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It's a marriage that could only happen in cyberspace -- quantum computing and artificial intelligence.

Quantum AI is a burgeoning computer science sector, dedicated to exploring the potential synergy that exists between quantum computing and AI, says Gushu Li, a professor at the University of Pennsylvania School of Engineering and Applied Science, in an email interview. "It seeks to apply principles from quantum mechanics to enhance AI algorithms." A growing number of researchers now believe that AI models developed with quantum computing will soon outpace classical computing AI development.

Quantum AI creates an intersection between quantum computing and artificial intelligence, observes Romn Ors, chief scientific officer at quantum computing software development firm Multiverse Computing, via email. He notes that quantum computing has the potential to take AI to entirely new levels of performance. "For instance, it's possible to develop quantum neural networks that teach a quantum computer to detect anomalies, do image recognition, and other tasks." Ors adds that it's also possible to improve traditional AI methods by using quantum-inspired approaches to dramatically reduce the development and training costs of large language models (LLMs).

Related:Demystifying Quantum Computing: Separating Fact from Fiction

Combining the quantum physics properties of superposition and entanglement, which can perform limitless processes simultaneously with machine learning and AI, and suddenly it's possible to do more than ever imagined, says Tom Patterson, emerging technology security lead at business advisory firm Accenture, via email. "Unfortunately, that includes being used by adversaries to crack our encryption and develop new and insidious ways to separate us from our information, valuables, and anything else we hold dear."

Still, Patterson is generally optimistic. Like ChatGPT, he expects quantum AI to arrive gradually, and then all at once. "While full use of an AI-relevant quantum computer remains years away, the benefits of thinking about AI with quantum information science capabilities are exciting and important today," he states. "The opportunities are here and now, and the future is brighter than ever with quantum AI."

For his part, Li believes that quantum AI's biggest initial impact will be in four specific areas:

Drug Discovery: Simulating molecules to design new drugs and materials with superior properties.

Financial Modeling: Optimizing complex financial portfolios and uncovering hidden trends in the market.

Related:Cybersecurity's Future: Facing Post-Quantum Cryptography Peril

Materials Science: Developing new materials with specific properties for applications like superconductors or ultra-efficient solar cells.

Logistics and Optimization: Finding the most efficient routes for transportation and optimizing complex supply chains.

Quantum AI is already here, but it's a silent revolution, Ors says. "The first applications of quantum AI are finding commercial value, such as those related to LLMs, as well as in image recognition and prediction systems," he states. More quantum AI applications will become available as quantum computers grow more powerful. "It's expected that in two-to-three years there will be a broad range of industrial applications of quantum AI."

Yet the road ahead may be rocky, Li warns. "It's well known that quantum hardware suffers from noise that can destroy computation," he says. "Quantum error correction promises a potential solution, but that technology isn't yet available."

Meanwhile, while quantum AI algorithms are being developed, classical computing competitors are achieving new AI successes. "While progress is being made, it's prudent to acknowledge that the integration of quantum computing with AI is a complex endeavor that will unfold gradually," Li says.

Related:What Is the Future of AI-Driven Employee Monitoring?

Patterson notes that many of the most promising quantum AI breakthroughs aren't arriving from university and corporate research teams, but from various regional developer and support communities that closely mirror natural ecosystems. "Regions that have decided that quantum and AI are too big and too important to leave to one group or another have organized around providing everything progress demands -- from investment to science to academics to entrepreneurs, growth engines, and tier-one buyers," he says. "These regional ecosystems are where the magic happens with quantum AI."

GenAI and quantum computing are mind-blowing advances in computing technology, says Guy Harrison, enterprise architect at cybersecurity technology company OneSpan, in a recent email interview. "AI is a sophisticated software layer that emulates the very capabilities of human intelligence, while quantum computing is assembling the very building blocks of the universe to create a computing substrate," he explains. "We're pushing computing both into the realm of the mind and the realm of the sub-atomic."

The transition to quantum AI won't be optional, Ors warns, since current AI is fundamentally flawed due to excessive energy costs. New models and methods will be needed to lower energy demands and to make AI feasible in the long term. "Early adopters of quantum AI will get a competitive advantage and will survive, as opposed to those that do not adopt or adopt it too late."

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Quantum Computing and AI: A Perfect Match? - InformationWeek

You have recently been selected to the Tech Nations Future Fifty programme. What are your expectations and how does it feel to be identified as a future unicorn?

