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Quantum computing is expected to revolutionize a broad swathe of industries. But as the technology edges closer to commercialization, what will the earliest use cases be?

Quantum computing is still a long way from going mainstream. The industry had some significant breakthroughs in 2021 though, not least IBMs unveiling of the first processor to cross the 100-qubit mark. But the technology is still experimental, and has yet to demonstrate its usefulness for solving real-world problems.

That milestone might not be so far off, though. Most quantum computing companies are aiming to produce fault-tolerant devices by 2030, which many see as the inflection point that will usher in the era of practical quantum computing.

Quantum computers will not be general-purpose machines, though. They will be able to solve some calculations that are completely intractable for current computers and dramatically speed up processing for others. But many of the things they excel at are niche problems, and they will not replace conventional computers for the vast majority of tasks.

That means the ability to benefit from this revolution will be highly uneven, which prompted analysts at McKinsey to investigate who the early winners could be in a new report. They identified the pharmaceutical, chemical, automotive, and financial industries as those with the most promising near-term use cases.

The authors take care to point out that making predictions about quantum computing is hard because many fundamental questions remain unanswered; for instance, the relative importance of the quantity and quality of qubits or whether there can be practical uses for early devices before they achieve fault tolerance.

Its also important to note that there are currently fewer than 100 quantum algorithms that exhibit a quantum speed-up, the extent of which can vary considerably. That means the first and foremost question for business leaders is whether a quantum solution even exists for their problem.

But for some industries the benefits look clearer than others. For drug makers, the technology holds the promise of streamlining the industrys long and incredibly expensive research and development process; the average drug takes 10 years and $2 billion to develop.

Quantum simulations could predict how proteins fold and tease out the properties of small molecules that could help produce new treatments. Once promising candidates have been found, quantum computers could also help optimize critical attributes like absorption and solubility.

Beyond research and development, quantum computers could also help companies optimize the clinical trials used to validate new drugs, for instance by helping identify and group participants or selecting trial sites.

Quantum simulation could also prove a powerful tool in the chemical industry, according to the report. Todays chemists use computer-aided design tools that rely on approximations of molecular behavior and properties, but enabling full quantum mechanical simulations of molecules will dramatically expand their capabilities.

This could cut out the many rounds of trial-and-error lab experiments normally required to develop new products, instead relying on simulations to do the heavy lifting, with limited lab-based validation to confirm the results.

Quantum computers could also help to optimize the formulations used in all kinds of productsfrom detergents to paintsby modeling the complex molecular-level processes that govern their action.

For both the pharmaceutical and chemical industries, its not just the design of new products that could be impacted. Quantum computers could also help improve their production processes by helping researchers better understand the reaction mechanisms used to create drugs and chemicals, design new catalysts, or fine-tune conditions to optimize yields.

In the automotive industry, the technology could significantly boost prototyping and testing capabilities. Better simulation of everything from aerodynamic properties to thermodynamic behavior will reduce the cost of prototyping and lead to better designs. It could even make virtual testing possible, reducing the number of test vehicles required.

As carmakers look for greener ways to fuel their vehicles, quantum simulations could also contribute to finding new materials and better designs for hydrogen fuel cells and batteries. But the biggest impact could be on the day-to-day logistics involved in running a major automotive company.

Supply chain disruptions cost the industry about $15 billion a year, but quantum computers could simulate and optimize the sprawling global networks companies rely on to significantly reduce these headaches. They could also help fine-tune assembly line schedules to reduce inefficiencies and even optimize the movements of multi-robot teams as they put cars together.

Quantum computings impact on the financial industry will take longer to be felt, according to the reports authors, but with the huge sums at stake its worth taking seriously. The technology could prove invaluable in modeling the behavior of large and complex portfolios to come up with better investment strategies. Similar approaches could also help optimize loan portfolios to reduce risk, which could allow lenders lower interest rates or free up capital.

How much of this comes to pass depends heavily on the future trajectory of quantum technology. Despite significant progress, there are still many unknowns, and plenty of scope for timelines to slip. Nonetheless, the potential of this new technology is starting to come into focus, and it seems that business leaders in those industries most susceptible to disruption would do well to start making plans.

Image Credit: Pete LinforthfromPixabay

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These Will Be the Earliest Use Cases for Quantum Computers - Singularity Hub

The world of quantum computing has so many terms, starting with Qubit, QPU, and superposition, to entanglement, trapping ions, and photons, but the heart of quantum computation lies in Qubits. Traditionally, data is encoded in bits, where each bit has a value of 0 or 1. However, quantum computers encode data in Qubits, where each Qubit can be encoded as either 0 or 1 or in a linear combination of the two states. The phenomenon is called superposition. Researchers of DOE Lawrence Berkeley National Laboratory and the University of California, Berkeley, are trying to find the ideal version of Qubits by exploring properties like superposition and entanglement.

