Archive for the ‘Quantum Computing’ Category
Quantum Computing Takes a Giant Leap With Light-Based Processors – SciTechDaily
Posted: March 9, 2024 at 2:40 am
Researchers have developed a groundbreaking light-based processor that enhances the efficiency and scalability of quantum computing and communication. By minimizing light losses, the processor promises significant advancements in secure data transmission and sensing applications. Credit: SciTechDaily.com
A team of scientists has created a reprogrammable light-based quantum processor, reducing light losses and enabling advancements in quantum computing and secure communications.
Scientists have created a reprogrammable light-based processor, a world-first, that they say could usher in a new era of quantum computing and communication.
Technologies in these emerging fields that operate at the atomic level are already realizing big benefits for drug discovery and other small-scale applications.
In the future, large-scale quantum computers promise to be able to solve complex problems that would be impossible for todays computers.
Lead researcher Professor Alberto Peruzzo from RMIT University in Australia said the teams processor a photonics device, which used light particles to carry information could help enable successful quantum computations, by minimizing light losses.
Our design makes the quantum photonic quantum computer more efficient in terms of light losses, which is critical for being able to keep the computation going, said Peruzzo, who heads the ARC Centre of Excellence for Quantum Computation and Communication Technology (CQC2T) node at RMIT.
If you lose light, you have to restart the computation.
Other potential advances included improved data transmission capabilities for unhackable communications systems and enhanced sensing applications in environmental monitoring and healthcare, Peruzzo said.
The teams reprogrammable light-based processor. Credit: Will Wright, RMIT University
The team reprogrammed a photonics processor in a range of experiments, achieving a performance equivalent to 2,500 devices, by applying varying voltages. Their results and analysis are published in Nature Communications.
This innovation could lead to a more compact and scalable platform for quantum photonic processors, Peruzzo said.
Yang Yang, lead author and RMIT PhD scholar, said the device was fully controllable, enabled fast reprogramming with reduced power consumption, and replaced the need for making many tailored devices.
We experimentally demonstrated different physical dynamics on a single device, he said.
Its like having a switch to control how particles behave, which is useful for both understanding the quantum world and creating new quantum technologies.
Professor Mirko Lobino from the University of Trento in Italy made the innovative photonic device, using a crystal called lithium niobate, and Professor Yogesh Joglekar from Indiana University Purdue University Indianapolis in the United States brought his expertise in condensed matter physics.
Lithium niobate has unique optical and electro-optic properties, making it ideal for various applications in optics and photonics.
My group was involved in the fabrication of the device, which was particularly challenging because we had to miniaturize a large number of electrodes on top of the waveguides to achieve this level of reconfigurability, Lobino said.
Programmable photonic processors offer a new route to explore a range of phenomena in these devices that will potentially unlock incredible advancements in technology and science, Joglekar said.
Meanwhile, Peruzzos team has also developed a world-first hybrid system that combines machine learning with modeling to program photonic processors and help control the quantum devices.
Peruzzo said the control of a quantum computer was crucial to ensure the accuracy and efficiency of data processing.
One of the biggest challenges to the devices output accuracy is noise, which describes the interference in the quantum environment that impacts how qubits perform, he said.
Qubits are the basic units of quantum computing.
There are a whole range of industries that are developing full-scale quantum computing, but they are still fighting against the errors and inefficiencies caused by noise, Peruzzo said.
Attempts to control qubits typically relied on assumptions about what noise was and what caused it, Peruzzo said.
Rather than make assumptions, we developed a protocol that uses machine learning to study the noise while also using modelling to predict what the system does in response to the noise, he said.
With the use of the quantum photonic processors, Peruzzo said this hybrid method could help quantum computers perform more precisely and efficiently, impacting how we control quantum devices in the future.
We believe our new hybrid method has the potential to become the mainstream control approach in quantum computing, Peruzzo said.
Lead author Dr. Akram Youssry, from RMIT, said the results of the newly-developed approach showed significant improvement over the traditional methods of modelling and control, and could be applied to other quantum devices beyond photonic processors.
The method helped us uncover and understand aspects of our devices that are beyond the known physical models of this technology, he said.
This will help us design even better devices in the future.
This work is published in Npj Quantum Information.
Peruzzo said startup companies in quantum computing could be created around his teams photonic device design and quantum control method, which they would continue to study in terms of applications and their full potential.
Quantum photonics is one of the most promising quantum industries, because the photonics industry and manufacturing infrastructure are very well established, he said.
Quantum machine-learning algorithms have potential advantages over other methods in certain tasks, especially when dealing with large datasets.
Imagine a world where computers work millions of times faster than they do today, where we can send information securely without any fear of it being intercepted, and where we can solve problems in seconds that would currently take years.
This isnt just fantasy its the potential future powered by quantum technologies, and research like ours is paving the way.
References:
Programmable high-dimensional Hamiltonian in a photonic waveguide array by Yang Yang, Robert J. Chapman, Ben Haylock, Francesco Lenzini, Yogesh N. Joglekar, Mirko Lobino and Alberto Peruzzo, 2 January 2024, Nature Communications. DOI: 10.1038/s41467-023-44185-z
Experimental graybox quantum system identification and control by Akram Youssry, Yang Yang, Robert J. Chapman, Ben Haylock, Francesco Lenzini, Mirko Lobino and Alberto Peruzzo, 13 January 2024, npj Quantum Information. DOI: 10.1038/s41534-023-00795-5
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Quantum Computing Takes a Giant Leap With Light-Based Processors - SciTechDaily
Google Is Offering $5 Million in a Quantum Computing Contest – Entrepreneur
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Google, the Geneva Science and Diplomacy Anticipator (GESDA), and XPRIZE launched a competition Monday that will award $5 million over three years to teams who can find real-life applications for quantum computers.
