Quantum-as-a-Service: Accessible Quantum Computing for Business

KARIOS Ai V26 SINGULARITY The Virtual Simulated Quantum Processor (VSQP) Unlocking Quantum Power on Classical Hardware The Virtual Simulated Quantum Processor (VSQP) represents a breakthrough in computational processing, designed to bridge the gap between classical and quantum computing. This technology enables standard x86 computer hardware to execute quantum code within a sophisticated, emulated quantum environment. The result is a significant boost in processing power, effectively transforming ubiquitous and cost-effective computing systems into quantum-capable machines. This innovation arrives at a pivotal moment, as the quantum technology market is projected to reach nearly $100 billion by 2035, with quantum computing capturing the largest share of this growth [1]. At its core, the VSQP is an intelligence-driven system that dynamically translates standard computer code into quantum code. This quantum code is then processed in a state of superposition—a fundamental principle of quantum mechanics that allows a quantum bit, or qubit, to exist in multiple states at once. This parallel processing capability is the source of the exponential speed-up promised by quantum computing. Once the computation is complete, the VSQP seamlessly converts the results back into standard code for use by the host system. This entire process, termed Quantum Accelerated Processing, delivers a powerful new layer of performance to existing hardware, unlocking solutions to problems previously considered intractable for classical computers. The Quantum Advantage in a Digital World The strategic advantage of the VSQP lies in its ability to deliver what is known as "quantum advantage"—the capacity to solve complex problems faster, more efficiently, or more accurately than any classical computer—without requiring the specialized, expensive, and physically delicate hardware of a true quantum computer. This has profound implications for a wide range of industries, including finance, pharmaceuticals, materials science, and artificial intelligence. By democratizing access to quantum-level processing, the VSQP can accelerate innovation in areas such as: •Financial Modeling: Complex risk analysis and portfolio optimization. •Drug Discovery: Simulating molecular interactions to design new therapies. •Artificial Intelligence: Training more complex and powerful machine learning models. As global investment in quantum technology surges, with governments and private entities committing billions to its development [1], the VSQP is positioned to capture a significant share of this expanding market by offering a practical and scalable solution for immediate quantum acceleration. References [1] McKinsey & Company. (2025, June 23). The Year of Quantum: From concept to reality in 2025.

THE QUANTUM LEAP What could we achieve if computers could think beyond today’s limits? In 2019, a small team at Google’s Quantum AI division did something extraordinary: they achieved “Quantum Supremacy.” Simply put, a quantum computer solved in minutes a problem that would have taken the world’s fastest supercomputer thousands of years. Sounds like science fiction, right? But it was real. This moment signaled the start of a new era. Classical computers have long followed Moore’s Law, with chips getting faster and transistors smaller. Quantum computing shattered that ceiling, unlocking possibilities that once seemed unimaginable. Other tech giants are racing forward too. Amazon is building quantum tools for startups through AWS Braket. Microsoft’s Azure Quantum integrates quantum computing into the cloud, letting businesses tackle problems classical computers can’t handle. IBM has opened its quantum machines to researchers and students worldwide. This isn’t just experimentation—it’s strategic positioning for a future where classical computing may no longer suffice. Why should this matter to you or me? Because quantum computing changes what we can do. In healthcare, it could simulate complex molecules to speed up drug discovery, turning years of work into weeks and making life-saving treatments accessible faster than ever. In finance, it could analyze markets, detect fraud, and optimize investments at lightning speed. In logistics, companies like Volkswagen are already using quantum algorithms to optimize taxi routes, cutting travel times and emissions. And for AI and machine learning, the possibilities are thrilling. Quantum computers can process enormous datasets far beyond classical limits, helping models learn faster, discover hidden insights, and tackle problems once thought impossible—predicting pandemics, optimizing energy grids, or solving climate challenges. Of course, quantum computing is still fragile. Machines operate near absolute zero, and even a small disturbance can cause errors. But the momentum is undeniable. Google’s 2019 milestone wasn’t just a tech feat—it was a wake-up call. It reminded us to rethink how we compute, innovate, and prepare for challenges that demand thinking beyond today. The best part? This revolution isn’t only for billion-dollar labs. With cloud-based quantum platforms, students, startups, and researchers anywhere—including right here in Uganda—can experiment and innovate. The next breakthrough could come from anyone brave enough to think beyond limits. Quantum computing isn’t just a leap in technology; it’s an invitation to dream bigger, design smarter, and redefine what’s possible. The question isn’t if it will change the world—it’s whether we’re ready to change with it. How far are you willing to go beyond the limits of today?

