classical computers, we would fail.”

“We are therefore,” Tommaso continues, “experiencing a turning point: more and more companies are developing quantum computers and the technology is proving its worth. In addition, governments and large companies such as IBM, AWS, Microsoft and NVIDIA are investing heavily, a sign that the market recognizes the value of quantum computing. Sectors such as finance and pharmaceuticals are also showing interest, aware of the impact this technology will have on their processes.”

Moore’s law is often cited when talking about classical and analog computing. Today we are seeing more and more use cases addressed with both artificial intelligence models and quantum computing. How do you see the evolution of these two areas?

“These are two different domains,” Tommaso explains, “Artificial intelligence is an application of classical computing, so we need to distinguish between the use of the resource and the resource itself. If we wanted to make a correct comparison, we should compare classical AI with quantum AI, but the latter exists today only in its conceptual state. Today, classical AI is powerful because of the great availability of computational power, but it makes no sense to compare it directly with quantum computing. It would be like comparing coal with uranium: both are resources, but nuclear power is much more efficient than coal power.”

In the AI world, there is also a strand of analog computing, which takes advantage of a different platform than digital. Do you think analog can represent an outgrowth of digital?

“It is possible,” Tommaso continues, “but it is unlikely to replace the entire digital infrastructure. We will probably see the use of analog chips for specific applications, such as machine learning, to make processes more efficient. However, they do not represent a fundamental leap, because with a classical analog chip it is not possible to simulate quantum processes anyway.”

“If the goal,” Tommaso points out, “is to improve performance and reduce costs, it is possible for analog to have an impact. But if we want to address problems beyond the capabilities of classical computing, we need quantum computing. One way to explain it is this: we can build faster and faster airplanes, but they will never take us to the Moon or Mars. To make that jump we need space rockets, which is something fundamentally different. Quantum computing is exactly that kind of leap.”

We retrace the steps that led you to found Entropica Labs.

“Of course. I am originally from Ivrea,” Tommaso says, “and I studied physics in Turin, completing the university course with a master’s degree. After a year at Banca Sella, I moved to Australia for a PhD in quantum information in Sydney. While there, I visited Singapore, where I discovered the CQT (Centre for Quantum Technologies) a center dedicated to quantum technologies and decided to move to the city-state to continue my academic journey. In 2016, I noticed the transition of quantum computing from being an academic field to a more experimental phase. I was lucky enough to work with people who shared my vision, and this prompted me to take the plunge into the world of entrepreneurship. I left university and, together with a friend, Ewan Munro (a PhD student at CQT), founded the startup in 2018 through the Entrepreneur First incubator. Entropica Labs focuses on developing advanced software for a crucial aspect of the future of quantum computing: quantum error correction, making quantum computing reliable, efficient and ready for practical applications.”

What are the latest developments in your company?

“We recently completed the first version of our software, called Loom. It is a platform that simplifies quantum error correction, turning applications into hardware-ready solutions that are tolerant of the imperfections that are inherent in quantum processes. Although it is still in an early stage, it can already perform essential functions.
But what excites us most is the potential that Loom is beginning to unlock. It is a first concrete step toward what we call the ‘new logical infrastructure’ of quantum computation. Our goal is ambitious: we want to make the power of quantum accessible, reliable, and integrable into the workflows of the world’s most strategic industries. There is still a lot of work to be done, but we are proud to be able to contribute to the emergence of this revolutionary technology.”