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Quantum is set to be the next frontier of computing. But it is an immense undertaking that has yet to be fully realized; researchers continue to face challenges in a multitude of areas including error correction, scalability, cost and hardware and software complex and capable enough to handle extremely high-performance simulations.

To support and accelerate scientific exploration into this next phase of computing, Nvidia today launched Quantum Cloud, which allows users to build and test new quantum apps and algorithms in the cloud.

The microservice is based on Nvidias open-source CUDA-Q quantum computing platform, which the company says is used by three-quarters of the companies deploying quantum processing units (QPUs).

Quantum computing presents the next revolutionary frontier of computing, said Tim Costa, Nvidias director of HPC and quantum computing. Its going to require the worlds most brilliant minds to bring this future one step closer.

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The new Nvidia Quantum Cloud is intended to accelerate scientific exploration, the company says. Its capabilities include:

Nvidia Quantum Cloud intends to break down the barriers to explore this transformative technology, said Costa. The goal is to help every scientist in the world harness the power of quantum computing and bring their ideas closer to reality.

Nvidia says it has 160 partners in quantum computing and many top tech companies and quantum companies are incorporating Quantum Cloud into their services including Google Cloud, Microsoft Azure, Oracle Cloud, IonQ, IQM Quantum Computers, OQC, ORCA Computing, qBraid and Quantinuum.

At HSBC, for instance, researchers designed a quantum machine learning (ML) application that can detect digital payment fraud. This simulated a whopping 165 qubits on Nvidia GPUs typically, projects dont extend beyond 40 of these fundamental calculating units.

The researchers were able to overcome challenges with scale thanks to ML techniques implemented with CUDA Quantum and cuTensorNet software on Nvidia GPUs, according to the company.

Nvidia is further working with nearly two dozen universities to help train the next generation of computer scientists. This involves designing curricula and teaching materials around CUDA Quantum. The company also recently co-sponsored the quantum hackathon QHack, whose winning team from Indian company Qkrishi used CUDA Quantum to develop an algorithm to simulate a material critical to designing better batteries.

Bridging the divide between traditional computers and quantum systems is essential to the future of computing, Theresa Mayer, VP for research at Carnegie Mellon University, said in a statement. Nvidias partnership with her school and others aims to help students and researchers navigate and excel in this emerging hybrid environment.

Nvidias CUDA Quantum and other systems are being used for a multitude of other quantum efforts, as well, the company reports.

These include:

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Beyond AI: How Nvidia is helping scale quantum computing - VentureBeat

Machine learning is used for prediction, and in health care we want to predict if somebody has a disease or not, he said. If you give enough examples of images that have pneumonia and not pneumonia, because there are two cases, this is called binary classification.

Tayur and a team of researchers studied a technique called support vector machine for classification using quantum-inspired computing, then compared it to other methodsin a recent paper.

We showed that it is pretty competitive, he said. It makes fewer mistakes and it takes less time.

Tayur founded theQuantum Technologies Group(opens in new window) at CMU to better understand and apply quantum computing methods to industries such as health care.

People are always looking for more efficient ways of solving problems and novel methods and technologies to tackle it, he said.

In the mid-20th century, scientists who led the first quantum revolution changed the world with innovations such as the transistor, laser and atomic clock. While hardware to compute using qubits is still in development, simulators are capable of tackling problems of realistic size with specially tailored algorithms, which is why this approach is known as quantum-inspired computing.

Assuming that qubit devices of larger size and lower errors are going to be developed, we can simulate them on a regular computer right now, Tayur said.

These technologies, however, are still at the leading edge of considerations when it comes to the application of artificial intelligence in health care.

In order to do so, the industry has four challenges ahead of it, as Tayurdescribed in research(opens in new window) with Tinglong Dai of Johns Hopkins Carey Business School: physician buy-in, patient acceptance, provider investment and payer support.

To achieve these goals, any AI applied to health care systems should consider how physicians will integrate it into their practices, and then review how patients perceive the role of AI in health care delivery.

We wrote that paper in 2022, but things havent changed that much. Its not just about building a better mousetrap, its about getting people to use that mousetrap, he said, referencinga long-held business idea(opens in new window) that success comes from simply designing the best product.

