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NEW YORK, June 20, 2023 /PRNewswire/ -- Thequantum computing market size is expected to grow by USD 9,013.68 million from 2022 to 2027, progressing at a CAGR of18.84% as per the latest Technavio market research report.North America is estimated to account for38% of the market's overall growth. A major factor influencing the market growth is thepresence of a substantial number of US-based customers. For instance, amain vendor of quantum computers, D-Wave, which is headquartered in Canada, has sold quantum computing machines to major US-based clients such as Lockheed Martin, Google, NASA, and Temporal Defense Systems. Furthermore, suchfirms have collaborations with D-Wave to upgrade to the latest machine once it has been developed. Additionally,these clients have high economies of scale and, therefore, have the finances and resources to adopt these technologies at a much faster pace compared to other regions.Hence, such factors influence the growth of the regional market during the forecast period.For more insights on the market share of various regions-Downloadsample report in MINUTES

Quantum Computing Market: Increasing Expenditure by Stakeholders to drive growth

The growing utilization of quantum cryptography, which is a technique for secure code-writing and solving is a major driver for the market growth.Quantum cryptography offers the highest level of security for transmitting even the most critical data. With the advent of quantum computers, vast amounts of encrypted data can be processed at incredibly high speeds.

Moreover,quantum computing can decrypt encrypted data into plain text in a matter of seconds, while classical computers might take years to do so. Thedecryption process is achieved by increasing the length of keys with more bits. This provides heightened security butthere is a concern that hackers may also use quantum computers to decrypt sensitive information, which has prompted many governments to invest millions of dollars in developing quantum computers with top-notch security features. Hence, such factors drive the market growth during the forecast period.

Quantum Computing Market: Growth Of AI And Machine Learning

The growth of AI and machine learning is an emerging trend shaping market growth.AI is a branch of science, which generallydeals with computers, machines, software, and computer-operated robots to think intelligently to find solutions for complex problems in a manner that is like how a human brain thinks. Also, machine learning is a type of AI that allows computers to self-learn.

Additionally,AI and machine learning will be some of the biggest applications of quantum computers, where AIrequires fast processors to work, and the development of quantum computing processor chips will be used in AI applications. This is because theseprocessors work at high speeds to compute data efficiently. Hence, such trends fuel the market growth during the forecast period.

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Some of the key Quantum Computing Market Players:

The quantum computing market isfragmentedand the vendors are deploying organic and inorganic growth strategies to compete in the market.

Some of the key market players are1QB Information Technologies Inc., Alibaba Group Holding Ltd., Alphabet Inc., Amazon.com Inc., Anyon Systems Inc., Atos SE, D-Wave Quantum Inc., Honeywell International Inc., ID Quantique SA, International Business Machines Corp., IonQ Inc., Microsoft Corp., QC Ware, QRA Corp., Quantica Computacao, Quantinuum Ltd., Quantum Circuits Inc., Qubitekk Inc., Rigetti and Co. LLC, and Intel Corp.

Quantum Computing Market: Segmentation Analysis

This report extensively coversmarket segmentation by deployment (cloud and on-premise), end-user (aerospace and defense, government, IT and telecom, and others), and geography (North America, APAC, Europe, South America, and Middle East and Africa).

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Quantum Computing Market Scope

Report Coverage

Details

Base year

2022

Historic period

2017-2021

Forecast period

2023-2027

Growth momentum & CAGR

Accelerate at a CAGR of 18.84%

Market growth 2023-2027

USD 9,013.68 million

Market structure

Fragmented

YoY growth 2022-2023 (%)

18.6

Regional analysis

North America, APAC, Europe, South America, and Middle East and Africa

Performing market contribution

North America at 38%

Key countries

US, China, Japan, India, and Germany

Competitive landscape

Leading Vendors, Market Positioning of Vendors, Competitive Strategies, and Industry Risks

Key companies profiled

1QB Information Technologies Inc., Alibaba Group Holding Ltd., Alphabet Inc., Amazon.com Inc., Anyon Systems Inc., Atos SE, D-Wave Quantum Inc., Honeywell International Inc., ID Quantique SA, International Business Machines Corp., IonQ Inc., Microsoft Corp., QC Ware, QRA Corp., Quantica Computacao, Quantinuum Ltd., Quantum Circuits Inc., Qubitekk Inc., Rigetti and Co. LLC, and Intel Corp.

Market dynamics

Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, and Market condition analysis for the forecast period.

Customization purview

If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized.