Unfortunately, Qubits are sensitive to their environment. As a result, they cant maintain their state for long periods, so they cant be used to store information long-term, and no one can retrieve the information further. In addition, quantum systems are characterised by a lot of noise, which results in a low coherence time (the time it takes a system to maintain a condition) and errors.

To assist in the development of Qubits, the DOE Lawrence Berkeley National Laboratory and the University of California, Berkeley are supporting a number of research projects.

The most advanced technology for Qubits is superconducting Qubits. Using a sandwich of metal, insulator, and metal, called a Josephson junction, can transform materials into superconductors in which electricity flows without loss. This is done by drastically lowering their temperatures. As a result, coherent electron pairs move through the material as single particles. Due to this movement, quantum states are more stable than conventional materials.

I Siddiqi and his colleagues, researchers at the University of California, inserted a thin insulating barrier between two superconductors in a quantum bit to scale up superconducting Qubits. The barrier affects the flow of electrons, making it possible to control their energy levels. In addition, it is possible to increase the coherence time by making this junction as consistent and small as possible.

Diamonds can develop nitrogen-vacancy centres by adding nitrogen to a place where a carbon atom would normally exist. To make these defect patterns, researchers created a stencil that was just two nanometers long, using the Center for Functional Nanomaterials. In this way, the coherence time of these Qubits was increased, and it was easier to entangle them.

Giulia Galli and her team, a group of researchers from NERSC and Berkeley Lab, using theory, predicted how to strain aluminium nitride in the right way to form Qubits. As nitrogen vacancies occur naturally in aluminium nitride, scientists should control electron spin in it just like they can in diamonds. David D Aschaloms team, the researchers at the Institute for Molecular Engineering, The University of Chicago, also discovered certain defects in silicon carbide that have coherence times comparable to or longer than nitrogen-vacancy centres in diamonds.

By using this method, custom materials can be created molecule by molecule. Danna E Freedman, a researcher at the Department of Chemistry, Northwestern University, and her team tailored the metals and molecules bound to create an environment with very little nuclear spin. The magnetic noise created by atoms containing nuclear spin makes it difficult to maintain and control the spin of electrons. They have achieved a one millisecond coherence time in molecules that contain the metal vanadium after testing different solvents, temperatures, and ions/molecules attached to the metal.

It is truly exciting to think that by using quantum simulations to view materials, it can be finally possible to develop technologically relevant technologies and materials that can completely transform the way of computations.

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Developing Qubits, the heart of a quantum computer - Analytics India Magazine

The University of Michigan has formed a collaboration with Michigan State and Purdue universities to study quantum science and technology, drawing together expertise and resources to advance the field.

The three universities are partnering to form the Midwest Quantum Collaboratory, or MQC, to find grand new challenges we can work on jointly, based on the increased breadth and diversity of scientists in the collaboration, said Mack Kira, professor of electrical engineering and computer science at the College of Engineering and inaugural director of the collaboration.

U-M researchers call quantum effects the DNA of so many phenomena people encounter in their everyday lives, ranging from electronics to chemical reactions to the study of light waves and everything they collectively produce.

We scientists are now in a position to start combining these quantum building blocks to quantum applications that have never existed, said Kira, also a professor of physics in LSA. It is absolutely clear that any such breakthrough will happen only through a broad, diverse and interdisciplinary research effort. MQC has been formed also to build scientific diversity and critical mass needed to address the next steps in quantum science and technology.

Collaborators at U-M include Steven Cundiff, professor of physics and of electrical engineering and computer science. Cundiffs research group uses ultrafast optics to study semiconductors, semiconductor nanostructures and atomic vapors.

The main goal of the MQC is to create synergy between the research programs at these three universities, to foster interactions and collaborations between researchers in quantum science, he said.

Each university will bring unique expertise in quantum science to the collaboration. Researchers at U-M will lead research about the quantum efforts of complex quantum systems, such as photonics, or the study of light, in different semiconductors. This kind of study could inform how to make semiconductor-based computing, lighting, radar or communications millions of times faster and billions of times more energy efficient, Kira said.

Similar breakthrough potential resides in developing algorithms, chemical reactions, solar-power, magnetism, conductivity or atomic metrology to run on emergent quantum phenomena, he said.

The MQC will be a virtual institute, with in-person activities such as seminars and workshops split equally among the three universities, Cundiff said.

In the first year, MQC will launch a seminar series and virtual mini-workshops focused on specific research topics, and will conduct a larger in-person workshop. The collaboration hopes fostering connections between scientists will lead to new capabilities, positioning the MQC to be competitive for large center-level funding opportunities.

