Qilimanjaro CEO Marta Estarellas talks about the current boom of QC and its future.

The global quantum computing (QC) sector is experiencing an unprecedented surge in capital and commercial attention, transforming what was once a domain of purely theoretical physics into a fierce geopolitical and financial race. This quantum gold rush, however, is defined by a deep and startling paradox: multi-billion-dollar valuations for public firms that run counter to minimal current revenue.

For companies like Barcelona’s Qilimanjaro Quantum Tech, the investment fervor represents a high-stakes transition from pure research to engineered commercial utility, driven largely by the exploding demands of artificial intelligence (AI). 

During an exclusive interview with EETimes, Marta Estarellas, CEO of Qilinamjaro, observed that this period of intense investment is palpable: “Our quantum industry is experiencing an inflection point, catalyzing new businesses, attracting substantial investment, and a global sector is emerging.”

The Boom echoes AI’s fever

The current excitement surrounding quantum computing shows “striking similarities” to the volatile hype cycles that defined AI’s long journey to commercial viability. QC is often compared to “artificial intelligence in 2010, when neural networks were on the cusp of becoming useful.”

This speculative fervor has inflated the valuations of “pure-play” quantum firms that went public via Special Purpose Acquisition Company (SPACs), such as IonQ ($19.9 billion market cap against $52.37 million LTM revenue) and D-Wave Quantum ($10.9 billion market cap against $22.28 million LTM revenue). These companies are sustaining “massive net losses” while prioritizing heavy research and development (R&D), indicative of a market betting entirely on a future paradigm shift.

Estarellas attributes this heightened appetite to a growing market maturity: “The demand for quantum technologies is intensifying and industries prepare for the next wave of computational breakthroughs.” She believes this is fueled by a better understanding of the necessary implications of these systems, coinciding with a computational crisis created by large-scale AI.

Quantum fix for the AI energy grid

The intersection of quantum computing and AI is proving to be the primary catalyst for the current investment surge. The massive computational demands of training complex AI models are straining global infrastructure.

Estarellas notes that “the acceleration of artificial intelligence, spanning practical use cases, real-world applications, and emerging needs, is unprecedented.” This AI expansion leads to a rapid increase in data processing needs that require real physical infrastructure—data centers and supercomputing centers. The prediction is that data processing needs will increase exponentially, requiring a doubling of infrastructure capacity by 2030, a feat complicated by immense cost and a severe energy gap.

Quantum computing is seen as a necessary technology to curb this unsustainable growth. As Estarellas explains, “Quantum computing’s ability to process data in an exponentially larger space compared to classical computers offers a more sustainable solution to the resource limitations of current data centers.” By increasing computational capabilities exponentially, QC simultaneously reduces resource needs.

Estarellas further suggests that the industry recognizes the financial and technological ceiling of current systems, stating pointedly that “The quantum chip is going to be the next Nvidia.” Investors are recognizing that when Nvidia’s growth potential plateaus, quantum computation is the likely successor for the next wave of exponential growth.

Startup imperative for efficiency and rigor

For startups like Qilimanjaro, which is involved in developing both analog and digital quantum computers for integration into the Barcelona Supercomputing Center’s MareNostrum 5, navigating this boom requires rigor and a focus on utility.

Estarellas, drawing on her scientific background, notes that understanding the physics and mathematics behind AI models is critical for optimization. She emphasizes that AI’s learning process is “a topic that is still poorly understood, as we don’t fully understand why a neural network learns.” If the underlying theory is comprehended, companies can begin to optimize models, making them more efficient.

Qilimanjaro is actively proving the practical utility of this convergence, even at the research level. Estarellas confirms: “We started by testing very simple image-classification algorithms and soon discovered, using theoretical approaches, that genuine learning was possible – quantum machines can learn and they do so with less resources.”

Beyond AI, the core utility of QC for enterprises, especially in the financial sector which is heavily invested in the technology, lies in optimization problems. The financial sector, which manages massive data sets, has complex optimization problems that grow exponentially in complexity. Estarellas points out that large logistical challenges, such as those faced by supply chains, “can be mapped to binary constraint optimization that can be mapped into quantum algorithms.” While quantum computers may not offer superior speed immediately, they offer competitive advantages in “resource efficiency and cost reduction.”

However, translating this potential into reality is complex, requiring seamless integration. Estarellas stresses the technical hurdle: “It’s not easy… We need to build software orchestrators that distribute task workflows between the different computing modalities. It’s a challenging task but a necessary one to bring the future of data centers and supercomputers.”

Geopolitical backstop to the ‘Quantum Winter’

Historically, technological booms have often been followed by periods of disillusionment or “winters” when grand promises fail to materialize. Estarellas admits this was her expectation: “My vision was that this was going to inflate… I worried that the field would inflate faster than the pace at which science actually progresses, leading to expectations and promises that could not be met within those timelines.” A disappointment, she feared, would lead to a lack of confidence, causing startups to disappear.

However, her prediction of an imminent crash has been wrong: “I expected a correction by now, and instead we are seeing the exact opposite. And I’m glad I was mistaken.”

The current QC boom is fueled by crucial factors such as constant scientific breakthroughs and geopolitical imperative. The threat that a quantum computer could “crack much of the encryption used by today’s most advanced communications systems” transforms QC development from a commercial race into a national security priority.

Europe’s public support

Estarellas highlights that government support reinforces investor confidence, noting: “Having the support of Governments and the European Commission sends a very strong signal to the market: we are developing a highly  strategic technology.”

While the ultimate goal of “quantum advantage“—where QC outperforms classical machines in all tasks—remains contingent on solving profound physical challenges such as quantum errors, the sustained state-level interest suggests that, even if commercial interest wavers, “a full-scale ‘quantum winter’ akin to the decades of abandonment suffered by AI may be averted.” The field is moving forward, propelled by both economic ambition and profound strategic necessity.

From TTimes