Table of Contents

1 Executive Summary

2 Market Landscape

3 Market Sizing

4 Historic Market Size

5 Five Forces Analysis

6 Market Segmentation by Deployment

7 Market Segmentation by End-user

8 Customer Landscape

9 Drivers, Challenges, and Trends

10 Vendor Landscape

11 Vendor Analysis

12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provide actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio's report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio's comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research Jesse Maida Media & Marketing Executive US: +1 844 364 1100 UK: +44 203 893 3200 Email:[emailprotected] Website:www.technavio.com

SOURCE Technavio

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Quantum Computing Market size to grow by USD 9,013.68 million ... - PR Newswire

White had appeared after former Australian of the Year, quantum computing expert Michelle Simmons. She explained how she has made the transition from world-leading scientist, to the CEO of a company that is competing head-to-head with some of the biggest tech firms on the planet.

Richard White says his company could wash its own face from the start.Peter Rae

Simmons has already taken a year to close a $130 million funding round, but said there was good news on that front around the corner. However, the evident difficulties in prizing open investors wallets has not dimmed the ambition of her vision to produce a broadly useful quantum computer by the 2030s.

Simmons was able to explain lucidly why she thinks her relatively small Sydney-based company can beat the likes of Microsoft, Google and IBM to a great prize, and it is this kind of dizzying ambition that Australian governments will be desperate to latch on to, as the resources boom fades into history.

Simmons believes they have settled on the correct materials to base a quantum computer on, have the in-house manufacturing expertise that doesnt come naturally to software giants, and has a significant advantage through its mix of corporate and government-backing.

We knew it was a deep tech play, weve kept the company small and focused and nimble, and basically we are literally gunning to get the prize, Simmons said.

It is a highly competitive field, and theres this question of if it is going to be one approach that takes everything, and my personal view is that it is.

The point is that, while we may be publishing many articles about the tech wreck and start-up failures on our pages this year, market cycles will not make or break the best companies.

One of Australias unicorn start-up founders, Luke Anear of SafetyCulture, summed this up on a later panel, when he spoke about what had made his company stand out in the first place.

In 2010 to 2012, when I was meeting with VCs in the US, they were very fond of Australian companies because we were quite disciplined due to less access to capital, he said.

We had to build companies that were economically sound from the beginning. I think over the last five or six years, there was a mad sort of period, and weve probably lost some of that discipline.

Its been wonderful to see that discipline having to come back, and were going to build real businesses again, that have real customers and make real money, Anear added.

Read the rest here:
Tech wreck forces entrepreneurs to wash their own face - The Australian Financial Review

Quantum Logic Gates: The Next Frontier in Computing Technology

Quantum logic gates, the fundamental building blocks of quantum computing, are poised to revolutionize the field of computing technology. As the world becomes increasingly reliant on digital information and the processing power of computers, the need for more advanced computing systems has become evident. Classical computers, which operate using binary bits that represent either a 0 or a 1, have limitations in their ability to solve complex problems and perform calculations at high speeds. Quantum computing, on the other hand, leverages the principles of quantum mechanics to process information in a fundamentally different way, opening up new possibilities for solving problems that were previously considered intractable.

At the heart of quantum computing are quantum bits, or qubits, which can exist in multiple states simultaneously, thanks to a phenomenon known as superposition. This allows quantum computers to perform multiple calculations at once, vastly increasing their processing power compared to classical computers. Additionally, qubits can be entangled, a unique property that allows them to be correlated with one another in such a way that the state of one qubit can instantly affect the state of another, regardless of the distance between them. This phenomenon, known as quantum entanglement, is another key aspect of quantum computing that enables it to outperform classical computing systems.

Quantum logic gates are the devices that manipulate the states of qubits, allowing them to perform operations and calculations. These gates are analogous to classical logic gates, which perform operations on binary bits in classical computers. However, quantum logic gates operate on qubits and take advantage of their unique properties, such as superposition and entanglement, to perform operations that are not possible with classical logic gates. As a result, quantum logic gates have the potential to unlock a new frontier in computing technology, enabling the development of quantum computers that can solve problems and perform calculations at speeds and scales that were previously unimaginable.

One of the most significant applications of quantum computing technology is in the field of cryptography. Modern encryption methods, which are used to secure digital information and communications, rely on the difficulty of factoring large numbers into their prime components a task that is incredibly time-consuming and resource-intensive for classical computers. However, quantum computers, with their vastly superior processing power, could potentially crack these encryption methods in a fraction of the time, rendering current cryptographic techniques obsolete. This has led to a race among researchers and technology companies to develop new encryption methods that can withstand the power of quantum computing.

Another promising application of quantum computing is in the field of artificial intelligence and machine learning. The ability of quantum computers to process vast amounts of data simultaneously could significantly accelerate the development of more advanced AI algorithms and enable the creation of more sophisticated machine learning models. This, in turn, could lead to breakthroughs in fields such as natural language processing, computer vision, and autonomous systems.

