Latest news with #QuantumComputing
Yahoo
5 hours ago
- Business
- Yahoo
Quantum Computing (QUBT) Climbs 8% on New Govt Deal
We recently published . Quantum Computing Inc. (NASDAQ:QUBT) is one of the best-performing stocks on Tuesday. Quantum Computing saw its share prices increase by 8.27 percent on Tuesday to close at $16.89 apiece after bagging a new deal from the US Department of Commerce for the development and supply of thin-film lithium niobate (TFLN) photonic integrated circuits (PICs). Under the agreement, Quantum Computing Inc. (NASDAQ:QUBT) will design and fabricate TFLN-based PICs, with performance requirements focused on low optical-loss waveguides, high-performance modulators, and narrow-band filters. Quantum Computing Inc. (NASDAQ:QUBT) said in a statement that new new award was its first direct government contract for its TFLN foundry services and represented a key step in its plans to become a trusted supplier of advanced photonic technologies. 'QCi is proud to deliver advanced photonic solutions to market through our commercial foundry. Additionally, we're pleased to add a leading Fortune 500 defense and technology contractor to our growing list of commercial customers, reinforcing the broad applicability of our TFLN platform across high-security, mission-critical environments.' While we acknowledge the potential of QUBT as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and have limited downside risk. If you are looking for an extremely cheap AI stock that is also a major beneficiary of Trump tariffs and onshoring, see our free report on the . Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
17 hours ago
- Business
- Yahoo
QUBT Rallies 113% Amid Quantum Deals: Will the Momentum Last?
Quantum Computing Inc. QUBT is progressing in 2025 in terms of both hardware advancements and strategic customer wins to broaden its market footprint. A major milestone is the delivery of its first commercial entangled photon source, a bulk Periodically Poled Lithium Niobate (PPLN) device, to a prominent South Korean research institution earlier this year. This marked QUBT's first commercial foray into photonic quantum hardware beyond optimization platforms, signaling a pivotal expansion in its product portfolio. Simultaneously, QUBT made its commercial debut in quantum-secured communications by securing a $332,000 order from a top-five U.S. bank to deploy a quantum communication system in a secure testbed. This is particularly notable as it positions QUBT to tap into the growing demand for cybersecurity solutions leveraging quantum technologies, a field poised for rapid growth, given rising concerns over classical encryption vulnerabilities. These wins come as QUBT increasingly targets real-world applications across critical verticals, including finance, national security, space and life sciences with its hardware-software co-development strategy. The company has also indicated that follow-on orders or scale-up discussions may be underway, which could provide more visibility into future revenue recognition as early pilot deployments mature. How are QUBT Peers Positioned Now? IonQ IONQ: It recently partnered with Australia's Emergence Quantum to co-develop advanced materials for trapped-ion systems and expand in the Asia-Pacific region. IonQ also secured a $22-million deal with EPB in Chattanooga to create a U.S. hub for quantum computing and networking. D-Wave Quantum QBTS: It raised $400 million in July 2025, boosting liquidity to over $800 million for scaling and strategic M&A. D-Wave also announced a NASA-partnered cryogenic packaging initiative to enhance processor density. QUBT's Price Performance Quantum Computing has rallied 112.8% in the past three months compared with the industry's 18.2% growth and the sector's 19% rise. The S&P 500 index, meanwhile, has improved 11.1% during the said period. Three-Month Share Price Comparison: QUBT Image Source: Zacks Investment Research Average Target Price Shows Near-term Upside Based on short-term price targets, Quantum Computing is currently trading 25% below its average Zacks price target. Image Source: Zacks Investment Research QUBT currently carries a Zacks Rank #3 (Hold). You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here. Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Quantum Computing Inc. (QUBT) : Free Stock Analysis Report IonQ, Inc. (IONQ) : Free Stock Analysis Report D-Wave Quantum Inc. (QBTS) : Free Stock Analysis Report This article originally published on Zacks Investment Research ( Zacks Investment Research
Forbes
a day ago
- Business
- Forbes
Top Infrastructure Upgrades Needed To Support AI And Quantum Growth
Emerging technologies like artificial intelligence and quantum computing have the potential to reshape nearly every industry—but only if global infrastructure evolves fast enough to support them. From intelligent energy systems and ultra-fast connectivity to new governance models and quantum-safe security, foundational upgrades are essential. The approaching tech revolution requires more than just faster chips or bigger data centers; business and government leaders must rethink how they manage power, information, regulations and talent. Below, members of Forbes Technology Council highlight the most critical infrastructure shifts needed to unlock the full potential of next-generation innovation. 