Were delighted to have been selected as the sole representative of a rich and diverse UK quantum tech industry. The quantum computing marketing is expected to grow to $28-72B over the next decade so I expect many unicorns to emerge, and we certainly hope to be one of them. Tech Nation has an excellent track record of picking and supporting high-growth leaders. Were excited to make the most of the opportunities the programme offers.

Quantum computing is an amazing idea the ability to harness the power of the atom to perform computation will transform many industries. Back in 2016, I was a research fellow at the University of Cambridge, and at that time, the majority view was that building a useful quantum computer wouldn't be possible in our lifetime - it was simply too big and too hard a problem. I disagreed but needed to validate this. By meeting with teams building quantum computers, I saw an amazing rate of progress a 'Moore's Law' of quantum computing with a doubling in power every two years, just like classical computers have done. That was the catalyst moment for me, and it became clear that if that trend continued, the next big problem would be quantum error correction. I founded Riverlane to make useful quantum computers a reality sooner!

Were building a technology called the quantum error correction stack, which corrects errors in quantum computers. Todays quantum computers can only perform a thousand or so operations before they fail under the weight of these errors. Quantum error correction technology will ultimately enable trillions of error-free operations, unlocking their full and transformative potential.

Implementing quantum error correction to achieve this milestone requires specialised knowledge of quantum science, engineering, software development and chip manufacturing. That makes quantum error correction systems difficult for each quantum computer maker to develop independently. Our strategy is not dissimilar to NVIDIA in providing a core enabling technology for an entirely new computing category.

When Riverlane was founded in 2016, there was a lot of focus on developing software applications to solve novel problems on small-scale quantum computers, a phase known as the noisy intermediate-scale quantum (NISQ) era. However, after the limits of NISQ became apparent due to considerable error rates hindering calculations, the industry shifted focus to building large and reliable quantum computers that could overcome the error problem

This is something weve been working on from the start through the invention of our quantum error correction stack but were now doubling down on its development to meet this growing demand from the industry. An important part to this has been scaling our team to nearly 100 people across our two offices in Cambridge (UK) and Boston (US) - two world-leading centres for quantum computing research and development.

Its a common misconception that you need a PhD in quantum physics or computer science to work in our field. The reality is we need people with a wide range of skills and from the broadest possible mix of backgrounds and demographics. Collectively, were a group that loves tackling hard and complex problems if not the hardest! This requires a culture that blends extremes of creativity, curiosity, problem-solving and analytical skills, plus an alchemy of driving urgency and zen like patience. Im also proud of the extraordinary openness and diversity of our team, including a healthy gender mix in a field where this is the exception not the norm.

Ive been fascinated with quantum physics since I was a student. Back then, the idea of building a computer that applied the unique properties of subatomic particles into computers to transform our understanding of nature and the universe was pure science fiction. Building a company that is now achieving this feels almost miraculous. Building a company with the right mix of skills and shared focus to do far faster than previously imaginable is brutally tricky and joyously rewarding in equal parts

Last September, we launched the worlds first quantum error correction chip. As the quantum computing industry develops, these chips will get better and better, faster and faster. Theyll ultimately enable the quantum industry to scale beyond its current limitations to achieve its full potential to solve currently impossible problems in areas like healthcare, climate science and chemistry. At a recent quantum conference, someone stood up and said quantum computing will be bigger than fire. I wouldnt go quite that far! But theyll unlock a fundamental new era of human knowledge and thats super exciting.

Have a bold and ambitious vision thats underpinned by a proven insight and data. In my case, it was that the presumption that a quantum computer was simply too hard to ever build could be disproven and overcome. Once you have this, be ready to learn fast and pivot fast in your tactics but never lose sight of your goal.

I spend at least a third of my time travelling. Meeting global leaders in our field face to face to hear their ideas, track their progress and build partnerships is priceless. When Im home, Im lucky enough to live about a mile from our office in Cambridge. No matter the weather, I walk to and from work every day. Cambridge is a beautiful place - the thinking time and fresh air give me energy and a calm headspace.

Steve Brierley is the CEO of Riverlane.

Tech Nations Future Fifty Programmeis designed to support late-stage companies with access and growth opportunities, the programme has supported some of the UKs most prominent unicorns, including Monzo, Darktrace, Revolut, Starling, Skyscanner and Deliveroo.