Despite the immense potential of quantum computing, there are still numerous challenges that must be overcome before this technology can be fully realized. One of the most significant obstacles is the issue of error correction, as quantum systems are highly susceptible to errors due to their delicate nature and sensitivity to external factors. Researchers are actively working on developing error-correcting codes and fault-tolerant quantum computing architectures to address this issue.

In conclusion, quantum logic gates represent the next frontier in computing technology, with the potential to revolutionize fields such as cryptography, artificial intelligence, and many others. As researchers continue to make progress in overcoming the challenges associated with quantum computing, we can expect to see a new era of technological advancements that will reshape the way we process and interact with digital information.

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Quantum Logic Gates: The Next Frontier in Computing Technology - CityLife

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Barely a week passes without another dramatic report about humanity and the planet reaching a climate change tipping point. The latest reports were a heart-stopping analysis from the World Meteorological Organization and arresting criticism from the UN Secretary-General. Both were shared in the final days of April.

Artificial Intelligence will determine whether we blow through the tipping point or row back from the brink.

AI is one of the significant tools left in the fight against climate change. AI has turned its hand to risk prediction, the prevention of damaging weather events, such as wildfires and carbon offsets. It has been described as vital to ensuring that companies meet their ESG targets.

Yet, its also an accelerant. AI requires vast computing power, which churns through energy when designing algorithms and training models. And just as software ate the world, AI is set to follow.

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AI will contribute as much as $15.7 trillion to the global economy by 2030, which is greater than the GDP of Japan, Germany, India and the UK. Thats a lot of people using AI as ubiquitously as the internet, from using ChatGPT to craft emails and write code to using text-to-image platforms to make art.

The power that AI uses has been increasing for years now. For example, the power required to train the largest AI models doubled roughly every 3.4 months, increasing 300,000 times between 2012 and 2018.

This expansion brings opportunities to solve major real-world problems in everything from security and medicine to hunger and farming. It will also have a punitive impact on climate change.

Computing goes hand-in-hand with high energy costs and a larger carbon footprint, which tap the accelerator pedal on the worlds climate change.

This is especially true for AI. The huge number of GPUs running machine learning algorithms get hot and need to be cooled; otherwise, they melt. Training even one large language model (LLM) requires an eye-watering amount of energy with a large carbon footprint.

For example:

As we move into the GPT4 era and the models get larger, the energy needed to train them grows. GPT-3 was 100 times larger than its predecessor GPT, and GPT-4 was ten times the size of GPT-3. All the while, larger models are being released quicker. GPT-4 arrived in March 2023, nearly four months after ChatGPT (powered by GPT-3.5) was released at the end of November 2022.

For balance, we shouldnt assume that as new models and companies emerge in the space AIs carbon footprint will continue growing. Geeta Chauhan, an AI engineer at Meta, is using open-source software to reduce the operational carbon footprint of LLMs. Her latest work shows a 24-fold reduction in carbon emissions compared with GPT-3.

However, AIs popularity and its exponential power undermine much of the climate action in force today and call into question its potential to be part of the solution.

We need a solution that allows AI to flourish while arresting its carbon footprint. So, what do we do?

As always, technology will drag us out of this predicament.

For the explosion of AI to be sustainable, advanced computing must come to the fore and do the heavy lifting for many tasks that are currently performed by AI. The good news is that we already have advanced computing technologies that are primed to execute these tasks more efficiently and quickly than AI, with the added benefit of using much, much less energy.

In short, advanced computing is the most effective tool we have to temper AIs carbon addiction. With it, we can slow the creep of climate change.

There are a number of different technologies in advanced computing emerging that can solve some of the problems AI is currently tackling.

For example, quantum computing is superior to AI in drug discovery. As humans live longer, they are encountering, in ever greater numbers, new diseases that are complex and untreatable. This is called the better than The Beatles problem, where new drugs have modest improvements on already successful therapeutics.

So far, drug development has focused on rare events within a dataset and making educated guesses to design the right drugs to target and bind to the proteins that cause disease. LLMs can be efficiently used to help with this task.

LLMs are remarkably good at predicting which words in our vocabulary can best fit a sentence to accurately convey meaning. Drug discovery isnt wildly dissimilar as the problem is identifying the best fit, or configuration, of molecules in a compound to get a therapeutic result.

However,molecules are quantum elements, so quantum computing is much better at tackling this problem. Quantum computing has the capacity to quickly simulate vast numbers of binding sites in medicines to create the right configuration for treating currently incurable diseases.

Quantums capabilities mean that these can be solved much faster and with much less energy usage.

Another development with a real possibility to be an enhancement to AI is photonics, or so-called optical computing, which uses laser-produced light instead of electricity to send information.

Some companies are building computers that use this technology, which is much more energy-efficient than most other computing technologies and is being recognized increasingly as a route to achieving Net Zero.