First, as an example, Tayur explained thatmore than 500 medical AI devices(opens in new window) have been approved by the FDA, but wide adoption of these technologies is still just beginning, in part because of the state of the health care industry and where financial incentives lie.

Having a good product is necessary, but its not sufficient, he said. You still need to figure out how people are going to use it, and who is going to pay for it.

Second, a major consideration in health care is liability. When it comes to devices, a company might encourage doctors to adopt them, but what happens if the device gives a faulty diagnosis or a doctor gives an incorrect interpretation of the data from the device?

In the paper, we basically talk about the fact that you have to figure out the business case, both risk and reward, along with training and upfront investments in adopting the technology, he said.

In applying elements of AI and quantum computing to health care, Tayur said while at least some progress has been made, there is still a long way to go.

Many times what happens is a lot of the AI in health care is derived by scientists and research physicians, he said. What they need is a business person who is less enamored by the mousetrap and more sensitive to the patient journey and commercial viability.

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Machine Learning, Quantum Computing Can Transform Health Care, Including Diagnosing Pneumonia - Carnegie Mellon University

These quantum computing stocks are fundamentally sound

Source: Amin Van / Shutterstock.com

Quantum computing is an early stage, high-growth industry that is garnering a lot of attention. Growth forecast suggests that annual annual growth could continue above 35% past the year 2030. Therefore, early-stage quantum computing stocks have incredible potential.

Yet, many of those companies are also fundamentally unsound. Some of the names known today will undoubtedly fall by the wayside and dissolve. Thats why investors should direct their capital toward the most fundamentally sound quantum computing stocks: Such investments better protect investor capital while also exposing investors to continued future growth.

Fortunately, there are currently pure-play stocks within quantum computing that are fundamentally sound. Outside of them, investors will have to look to larger, diversified companies in order to chase quantum computing gains.

Source: Boykov / Shutterstock.com

FormFactor (NASDAQ:FORM) is one of the superior quantum computing stocks for investor consideration. It is also the closest thing to a pure-play quantum computing investment that is also fundamentally on strong footing.

FormFactor is first and foremost a semiconductor firm. The company also has a strong connection to the quantum computing industry. FormFactor sells cryogenic systems that are integral to the manufacture of quantum computers. The more the quantum computing industry develops the more in demand those cryogenic systems will be which should obviously propel shares higher.

The industry connection is paramount, but so too is the fact that the company is fundamentally sound. While revenues are currently relatively flat they, along with margins, were above the midpoint of the guidance range. That suggests fundamental soundness as does the fact that the company continues to produce net income overall. That is exceedingly rare across the quantum computing sector at this time.

The combination of those factors continues to make FormFactor among the most fundamentally sound quantum computing stocks available currently.

Source: shutterstock.com/LCV

IBM (NYSE:IBM) continues to do a lot in relation to quantum computing. The stock is already quite strong and has re-emerged as a force in the tech space.

Users who would like to access IBMs quantum computing facilities currently have to do so through its New York data center. However, IBM is scheduled to complete its EU data center located in Ehningen, Germany this year. Its completion will grant cloud access to quantum computing users across Europe. IBM is opening another quantum computing data center which is a strong indication of its belief and investment into the technology.

IBM currently has more than 10 utility scale Quantum systems dotted across the globe currently. The more it connects, the more power.

Greater power is the ultimate goal here. The current world demands access to greater volumes of data at higher speeds. Quantum computing promises to deliver on that goal. Thus, quantum computing connected with other technological advancements like AI should lead to improved analytics and big data which in turn leads to greater insights and better business decisions. IBM is a big part of that.

Source: achinthamb / Shutterstock.com

Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) is generally going to be considered a strong stock investment throughout the remainder of 2024. The companys recent AI slip up doesnt seem to be affecting share prices too much as they have started to rebound. Beyond that, the forecast remains bright.

Thats a general reason to consider investing in Google but we are discussing quantum computing. Google has made significant strides. The company opened a quantum computing campus back in 2021. The goal is to build an error corrected quantum computer at some point.

Googles goal is to build a computer boasting 1 million physical qubits. IBM released the first quantum computing system capable of 1,000 physical qubits and a 1,000 qubit chip at the end of 2023. Thus, if Google is to reach its goal it will have to do 1,000 times better than IBM has.