Quantum computing isn’t science fiction anymore. It’s closer than most leaders realize—yet Corporate America is nowhere near ready. Breakthroughs from Microsoft, Google, and IBM are speeding things up. Talent gap: 250k quantum jobs by 2030, but the pipeline is thin. Early movers (Moderna, finance, telecom) are already experimenting. Quantum could break today’s encryption—data you protect now may not be safe later. 👉 Bottom line: If you’re not preparing, you’re already behind. Quantum computing is coming. Corporate America isn't ready https://lnkd.in/gRhhM4bK

Microsoft Claims Breakthrough in Quantum Error Correction With 4D Codes Introduction Quantum computing’s greatest obstacle has long been error correction, as fragile qubits are prone to failure and cannot be copied like classical bits. Microsoft now says it has achieved a major breakthrough with a new “4D geometric coding” method that reduces quantum errors by a factor of 1,000. This advance could mark a turning point toward fault-tolerant, scalable quantum machines. Key Details • The Error Problem in Quantum Systems • Classical error correction relies on redundancy—making multiple copies of bits. • Qubits, however, collapse when measured and cannot be cloned, making direct error correction extremely difficult. • Quantum systems experience error rates far higher than classical computers, limiting practical applications. • Microsoft’s 4D Geometric Coding • The new technique applies four-dimensional codes to entangle “logical” qubits with additional “physical” qubits. • Errors can then be detected and corrected indirectly, without disturbing the logical qubits themselves. • Reported results show a 1,000-fold reduction in errors, dramatically improving reliability. • Fault-Tolerance Breakthrough • The technique addresses the key bottleneck to building practical, universal quantum computers. • Scientists suggest this may be the foundation for reliable large-scale quantum hardware. • Microsoft’s Positioning • The announcement, made in a June 19 blog post, emphasizes that “reliable quantum computing is here.” • It reinforces Microsoft’s strategy of combining advanced theory with scalable architecture to compete in the global quantum race. Why It Matters If validated, Microsoft’s 4D code breakthrough could unlock the long-sought era of fault-tolerant quantum computing. Reliable qubits would pave the way for solving problems beyond the reach of classical supercomputers, from cryptography and climate modeling to drug discovery and advanced materials. By reducing error rates a thousandfold, Microsoft may have delivered the missing piece needed to transition quantum computing from experimental labs to real-world industries. I’ve had the privilege of reaching over 17 million views in the past year, sharing daily insights with a network of 26,000+ followers and 9,000+ professional contacts across defense, technology, and policy. If this topic resonates, I welcome you to connect and continue the conversation. Keith King https://lnkd.in/gHPvUttw

This week Google Quantum AI was announced as an entrant to the Defense Advanced Research Projects Agency (DARPA) quantum benchmarking initiative (QBI). This initiative was set up last year with a simple aim: to (rigorously) verify and validate, through a multi-year three-stage program, if any quantum computing approach can achieve utility-scale operation - meaning its computational value exceeds its cost - within a decade. In essence, DARPA threw down a gauntlet for quantum companies to show that their technology could plausibly lead to a fault-tolerant quantum computer. Google Quantum AI is just the latest to take up this challenge. 16 other quantum companies have already done so, with one more yet to be announced (the full list can be found here: https://lnkd.in/eK-3gpir). It’s worth noting that just to get to this point, each of these companies has already had to show serious promise through a process including a daylong oral presentation before a team of U.S. quantum experts, which is worthy of celebration in itself. In addition to the 17 current QBI companies, mention should also be made of PsiQuantum and Microsoft. Whilst not a part of the QBI, both have now entered the third phase of DARPA’s related Underexplored Systems for Utility-Scale Quantum Computing (US2QC) program. Notably, this third phase has the same technical goals as stage C (i.e., the final stage) of the QBI - verification and validation of an industrially useful quantum computer. The companies involved in the DARPA programs highlight the incredible diversity within quantum research, with each company exploring a different approach toward the same ultimate end goal. Such a showcase of competing (though in many cases complimentary) ideas is fascinating to see from an intellectual property perspective. But perhaps the most interesting takeaways revealed by this collection of companies are: 🌍 The global nature of quantum research and innovation: undoubtedly the US is a major hub (just over half of the companies are headquartered there), but participants from each of Canada, the UK, France, and Australia also appear. 📈 The significant role that start-ups are playing in this space: 13(!) of these 19 companies were founded after the start of 2015, showcasing just how much quantum innovation is being driven by focused, venture-backed start-ups (emphasis placed on ‘venture-backed’ here, with lots of investment and fundraising announcements coming out of the quantum space in just the last few weeks alone). It’ll be interesting to see who is announced as the final member of the DARPA QBI program, and how the program progresses over the next few years! #QuantumComputing #DARPA #DeepTech #Innovation #QuantumTechnology #QuantumBenchmarking #GlobalTech Mewburn Ellis