1. Time-Aware Infrastructure What we need is time-aware infrastructure—systems that don't just process data fast, but also understand when to act, defer or self-correct. Next-gen tech isn't just about power; it's about precision, timing and trust. Without temporal intelligence, scale becomes noise. - Adam Zachary, Mobiz IT 2. Expanded Global Connectivity To support AI and quantum tech, the world needs much faster, more stable and more secure internet (like 5G, 6G and quantum internet). Without strong global connectivity, these technologies can't transfer huge amounts of data quickly or work effectively for health, research and industry. - Gopikrishnan Anilkumar, Amazon Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? 3. Quantum-Ready Talent The critical upgrade isn't hardware—it's human capital. We're building quantum-ready infrastructure while our workforce still struggles with basic cloud concepts. The biggest bottleneck will be finding engineers who understand both legacy systems and quantum principles. Infrastructure is useless without operators who can manage it. - Anna Turos, Lighthouse HQ 4. Modern Power Grids We need a power grid glow-up—energy infrastructure is the bottleneck. AI and quantum suck juice like V8s with turbos. Without smarter, decentralized grids—think microgrids and edge energy—tech will stall. I saw this at GM data centers. Future tech isn't just code—it's current. No watts, no wonder. - Tim Bates, Godfather of Tech 5. Sustainable Compute Practices The AI gold rush is overwhelming infrastructure that was never built for this scale. Power grids are strained, data centers are bottlenecked and companies keep throwing more hardware at the problem. That model is broken. Without a shift to workload efficiency, longer asset life and sustainable compute practices, AI's growth will collapse under the weight of its own demand. It's time to rethink the foundation. - Tomas O Leary, Origina 6. Agentic AI Functionality One critical upgrade is building infrastructure that supports agentic AI, or AI that acts on behalf of users. To unlock its full potential, global systems must prioritize performance, scalability and seamless integration, enabling AI to transform everyday users into power users by automating repetitive tasks and enhancing productivity. - Adam Lieberman, Finastra 7. Global Ethical Protocols We need global standardization of ethical protocols. To harness AI and quantum safely, nations must establish interoperable ethical frameworks and audit standards. Without harmonized regulations on data use, algorithmic bias and quantum encryption, cross-border innovation risks fragmentation and public mistrust, stifling the very technologies meant to advance humanity. - Cristian Randieri, Intellisystem Technologies 8. Data-Centric Architectures To support next-gen tech like AI and quantum, global infrastructure must shift to data-centric architectures—scalable, low-latency systems that move data closer to compute. Speed, locality and parallelism will define success as workloads outpace traditional network and storage designs. - Sven Oehme, DataDirect Networks 9. Increased Bandwidth Accessibility I do not believe global infrastructure can handle the bandwidth necessary for AI and quantum to grow substantially. Currently, 1 Gbps symmetrical service is difficult to find, and when it is available, the price is often out of reach, especially for small businesses and tech startups. The lack of available bandwidth and the cost of bandwidth will slow the adoption of AI and quantum technologies. - Robert Martin, Oil City Iron Works, Inc. 10. Upgraded Energy Distribution Systems A critical shift is modernizing power infrastructure. AI and quantum workloads demand immense, stable energy. Without investment in clean, high-density energy grids and smarter distribution, innovation will bottleneck at the plug. Energy is the new scalability frontier. - Luis Peralta, Parallel Plus, Inc. (dba ParallelStaff) 11. Data That's Decoupled From Applications A critical shift is decoupling data from applications. Today, data is linked to specific apps, limiting AI's ability to access and learn from it. Unlocking next-gen tech like AI and quantum requires treating data as a universal asset, accessible across platforms and systems. - Yogesh Malik, Way2Direct 12. HPC-Grade Infrastructure To support AI and quantum computing, enterprises must shift to HPC-grade infrastructure built with accelerated processors, high-speed networking and scalable storage. This upgrade enables faster data processing, low-latency hybrid workloads and quantum-safe security, making it essential for next-gen innovation across IT. - Sai Sandeep Ogety 13. More Resilient, Smart-Routing Infrastructure Survivability is critical for global infrastructure as AI and quantum continue to boom. Dense, distributed workloads mean zero tolerance for downtime. Single-region, monolithic systems won't cut it. We need infrastructure built to expect failure, reroute around it and stay consistent when regions or providers go dark. If you can't guarantee consistency, you aren't ready for what's coming. - Spencer Kimball, Cockroach Labs 14. Data Interoperability A critical shift is data interoperability. The future of AI depends less on raw compute power and more on whether systems—especially in healthcare—can speak the same language. Without harmonized, structured data, even the best models are flying blind. - Zameer Rizvi, Odesso Inc. 15. Post-Quantum Cryptography A critical shift will be the widespread adoption of post-quantum cryptography (PQC). As quantum computers advance, they'll threaten current encryption methods. Global infrastructure must rapidly transition to quantum-resistant algorithms to protect sensitive data and critical systems across all industries, from finance to healthcare, before a 'quantum doomsday' scenario. - Dennis-Kenji Kipker, 16. Deterministic Networking AI and quantum don't just need speed; they need precision. One failed