We know collaboration is key to driving innovation, especially for quantum, said David Stewart, managing director of the Purdue Quantum Science and Engineering Institute. The MQC will not only provide students with scientific training, but also develop their interpersonal skills so they will be ready to contribute to a currently shorthanded quantum workforce.

The MQC also will promote development of the quantum workforce by starting a seminar series or journal club for only students and postdocs, and encouraging research interaction across the three universities.

MQC also provides companies with interest in quantum computing with great opportunities for collaboration with faculty and students across broad spectrums of quantum computing with the collaborative expertise spanning the three institutions, said Angela Wilson, director of the MSU Center for Quantum Computing, Science and Engineering.

Additionally, bringing together three of our nations largest universities and three of the largest quantum computing efforts provides potential employers with a great source of interns and potential employees encompassing a broad range of quantum computing.

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UM part of collaboration to study quantum science, technology | The University Record - The University Record

People often look at technology as some kind of a monolith, but the thing about that is that it does not reflect the reality on the ground. Technology is vast and varied, and there are specific kinds of tech that might be a great deal more life changing than others. We are going to discuss ten of the most prominent tech trends out there right now that are liable to change the world as we know it through their innovation.1. Quantum Computing Chart via:Statista.

The increase in the computing power of various devices has been exponential. For example, modern smartphones would have seemed like high tech supercomputers not too long ago. Quantum computing might enable this exponential growth in computing power to continue for many more decades in the future.

More and more erstwhile mundane items are being connected to the internet, and this has led to the rise of the Internet of Things. With smart homes and factories quickly starting to be adopted, its not unlikely that the IoT will comprise every single item we interact with on a regular basis! While this is not necessarily a good thing, its definitely an exciting development.

Read next:The Biggest Cyber Security Trends That We Can Expect To Encounter In 2022

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These Trends Are Revolutionizing The Technology World - Digital Information World

As Artificial Intelligence (AI) and natural language processing advance, people often do not know if they are talking to a person or an AI-powered chatbot. What matters more than who or what is on the other side of the chat is the perceived humanness of the interaction.

With text-based bots becoming ubiquitous and AI-powered voice systems emerging, consumers of everything from shoes to insurance may find themselves talking to non-humans. Companies will have to decide when bots are appropriate and effective and when they are not. Researchers then developed a measurement for perceived humanness.

In the study, participants chatted with bots or human agents from companies and rated them on humanness. Sixty-three of 172 participants could not identify whether they were interacting with a human or a machine. But whether the interaction featured AI or not, higher scores of perceived humanness led to greater consumer trust in the companies.

If people felt like if it was humaneither with really good AI or with a real personthen they felt like the organisation was investing in the relationship. People think that the company is trying to create good interaction and the company put some time or resources into this, and therefore they trust the organisation.

Tom Kelleher, Ph.D., Advertising Professor, College of Journalism and Communications, University of Florida

Researchers started studying how language affects customer trust more than a decade ago when blogging culture introduced a conversational approach to the stuffy, stilted language businesses tended to bludgeon their customers with.

Companies noticed that as jargon waned, consumer trust, satisfaction and commitment grew. The new study shows that the same holds true with chatbots and other online interactions, and can be applied to bots and humans alike.

As AI-powered interfaces blossom, even expanding to include animated avatars that look human, ethical issues will follow. Should companies disclose when customers are interacting with a non-human agent? What if the helper is a hybrid: A person assisted by AI? Are there areas where consumers will not accept bots, such as health care, or situations where they might prefer a non-human?

If Im just trying to get an insurance quote, I would almost rather put something into an app than have to make small talk about the weather. But later on, if my house floods, Im going to want to talk to a real person. As the metaverse evolves, understanding when to employ AI and when to employ real people will be an increasingly important business decision, Kelleher said.

As reported by OpenGov Asia, a new report showed that Artificial Intelligence (AI) has reached a critical turning point in its evolution. Substantial advances in language processing, computer vision and pattern recognition mean that AI is touching peoples lives dailyfrom helping people to choose a movie to aid in medical diagnoses.

With that success, however, comes a renewed urgency to understand and mitigate the risks and downsides of AI-driven systems, such as algorithmic discrimination or the use of AI for deliberate deception. Computer scientists must work with experts in the social sciences and law to assure that the pitfalls of AI are minimised.

The report Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report aims to monitor the progress of AI and guide its future development. This new report, the second to be released by the AI100 project, assesses developments in AI between 2016 and 2021.

In terms of AI advances, the panel noted substantial progress across subfields of AI, including speech and language processing, computer vision and other areas. Much of this progress has been driven by advances in machine learning techniques, particularly deep learning systems, which have leapt in recent years from the academic setting to everyday applications.

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3 Phases on the Journey to Multicloud OpenGov Asia - OpenGov Asia