The Near Future of Quantum Computing: A Game-Changer Awaits 🚀 Quantum computing is no longer a distant dream—it’s rapidly moving toward becoming a transformative force in technology, science, and business. But what does the near future hold? ✅ From Theory to Practicality In the next few years, we’ll see quantum computing shift from experimental research to real-world applications, particularly in sectors like cryptography, pharmaceuticals, finance, and logistics. Quantum algorithms will begin solving problems that classical computers simply can’t handle efficiently. ✅ Hybrid Systems Will Lead the Way Rather than replacing classical systems, quantum computers will augment existing infrastructure, working alongside traditional supercomputers to tackle highly complex computations. ✅ Breakthroughs in Security & AI Expect advancements in post-quantum cryptography to protect data in a quantum-powered world. In AI, quantum computing will accelerate training times and enable more powerful models for pattern recognition and optimization. ✅ Challenges Remain Stability, error correction, and scalability are still hurdles, but tech giants and startups are investing heavily in quantum error correction and qubit coherence, bringing us closer to practical quantum advantage. 📌 Bottom line: In the near future, quantum computing will redefine problem-solving, opening doors to innovation that was once considered impossible. The companies preparing for this paradigm shift today will be the leaders of tomorrow.

Current Market Status and Outlook: 1. Global quantum computing is currently in the NISQ (Noisy Intermediate-Scale Quantum) era, characterized by systems with 50–1000 qubits, lacking fault-tolerant mechanisms, exhibiting high error rates, and applications remaining in the prototype verification stage. 2. Technologically, the focus centers on variational quantum algorithms (VQA), including VQE, QAOA, and QML, applied to molecular simulation, combinatorial optimization, and quantum machine learning. 3. U.S. firms like IBM, Google, and IonQ maintain leadership, focusing on platform scaling and fault-tolerant R&D; China strengthens government-industry-academia collaboration, with CAS and Baidu spearheading cloud platform and chip development; Europe leverages flagship initiatives to integrate Pasqal, IQM, and academic/research institutions, accelerating modular scenario implementation. 4. PEST analysis reveals three major regions forming competitive-cooperative dynamics: the U.S. leads in technology and capital, China leverages policy drivers and infrastructure advantages, while Europe emphasizes ethics and transnational integration. These three players are progressively engaging in multi-track interactions across standardization, security regulations, computing power competition, and application domains. 5. Four major challenges persist: high error rates (requiring QEC support), high costs (dilution and cooling equipment are expensive), talent gaps (insufficient interdisciplinary expertise), and lack of international standards (risk of governance fragmentation). 6. The quantum industry chain is taking shape, with upstream segments still dominant. However, the market value share of mid-to-downstream segments is rapidly increasing, and the commercial potential of applications and platforms is being unlocked. 7. Global market distribution by region is approximately: U.S. 30–40%, China 28%, Europe 30%. Regional differentiation in competition is emerging based on technological strengths, market scale, capital, and institutional frameworks. 8. Looking ahead to 2024–2028, the global market size is projected to grow from RMB 6.95 billion to over RMB 25 billion, achieving a CAGR of 38%. The downstream applications segment is expected to expand its market share from 15% to 30%. 市場現狀況與展望： 1. 全球量子計算正處於 NISQ 時代（含噪中型量子階段），特徵為 50–1000 量子比特、無容錯機制、誤差率高、應用處於原型驗證階段。 2. 技術層面以變分量子演算法（VQA）為主線，包括 VQE、QAOA、QML 等，應用於分子模擬、組合優化與量子機器學習等領域。 3. 美國企業如 IBM、Google、IonQ 持續領先，聚焦平臺擴展與容錯技術研發；中國強化政產學聯動，以中科院、百度為核心推動雲平臺與晶片研發；歐洲則以旗艦計畫整合 Pasqal、IQM 與學研機構加速模組化場景落地。 4. PEST 分析顯示三大區域形成競合：美國技術與資本領先、中國政策驅動與基建優勢、歐洲重視倫理與跨國整合，三者在標準制定、安全法規、算力競爭與應用領域逐步展開多軌互動。 5. 當前仍面臨四重挑戰：高錯誤率（需千比特糾錯碼支撐）、高成本（稀釋冷卻設備昂貴）、人才缺口（跨學科人才不足）、缺乏國際標準（治理碎片化風險）。 6. 量子產業鏈初步形成，上游仍占多數，但中下游市值占比快速提升，應用與平臺商業化潛力釋放中。 7. 全球主要地區占比分布為：美國約 30–40%、中國約 28%、歐洲約 30%，彼此以技術優勢、市場規模、資金與制度形成區域分化競爭。 8. 展望 2024–2028 年，全球市場規模預估將從 69.5 億人民幣增至超過 250 億，CAGR 達 38%；下游應用預計市值占比從 15% 擴展至 30%。