Elsewhere, we have neuromorphic computers. This is a type of computer engineering where elements of the computer system are modeled on those in the human brain and nervous system. They perform computations to replicate the analog nature of our neural system. Trials of this technology include projects by Mythic and Semron. Neuromorphic is another greener option that needs further investment. Its hardware has the potential to run large deep learning networks that are more energy-efficient than comparable classical computing systems.

For example, processing information through its hundred billion neurons consumes only 20 watts, similar to an energy-saving light bulb in a home.

Developing and applying these innovations are imperative if we are to apply the brakes on climate change.

There are many startups (and investors) around the world obsessed with advanced computing but there are just a handful of companies that are focusing on so-called impact areas like healthcare, the environment and climate change.

Within quantum computing, the most-exciting companies that are developing use cases for energy and drug discovery are Pasqal (its cofounder was awarded the Nobel Prize in Physics 2022), Qubit Pharmaceutical and IBM. When it comes to photonics, we view the leaders with global impact as Lightmatter and Luminous, while in neuromorphic computing, we are tracking the progress of Groq, Semron and Intel.

Advanced computing is vital for achieving the energy efficiency we need to fight climate change. It simply takes too long and is too energy-intensive to run artificial neural networks on a GPU.

By adopting advanced computing methods as alternatives to AI, businesses can greatly alleviate the impact that AI has on the environment while still ensuring its vast power can mitigate some of the impacts of climate change, like anticipating wildfires or extreme weather.

The existential endpoint is approaching for our environment. But the situation is not hopeless.

The deployment of advanced computing is one credible and powerful resource to counteract the problem. We need to invest in these technologies now to solve the greatest challenge facing humanity.

Francesco Ricciuti is a VC at Runa Capital.

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Energy in the Quantum World: Understanding the Requirements of Quantum Computers

Quantum computing has been a hot topic in the world of technology for quite some time now. The potential of quantum computers to revolutionize industries such as cryptography, drug discovery, and artificial intelligence has led to a surge in research and development in this field. However, one aspect that is often overlooked is the energy requirements of these powerful machines. As we delve deeper into the quantum world, it is crucial to understand the energy needs of quantum computers and the challenges that lie ahead in making them a reality.

Quantum computers operate on the principles of quantum mechanics, which is fundamentally different from classical physics. In classical computing, information is stored and processed in bits, which can be either a 0 or a 1. Quantum computers, on the other hand, use qubits, which can be both 0 and 1 simultaneously, thanks to a phenomenon known as superposition. This allows quantum computers to perform complex calculations at an exponentially faster rate than classical computers.

However, the power of quantum computing comes at a cost. The delicate nature of qubits requires them to be maintained in a highly controlled environment, isolated from any external disturbances. This is because qubits are extremely susceptible to decoherence, a process in which the quantum state of a qubit is lost due to interactions with its surroundings. To prevent decoherence, quantum computers need to be cooled to temperatures close to absolute zero (-273.15 degrees Celsius), which requires a significant amount of energy.

In addition to cooling, quantum computers also require energy for error correction. Due to the inherent instability of qubits, quantum computers are prone to errors, which can significantly impact the accuracy of their calculations. To overcome this challenge, researchers have developed various error correction techniques that require additional qubits and energy resources. As the number of qubits in a quantum computer increases, so does the need for error correction, leading to a higher energy demand.

The energy requirements of quantum computers pose a significant challenge to their large-scale implementation. While research is ongoing to develop more energy-efficient quantum computing technologies, it is essential to consider the environmental impact of these powerful machines. The energy consumption of data centers, which house classical computers, already accounts for about 1% of global electricity use, and this number is expected to grow as our reliance on technology increases. If quantum computers were to replace classical computers, the energy demand could potentially skyrocket, putting immense pressure on our already strained energy resources.

One possible solution to the energy challenge in quantum computing is the development of hybrid systems that combine the best of both classical and quantum computing. These systems would use quantum computers for specific tasks that require their unique capabilities, while relying on classical computers for other tasks. This approach could help minimize the energy consumption of quantum computers while still harnessing their immense computational power.

Another avenue of research is focused on developing new materials and technologies that can support quantum computing at higher temperatures. This would reduce the need for extreme cooling and potentially make quantum computers more energy-efficient. However, this research is still in its early stages, and it remains to be seen whether it will yield practical solutions.

In conclusion, the energy requirements of quantum computers are a critical aspect that needs to be addressed as we move closer to realizing their potential. While the challenges are significant, ongoing research and development in this field hold the promise of finding innovative solutions to make quantum computing more energy-efficient and environmentally sustainable. As we continue to explore the quantum world, it is essential to keep in mind the energy implications of this groundbreaking technology and strive to develop solutions that balance both performance and sustainability.

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Energy in the Quantum World: Understanding the Requirements of ... - EnergyPortal.eu