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Riverlane, the company making quantum computing useful far sooner than anticipated - Maddyness

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The novel quantum data assimilation method can significantly reduce the computation time required for numerical weather prediction, enabling deeper understanding and improved predictions

Credit: Brett Jordan from Openverse https://openverse.org/image/563410ca-1385-475c-a7f6-fd521f910623

Data assimilation is a mathematical discipline that integrates observed data and numerical models to improve the interpretation and prediction of dynamical systems. It is a crucial component of earth sciences, particularly in numerical weather prediction (NWP). Data assimilation techniques have been widely investigated in NWP in the last two decades to refine the initial conditions of weather models by combining model forecasts and observational data. Most NWP centers around the world employ variational and ensemble-variational data assimilation methods, which iteratively reduce cost functions via gradient-based optimization. However, these methods require significant computational resources.

Recently, quantum computing has emerged as a new avenue of computational technology, offering a promising solution for overcoming the computational challenges of classical computers. Quantum computers can take advantage of quantum effects such as tunneling, superposition, and entanglement to significantly reduce computational demands. Quantum annealing machines, in particular, are powerful for solving optimization problems.

In a recent study, Professor Shunji Kotsuki from the Institute for Advanced Academic Research/Center for Environmental Remote Sensing/Research Institute of Disaster Medicine, Chiba University, along with his colleagues Fumitoshi Kawasaki from the Graduate School of Science and Engineering and Masanao Ohashi from the Center for Environmental Remote Sensing, developed a novel data assimilation technique designed for quantum annealing machines. "Our study introduces a novel quantum annealing approach to accelerate data assimilation, which is the main computational bottleneck for numerical weather predictions. With this algorithm, we successfully solved data assimilation on quantum annealers for the first time," explains Prof. Kotsuki. Their study has been published in the journal Nonlinear Processes in Geophysics on June 07, 2024.

In the study, the researchers focused on the four-dimensional variational data assimilation (4DVAR) method, one of the most widely used data assimilation methods in NWP systems. However, since 4DVAR is designed for classical computers, it cannot be directly used on quantum hardware. Prof. Kotsuki clarifies, "Unlike the conventional 4DVAR, which requires a cost function and its gradient, quantum annealers require only the cost function. However, the cost function must be represented by binary variables (0 or 1). Therefore, we reformulated the 4DVAR cost function, a quadratic unconstrained optimization (QUO) problem, into a quadratic unconstrained binary optimization (QUBO) problem, which quantum annealers can solve."

The researchers applied this QUBO approach to a series of 4DVAR experiments using a 40-variable Lorentz-96 model, which is a dynamical system commonly used to test data assimilation. They conducted the experiments using the D-Wave Advantage physical quantum annealer, or Phy-QA, and the Fixstars Amplify's simulated quantum annealer, or Sim-QA. Moreover, they tested the conventionally utilized quasi-Newton-based iterative approaches, using the Broyden-Fletcher-Goldfarb-Shanno formula, in solving linear and nonlinear QUO problems and compared their performance to that of quantum annealers.

The results revealed that quantum annealers produced analysis with comparable accuracy to conventional quasi-Newton-based approaches but in a fraction of the time they took. The D-Wave's Phy-QA required less than 0.05 seconds for computation, much faster than conventional approaches. However, it also exhibited slightly larger root mean square errors, which the researchers attributed to the inherent stochastic quantum effects. To address this, they found that reading out multiple solutions from the quantum annealer improved stability and accuracy. They also noted that the scaling factor for quantum data assimilation, which is important for regulating the analysis accuracy, was different for the D-Wave Phy-QA and the Sim-QA, owing to the stochastic quantum effects associated with the former annealer.

These findings signify the role of quantum computers in reducing the computational cost of data assimilation. "Our approach could revolutionize future NWP systems, enabling a deeper understanding and improved predictions with much less computational time. In addition, it has the potential to advance the practical applications of quantum annealers in solving complex optimization problems in earth science," remarks Prof. Kotsuki.

Overall, the proposed innovative method holds great promise for inspiring future applications of quantum computers in advancing data assimilation, potentially leading to more accurate weather predictions.

About Professor Shunji Kotsuki

Dr. Shunji Kotsuki is currently a Professor at the Institute for Advanced Academic Research (IAAR), Chiba University, leading "Environmental Prediction Science." He received his B.S. (2009), M.S. (2011), and Ph.D. (2013) degrees in civil engineering from Kyoto University. He has over 40 publications and received over 500 citations. Dr. Kotsuki is a leading scientist in data assimilation, deep learning numerical weather prediction with over ten years of research experience in the development of the global atmospheric data assimilation system (a.k.a. NICAM-LETKF). His research interests include data assimilation mathematics, model parameter estimation, observation diagnosis including impact estimates, satellite data analysis, hydrological modeling, and atmospheric and hydrological disaster predictions. He is currently the project manager for Goal 8 of Japan's Moonshot Program, where he leads an interdisciplinary research team. This team includes experts in meteorology, disaster mathematics, information science, computer vision, ethics, and legal studies, all working together to achieve a weather-controlled society.