deployment showed us it's not bandwidth that breaks systems, but timing. A few milliseconds of network jitter, and the model collapses. The next wave of infrastructure must prioritize deterministic networking and tightly synchronized edge computing. Without timing, intelligence stalls. - Aditya Vikram Kashyap, Morgan Stanley 17. Energy-Resilient Compute Fabrics To support AI and quantum at scale, global infrastructure must shift toward energy-resilient compute fabrics—integrated systems that co-optimize compute, cooling and clean power. These workloads demand not just speed, but also sustainability. Without upgrading to intelligent, decentralized and carbon-aware compute grids, the physical backbone for next-gen tech will become a bottleneck. - Giridhar Raj Singh Chowhan, Microsoft 18. Modernized Data Centers One key upgrade will be modernizing global data centers to meet the huge demands of AI and quantum computing—both in terms of processing power and energy use. This means adding advanced cooling systems, faster networking and hybrid setups that combine classical and quantum technologies, all while shifting to more sustainable energy sources to keep up with rapid data growth. - Ajit Sahu, Walmart
Forbes
2 days ago
- Business
- Forbes
Quantum Machine Learning: Here's How Business Leaders Can Prepare Now
Klaudia Zaika is the CEO of Apriorit, a software development company that provides engineering services globally to tech companies. The computational demands of today's AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML introduces a fundamentally different approach to learning and optimization by applying quantum principles to AI algorithm design. This isn't a replacement, but rather an enhancement to classical AI and problem-solving. You may think that it's too early to prepare for QML, as most of today's quantum-related projects remain experimental and scientific. But not so long ago, in 2022, almost no one had heard about ChatGPT, and Google's Bard (now Gemini) wasn't even released yet. Now, as we've all seen, they are among the top go-to services for anything from organizing personal schedules to operating large enterprises. That's how fast these technologies evolve. This is why I believe that now is the perfect time to get ready and start building new infrastructures, developing new skills and planning your QML adoption strategy. What Makes Quantum Machine Learning Different QML isn't just about running existing AI models on faster hardware. It's about reimagining how learning itself happens. Classical AI systems rely on binary data structures and deterministic logic. These models weren't built to take advantage of quantum behavior and may lose efficiency or accuracy when forced into that environment. In contrast, QML models are designed to implement quantum principles like superposition and entanglement. These capabilities allow QML models to explore complex problem spaces more efficiently than non-quantum systems. As this field is still forming, there's no unified vision for the term 'quantum machine learning,' and it often refers to: • Quantum-enhanced machine learning, where quantum algorithms boost specific AI tasks, such as optimization or clustering. • Machine learning-enhanced processing of quantum data and the outputs from quantum experiments or simulations. • Hybrid quantum-classical models that combine two previous approaches and are often the most practical path forward in today's noisy intermediate-scale quantum (NISQ) era. With so much ambiguity, the path to industrial adoption of QML seems to be far from straightforward and is filled with lots of obstacles. Knowing and preparing for these obstacles will help your business avoid costly missteps when integrating this technology into your products, services and organizational processes. Barriers To Widespread QML Adoption From my company's experience with similar ground-breaking innovations, specifically cloud and AI, there are a few challenges that I believe leaders in this space should expect first. Take model size and complexity, for instance. The first and most important barrier to account for in this case is hardware. Most quantum systems today still fall into the NISQ category. They are a good fit for experimentation but won't be able to handle broad commercial deployment as they lack qubit stability, error correction and scalability. Next, if you look at today's software architectures, you'll see that they are also not ready for quantum adoption. In fact, there's still a lot of work for those who want to make legacy systems cloud- and AI-compatible, even in terms of building the right data architectures. And QML requires much more architectural modularity and flexibility than any other technology we can think of today. Hybrid systems are also a challenge of their own. You'll need to determine which functions to delegate to the quantum part and which are better left with the traditional, non-quantum side of your system. Designing and testing these hybrid environments, as well as integrating them with the existing software ecosystems, will require new thinking, especially in cybersecurity, data handling and orchestration. Last but not least, there's a deep talent gap. Quantum computing and machine learning are complex fields, and very few professionals are trained at the intersection of those two. When you listen to quantum enthusiasts, you may feel tempted to treat QML as an emerging silver bullet, which it isn't. Yet, it's a fundamental shift that will require prolonged, well-planned preparations from your business. How To Prepare For QML Today: A Strategic Roadmap QML adoption is a marathon, not a race. So if you want your business to use and benefit from QML, it's already time to prepare your teams, processes and software architecture for what's coming. Here's what you can start doing right now: 1. Educate your team. You don't need a quantum physicist on staff tomorrow, but your developers and architects should start building foundational literacy. Workshops, online courses and partnerships with academic programs can accelerate this process and help your business mitigate the risk of facing talent shortages in the future. 