Google is a fundamentally sound firm with a serious investment in quantum computing technology. It represents a fine investment for those who seek to take advantage of future growth therein.

On the date of publication, Alex Sirois did 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.com Publishing Guidelines.

Alex Sirois is a freelance contributor to InvestorPlace whose personal stock investing style is focused on long-term, buy-and-hold, wealth-building stock picks. Having worked in several industries from e-commerce to translation to education and utilizing his MBA from George Washington University, he brings a diverse set of skills through which he filters his writing.

Original post:
QC's Finest: The 3 Most Fundamentally Sound Quantum Computing Stocks - InvestorPlace

BOSTON, March 18, 2024 /PRNewswire/ -- Quantum computing is pitched as enabling exponentially faster drug discovery, battery chemistry development, multi-variable logistics, vehicle autonomy, accurate asset pricing, and much more. In the last decade, the number of companies actively developing quantum computer hardware has quadrupled. Between 2022 and 2024, multiple funding rounds within the quantum computing market surpassed US$100 million were closed, and the transition from lab-based toys to commercial product began.

Competition is building in the quantum computing market, not only between different companies but between quantum computing technologies. The focus today has intensified on the need for logical or error-corrected qubits. The challenge ahead is to scale up hardware and increase qubit number while reducing errors as well as infrastructure demand no mean feat. Leaders today have between 1 and 50 logical qubits, thousands are likely needed to provide a meaningful advantage over classical computing alternatives.

The race to build a large-scale fault-tolerant quantum computer is underway, with increasing logicalqubit number key hurdles for hardware developers to overcome in the near term. However, many more challenges remain, such as reducing manipulation and read-out complexity and reducing infrastructure demands. As such, despite signs of early competitive advantage from some modalities, there is still a long way to go before a winner is crowned. Source: IDTechEx

Yet the quantum computing hardware market today has the unique property of seeing rapid growth in revenue generation despite remaining at a low technology readiness level. National laboratories and supercomputing centers are already investing in the installation of early-stage machines on premises, primarily for research but also to allow more local users the ability to 'pay to play'. This is, in part, a result of the intensifying governmental stake in the technology and its potential to provide significant economic and national security advantages in conjunction with quantum sensing and quantum communications. As a result, while multiple technical challenges remain, it appears that the race to commercial advantage could well be paved with gold for some. However, towards the end of the decade, as pressure mounts to deliver commercial value and return on investment some of those leading the charge today may not necessarily prove to be the true winners in the long term.

With so many competing quantum computing technologies across a fragmented landscape, determining which approaches are likely to dominate is essential in identifying opportunities within this exciting industry. IDTechEx's new report, "Quantum Computing Market 2024-2044: Technology, Trends, Players, Forecasts", covers the hardware that promises a revolutionary approach to solving the world's unmet challenges. Drawing on extensive primary and secondary research, including interviews with companies and attendance at multiple conferences, this report provides an in-depth evaluation of the competing quantum computing technologies: superconducting, silicon-spin, photonic, trapped-ion, neutral-atom, topological, diamond-defect and annealing.

These competing quantum computing technologies are compared by key benchmarks, including qubit number, coherence time, and fidelity. The scalability of whole computer systems is appraised incorporating hardware needs for qubits initialization, manipulation, and readout. This results in a twenty-year market forecast covering 2024-2044. The total addressable market for quantum computer use is converted to hardware sales over time, accounting for advancing capabilities and the cloud access business model. The entire hardware market is forecast to grow to US$800M by 2034. This growth will be driven by applications in pharmaceutical, chemical, aerospace, and finance, leading to increased installation of quantum computers into data centers, research institutes, and private networks alike. Revenue and volume forecasts are split into eight forecast lines for each methodology covered. Historic data on the number of quantum computer start-ups utilizing each methodology and the qubit milestones achieved are also included.

Key questions answered in this report include:

To find out more about the new IDTechEx report "Quantum Computing Market 2024-2044: Technology, Trends, Players, Forecasts", including downloadable sample pages, please visit http://www.IDTechEx.com/QuantumComputing.

For the full portfolio of market research available from IDTechEx, please visit http://www.IDTechEx.com.