Embracing AI-first Automation with Quantum Computing :- (Future has begun already) As automation becomes increasingly prevalent in various industries, organizations are seeking innovative approaches to enhance productivity, improve accuracy, and streamline processes. One emerging technology that holds immense promise in achieving these objectives is quantum computing. Although still in its early stages, quantum computing has the potential to revolutionize automated workflows by tackling complex problems that are currently intractable for classical computers. By exploiting the principles of quantum mechanics, quantum computers can evaluate numerous possibilities simultaneously, enabling them to optimize and analyze vast datasets far more efficiently than traditional computational models. Consequently, quantum computing can significantly contribute to enhancing automation efforts in areas such as logistics, manufacturing, finance, and artificial intelligence. For example, in supply chain management, quantum computing can assist in optimizing delivery routes, predicting demand fluctuations, and identifying bottlenecks, thereby facilitating seamless coordination and resource allocation. Similarly, in finance, quantum algorithms can potentially uncover hidden patterns and correlations in financial markets, enabling investors to make more informed decisions and mitigate risks more effectively. Moreover, in the realm of artificial intelligence, quantum computing can augment machine learning algorithms, empowering them to learn from larger datasets and make more nuanced predictions. This enhanced capability can lead to improved decision-making, increased operational efficiency and better customer experiences across diverse sectors. However, integrating quantum computing into existing automation frameworks presents several challenges. Chief among these is, addressing the noise inherent in quantum systems, which can produce errors and hinder performance. Additionally, developing efficient quantum algorithms tailored to specific industrial applications remains a challenging task. Despite these hurdles, ongoing research and development in quantum computing continue to yield encouraging results, paving the way for a brighter future of automation and Industry 4.0.

Quantum Computing vs. Classical Supercomputing: Partners, Not Rivals! There's a common view that quantum computing is going to take over from today’s powerful supercomputers. But the truth is a lot more complicated. Instead of being a replacement, quantum machines are actually specialised tools that work alongside classical systems. Why Quantum Won't Replace Classical Computing Classical supercomputers are still the best at handling large-scale simulations, heavy-duty data analysis, and deep learning. These areas have benefited from years of development (Dongarra et al., 2020). On the other hand, quantum devices use superposition and entanglement to tackle specific problems that don't work well on classical computers. The foundational work by Shor (1994) and Grover (1996) highlighted this potential, and Aspuru-Guzik et al. (2005) showed how quantum simulation can be really effective in fields like chemistry and materials science. The Case for Hybrid Models We're starting to see a shift towards hybrid computing. For instance, IBM’s Quantum Roadmap (2023) reveals how quantum processors can be integrated into high-performance computing (HPC) workflows, especially with tools like Qiskit Runtime. Google Quantum AI is also diving into hybrid approaches for optimization and materials research (Arute et al., 2019). In Australia, Q-CTRL is working on error correction and control software, paving the way for practical hybrid systems. Just like GPUs enhanced CPUs without taking their place, quantum technology is poised to complement traditional computing. Why This Matters For researchers, businesses, and policymakers, it's important to understand that the real benefits of quantum will come when it's used alongside classical computing, not by itself. The breakthroughs will happen at the intersection of these two technologies, leading to significant improvements in established HPC environments. Embracing this future means investing in training, funding, and collaboration between both domains. In short, quantum computing isn’t about replacing classical systems; it’s about creating a partnership. Together, their combined strengths may help us tackle challenges that seemed impossible before. Robert SangUniversity of Southern QueenslandIBMQ-CTRLQuantum Australia