2. Explore low-risk pilot projects. Optimization, anomaly detection and pattern recognition are great starting points, especially when executed using quantum simulators or early-access platforms. These efforts can help your teams build hands-on familiarity without overcommitting. On the other hand, if you engage early as a business, whether through vendor exploration or academic partnerships, you can gain better visibility into what's coming and where your organization fits. 3. Build adaptable software architectures. Flexible, non-monolithic architectures are already gaining traction. But to prepare your software for QML or post-quantum cryptography (PQC), you need to bring it to a whole new level of agility. This means making your software architecture mostly API-driven, modular and as loosely coupled as possible. 4. Evolve your cybersecurity measures. Even if QML doesn't fit your business, you still need to think about ways to protect your data and systems from upcoming quantum threats. In particular, make sure to keep track of the US National Quantum Initiative and the latest PQC news from NIST. 5. Plan for the long run. QML isn't an investment that can offer a short-term ROI for most companies. Yet, just like cloud and AI before it, I believe this technology will fundamentally reshape how software is developed and deployed. The shift to quantum machine learning won't happen overnight. That means you still have time to prepare your business for the adoption of this promising technology—from considering fitting use cases and determining where and how QML will benefit you the most to deciding on the first implementation steps. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Yahoo
3 days ago
- Business
- Yahoo
Huationg Global (Catalist:41B) shareholders have earned a 43% CAGR over the last five years
Long term investing can be life changing when you buy and hold the truly great businesses. While not every stock performs well, when investors win, they can win big. Don't believe it? Then look at the Huationg Global Limited (Catalist:41B) share price. It's 393% higher than it was five years ago. This just goes to show the value creation that some businesses can achieve. On top of that, the share price is up 56% in about a quarter. Now it's worth having a look at the company's fundamentals too, because that will help us determine if the long term shareholder return has matched the performance of the underlying business. This technology could replace computers: discover the 20 stocks are working to make quantum computing a reality. To quote Buffett, 'Ships will sail around the world but the Flat Earth Society will flourish. There will continue to be wide discrepancies between price and value in the marketplace...' One flawed but reasonable way to assess how sentiment around a company has changed is to compare the earnings per share (EPS) with the share price. Over half a decade, Huationg Global managed to grow its earnings per share at 36% a year. This EPS growth is remarkably close to the 38% average annual increase in the share price. Therefore one could conclude that sentiment towards the shares hasn't morphed very much. Rather, the share price has approximately tracked EPS growth. The image below shows how EPS has tracked over time (if you click on the image you can see greater detail). Before buying or selling a stock, we always recommend a close examination of historic growth trends, available here. What About Dividends? As well as measuring the share price return, investors should also consider the total shareholder return (TSR). The TSR incorporates the value of any spin-offs or discounted capital raisings, along with any dividends, based on the assumption that the dividends are reinvested. So for companies that pay a generous dividend, the TSR is often a lot higher than the share price return. We note that for Huationg Global the TSR over the last 5 years was 499%, which is better than the share price return mentioned above. And there's no prize for guessing that the dividend payments largely explain the divergence! A Different Perspective It's good to see that Huationg Global has rewarded shareholders with a total shareholder return of 217% in the last twelve months. That's including the dividend. Since the one-year TSR is better than the five-year TSR (the latter coming in at 43% per year), it would seem that the stock's performance has improved in recent times. Given the share price momentum remains strong, it might be worth taking a closer look at the stock, lest you miss an opportunity. It's always interesting to track share price performance over the longer term. But to understand Huationg Global better, we need to consider many other factors. Take risks, for example - Huationg Global has 3 warning signs we think you should be aware of. If you are like me, then you will not want to miss this free list of undervalued small caps that insiders are buying. Please note, the market returns quoted in this article reflect the market weighted average returns of stocks that currently trade on Singaporean exchanges. Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