Nonlinear Processes in Geophysics

Computational simulation/modeling

Not applicable

Quantum Data Assimilation: A New Approach to Solve Data Assimilation on Quantum Annealers

7-Jun-2024

The authors have no competing interests to declare.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Quantum data assimilation: A quantum leap in weather prediction - EurekAlert

Technology firms, both public and private, have been working hard to develop quantum computing technologies for decades. The reasons for that are straightforward. Quantum machines, which harness the quantum mechanics undergirding subatomic particles, have a number of advantages over classical computers. Portfolio optimization and climate predictive algorithms that improve with more complexity are better handled by quantum computers.

U.S. equities markets have surged with the rise of generative artificial intelligence (AI) and its potential to create enormous efficiencies and profits for firms across various industries. While AI has brought quantum computing back into the spotlight, a lack of practical ways to scale these complex products has severely dented the performance of pure-play quantum computing stocks, such as IonQ (NYSE:IONQ) and Rigetti Computing (NASDAQ:RGTI).

Fortunately, not every public company invested in quantum computing has seen doom and gloom. Below are the three best quantum computing stocks investors should buy in June.

Source: shutterstock.com/LCV

International Business Machines (NYSE:IBM) is a legacy American technology business. It has its hands in everything from cloud infrastructure, artificial intelligence, and technology consulting services to quantum computers.

The firm committed to developing quantum computing technologies in the early 2000s and tends to publish new findings in the burgeoning field frequently. In December 2023, IBM released a new quantum chip system, Quantum System Two, that leverages the firms Heron processor, which has 133 qubits. Qubits are analogous to bytes on a classical computer. But instead of being confined to states of 0s and 1s, qubits, by way of superposition, can assume both states at the same time.

Moreover, what makes Quantum System Two particularly innovative is its use of both quantum and classical computing technologies. In a press release, IBM states, It combines scalable cryogenic infrastructure and classical runtime servers with modular qubit control electronics. IBM believes the combination of quantum computation and communication with classical computing resources can create a scalable quantum machine.

IBMs innovations in quantum computing technologies as well as AI has not gone unnoticed either. Shares have risen 31.3% over the past 12 months. The computing giants relatively cheap valuation coupled with its exposure to novel, high-growth fields could boost the value of its shares in the long-term.

Source: sdx15 / Shutterstock.com

Investors have given Nvidia (NASDAQ:NVDA) attention and praise over the past 12 months due to its critical role in AI computing technologies. The chipmakers advanced GPUs, including the H100 and H200 processors, are some of the most coveted chips on the market. The new Blackwell chips, coming to the market in the second half of 2024, bring to the table even better performance.

Though Nvidias prowess in the world of AI captures much of the headlines, the firm has already made inroads into the next stage of computing. In 2023, Nvidia announced a new quantum system in conjunction with startup Quantum Machines. It leverages what Nvidia calls the Grace Hoper Super Chip (GH200) as well as the chipmaker advanced CUDA Quantum (CUDA-Q) developer software.

In 2024, Nvidia released its Quantum Cloud platform, which allows users to build and test quantum computing algorithms in the cloud. The chipmakers GPUs and its open-source CUDA platform will likely be essential to scaling up the quantum computing space.

Nvidias share price has surged 214.2% over the past 12 months.

Source: Bartlomiej K. Wroblewski / Shutterstock.com

Quantum computers are complex machines that require all kinds of components. Furthermore, it is vital for quantum systems to operate at extremely low temperatures in order to operate efficiently.

FormFactor (NASDAQ:FORM) specializes in developing cryogenic systems or systems that are meant to deal with low temperatures. Everything from wafer testing probes to low-vibration probe stations as well as sophisticated refrigerators call cryostats, FormFactor provides. Also, the firms analytical probe tools are useful for developing advanced chips, such as NAND flash memory.

With quantum computing systems and advanced memory chips in greater demand these days, FormFactor could see revenues and earnings rise in the near and medium terms. FormFactors share price has surged 77.5% over the past 12 months, underscoring that investors are taking notice of the companys long-term value.