About IDTechEx:

IDTechEx provides trusted independent research on emerging technologies and their markets.Since 1999, we have been helping our clients to understand new technologies, their supply chains, market requirements, opportunities and forecasts. For more information, contact[emailprotected]or visitwww.IDTechEx.com.

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SOURCE IDTechEx

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The Race to Build a Quantum Computer Is Paved With Gold - Says IDTechEx - PR Newswire

PALO ALTO, Calif., March 18, 2024 /PRNewswire/ --QC Ware, makers of Promethium, a quantum-inspired, molecular discovery platform, announced today it is leveragingNVIDIA Quantum Cloud to accelerate drug discovery by providing AI platforms with the ability to generate highly accurate training data on large, complex molecules faster than ever before, aiming to redefine the landscape of in silico molecular simulation. These are critical problems that will be accelerated by future quantum computers, but today are best solved by advanced methods on GPUs. This will enable molecular AI platforms to train better ML models, ultimately helping pharmaceutical companies find quality drug candidates more quickly.

NVIDIA Quantum Cloud is a microservice that lets users for the first time build and test in the cloud new quantum algorithms and applications, including powerful simulators and tools for hybrid quantum-classical programming.

Promethium to Empower ML Models for Drug Discovery Using NVIDIA Quantum Cloud

"Promethium is helping steer the future of drug discovery and this latest work with NVIDIA signifies our commitment to advancing pharmaceutical research and underscores the importance of technological innovation in the quest for groundbreaking solutions to some of the most challenging medicinal problems of modern times," said Paul Baines, VP of Product & Engineering, at QC Ware.

ML models are already playing a large role in drug discovery, accelerating the ability to find new and promising candidates for clinical trials over historical methods. With an abundance of these ML models coming into play, one of the main challenges that research leaders face is determining the quality of the models they are using. Typically, the best ML models are trained on the best data. This has created a need for large amounts of extremely high-quality data.

The molecular data that currently exists is limited in scale, scope, and application. To build the best general-purpose ML model, or to customize an ML model for a specific purpose, lots of data must be generated and fast. Promethium is on a journey to generate the highest-quality data faster than it's ever been done. AI platforms for drug discovery are already taking advantage of these benefits. One example is a venture-backed start-up using Promethium to create highly accurate data, very quickly, and at scale.

"For representative systems we currently run today, Promethium is 30 times faster than our current toolsets," says the startup's CTO. "This means that we can generate high-quality training data faster, leading to extremely accurate ML models for researchers to use. The result? Truly transformative ML models that will unlock massive amounts of value for pharmaceutical companies."

Additionally, this type of data has yet to be created at scale for larger molecules. This was primarily due to how computationally intensive it was to create accurate data for molecular modeling. This limitation kept ML models from accurately predicting properties of larger molecules. Promethium's breakthrough software, combined with NVIDIA's state-of-the-art GPUs and cloud scalability, has unlocked the ability to create training data for large, complex molecules that will fuel the advanced capabilities of innovative AI platforms.

"Quantum computing has the potential to transform drug discovery," said Tim Costa, Director of HPC and Quantum at NVIDIA. "Promethium is using NVIDIA Quantum Cloud to rapidly generate training data on large, complex molecules, enabling better machine learning models that will help pharmaceutical companies find drug candidates more quickly."

Leaders in the pharmaceutical industry are already taking advantage of AI as a force multiplier in the drug discovery race. Not only is it helping them hone in on more promising candidates more quickly, but it's also creating a new benchmark for efficiency in R&D spend. Companies that are able to wield this technology effectively will be poised to achieve or better maintain industry dominance in the new age of drug discovery.

About QC Ware

Promethium is a quantum chemistry SaaS platform developed by QC Ware, a quantum and classical computing software and services company focused on delivering enterprise value through cutting-edge computational technology. With specialization in machine learning and chemistry simulation applications, QC Ware develops software for both near-term quantum and state-of-the-art classical computing hardware. QC Ware's team is composed of some of the industry's foremost experts in quantum and classical computing. QC Ware is headquartered in Palo Alto, California, and supports its European customers through its subsidiary in Paris and customers in Asia through its business development office in Tokyo, Japan.

Media Contact:[emailprotected] 317-525-5882

SOURCE QC Ware Corp.

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Accelerating the Development of New Molecules - Promethium to Empower ML Models for Drug Discovery Using ... - PR Newswire