At the beginning of May, FormFactor released first quarter results for fiscal year 2024 and topped revenue estimates while EPS came in line with market expectations. The firm expects strong demand for advanced memory chips, such as DRAM, will help propel revenue growth in the following quarters.

On the date of publication, Tyrik Torresdid not have (either directly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

Tyrik Torres has been studying and participating in financial markets since he was in college, and he has particular passion for helping people understand complex systems. His areas of expertise are semiconductor and enterprise software equities. He has work experience in both investing (public and private markets) and investment banking.

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The 3 Best Quantum Computing Stocks to Buy in June 2024 - InvestorPlace

Capitalize on the synergy between AI and quantum with these millionaire-maker quantum computing stocks

Quantum computing, with its unparalleled data processing speed, has the potential to usher in a new era in tech. Moreover, the synergy between AI and quantum computing will elevate millionaire-maker quantum computing stocks to new heights. The industry is likely to achieve these kinds of returns as a result of becoming a new critical technology at the center of data processing and connection.

Moreover, quantum tech is leaving traditional silicon-based systems in the dust. Beyond this, some of the most influential companies in the tech world are driving the industry, promising exciting opportunities for investors. However, backing the right horses in the race for quantum supremacy is important to maximize your upside potential.

That said, here are three millionaire-maker quantum computing stocks worth investing in for the long haul. Thats because the industry still operates on the fringes of science and technology, making it a long-term play for those looking for generous returns.

IonQ (NYSE:IONQ) is the top pure-play quantum computing stock, perhaps the most promising among its peers. It has made some impressive strides of late, achieving ion stability for an hour, a feat that far comfortably outpaces its competition. Its promise is reflected in its recent strong financial performance. It recently reported its first-quarter (Q1) results, where sales soared 77.2% on a year-over-year (YOY) basis to $7.6 million. Additionally, its loss of 19 cents per share beat expectations by six cents. For the full year, it expects sales between $37 million and $41 million, over 70% growth at the mid-point on a YOY basis. Moreover, the company recently partnered with Oak Ridge National Laboratory (ORNL) to leverage quantum technology to modernize the power grid. This stellar partnership, along with others, demonstrates IonQs ability to innovate and expand its applications, offering healthy long-term upside ahead for its investors.

Source: Shutterstock

Investing in quantum computing can be complicated and speculative at the same time. To simplify the process, the Defiance Quantum ETF (NYSEARCA:QTUM) works best, with it investing in AI stocks to provide a balanced cushion.

The QTUM ETF offers investors exposure to some of the leading global businesses in transformative technologies such as machine learning, quantum computing, and cloud platforms. It holds investments in 70 different stocks, with its top 10 holdings representing just 20% of its $252 million net assets. Hence, its holdings are highly diversified, with an expense ratio of just 0.40%. Some of the companies in its investment portfolio are MicroStrategy(NASDAQ:MSTR),Nvidia(NASDAQ:NVDA), andMKS Instruments(NASDAQ:MKSI) to name a few.

Moreover, QTUM stock has been a smashing success for its investors in the past five years, generating a total return of over 175%, 361% higher than the median of all ETFs. In the past year alone, its up 30% and is positioned for healthy long-term gains.

Source: The Art of Pics / Shutterstock.com

Microsoft (NASDAQ:MSFT), a tech giant, has tentacles in virtually every major tech vertical, and quantum computing is no different. The AI revolution took Microsofts business up a notch or two last year, and it is eyeing quantum computing as the next frontier. Its partnership with quantum computing pure-play Quantinuum could be a breakthrough for the entire sector. According to a recent statement from one of Microsofts executives, the company has made massive progress in reducing qubit error rates, which is critical for commercializing quantum technology. Its qubit-virtualization system applied to Quantinuums ion-trap hardware, led to more than 14,000 error-free experiments. The breakthrough will set the stage for Quantinuums Helios H-Series quantum computer by next year. Moreover, the collaboration between the two tech companies aims to go from 100 reliable logical qubits to a whopping 1,000 qubits. If these lofty plans come to fruition, I wont be surprised if MSFT stock goes on another monumental run like last year.

On thedate of publication, Muslim Farooque did not have (eitherdirectly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines

Muslim Farooque is a keen investor and an optimist at heart. A life-long gamer and tech enthusiast, he has a particular affinity for analyzing technology stocks. Muslim holds a bachelors of science degree in applied accounting from Oxford Brookes University.

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3 Quantum Computing Stocks to Turn $100000 Into $1 Million: June Edition - InvestorPlace