Quantum computers process information differently from the regular, classical computers in use today, which allows them to complete certain tasks in shorter periods of time. Google researchers found in 2019 that a quantum computer took 200 seconds to complete a task that a high-performing supercomputer, which IBM estimates can have a million times more processing power than a standard laptop, would take 10,000 years to complete.
The problem that the XPRIZE competition sets out to solve is the disconnect between quantum algorithms and the real world. Applicants should be working on quantum algorithms that address sustainability and social impact.
The contest is open to anyone across the world working in any field. Winners will have submissions that "most accelerate" quantum algorithms for "positive real-world applications," according to the competition guidelines.
Applicants can submit a new quantum algorithm, a new application of an existing algorithm, or enhanced performance in the form of fewer resources to run an established algorithm. The University of Chicago, IBM, Microsoft, and Purdue University are some of the many institutions that offer courses on quantum computing.
Registration is open on the XPRIZE website.
Related: Quantum Computing Threatens Everything Could it be Worse Than the Apocalypse?
A cryostat from a quantum computer stands during a press tour of the Leibniz Computing Center. Photo: Sven Hoppe/dpa (Photo by Sven Hoppe/picture alliance via Getty Images
Quantum computing is a focus area for many tech giants, with McKinsey estimating a record $2.35 billion in investments in 2022. The McKinsey report further suggests that four industries are likely to see the earliest benefits of quantum computing: automotive, chemicals, financial services, and life sciences.
Related: Why This Technology Will Surge This Year and How You Can Capitalize On It
IBM CEO Arvind Krishna spoke to the Duke Fuqua School of Business last April about the benefits of quantum computing, and about how business minds were essential to determine the right use cases for the technology.
"So, you need to work on what kind of algorithms, which use case can leverage those algorithms, and the technology," Krishna told the outlet.
IBM and Google gave $150 million last year to advance quantum computing research at the University of Chicago and the University of Tokyo.
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Google Is Offering $5 Million in a Quantum Computing Contest - Entrepreneur
Google sets up $5 million competition to find out what quantum computers can really do – The Indian Express
Posted: at 2:40 am
If you have no idea what quantum computers can do, do not worry. You are in the same club as search and advertising giant Google. The company on Monday announced it is launching the 3-year, $5-million-dollar XPRIZE Quantum Applications to solve real-world challenges with the technology.
The competition is soliciting quantum computing algorithms that can potentially be used to achieve what Google is referring to as societally beneficial goals, like the United Nations Sustainable Development Goals. This is in line with Google Quantum AIs mission to build a large-scale, error-corrected quantum computer and develop useful quantum computing applications.
The device you are reading this on, whether it is a personal computer, a smartphone or even a VR headset, is powered by classical computing. Classical computers store information in binary bits, which can have two values either 0 or 1. Quantum computers encode information in what is known as a quantum bit or a qubit.
Quantum computers are machines that use the properties of quantum physics to store data and perform computations. This can be extremely advantageous for certain tasks where they could vastly outperform even our best supercomputers.
Classical computers, which include smartphones and laptops, encode information in binary bits that can either be 0s or 1s. In a quantum computer, the basic unit of memory is a quantum bit or qubit. Just like a classical computing bit, a qubit can have two distinct states and these can be used to represent either a 0 or a 1. But unlike a classical bit which can only exist in one of these states, a qubit can exist in superposition states or even be entangled with other quantum bits.
This, in theory, makes qubits much more powerful than classical bits, therefore making quantum computers much more powerful than classical computers, depending on the application.
A majority of the efforts spent in research is directed at actually building viable quantum computers. As such, most quantum algorithms are mainly studied in the context of abstract mathematical problems.
Scientists have many reasons to be optimistic about the potential of quantum computing but they are still in the dark about the full scope of this technology and what real-world applications, especially during its early stages. Google is hoping that this prize will incentivise the quantum computing community to come up with the answer to the most pressing question What do we do with quantum computers once they are built?
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First uploaded on: 06-03-2024 at 14:17 IST
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How Quantum AI Adapts to Changing Market Trends – Native News Online
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In today's fast-paced and ever-changing world, staying ahead of market trends is crucial for businesses to thrive. Traditional methods of market analysis and prediction are often limited by their reliance on classical computing algorithms. However, a revolutionary technology called Quantum AI is changing the game, offering unprecedented capabilities for adapting to changing market dynamics.
The essence of Quantum AI lies in the convergence of quantum computing and artificial intelligence. To comprehend the power of Quantum AI in market analysis, it is imperative to grasp the fundamental concepts behind quantum computing.
Quantum AI represents a cutting-edge technological frontier that holds immense promise for revolutionizing various industries, and with this knowledge in mind, your Quantum AI journey begins. By leveraging the principles of quantum mechanics and artificial intelligence, Quantum AI opens up a realm of possibilities that were previously unimaginable. The fusion of these two advanced fields not only enhances computational capabilities but also paves the way for groundbreaking advancements in data analysis, machine learning, and predictive modeling.
Quantum computing is based on the principles of quantum mechanics, which deal with the behavior of matter and energy at the atomic and subatomic levels. Unlike classical computers that use bits to represent information as either a 0 or a 1, quantum computers utilize quantum bits, or qubits, which can exist in multiple states simultaneously. This enables quantum computers to perform complex calculations at an unimaginable speed.
At the core of quantum computing is the phenomenon of superposition, where qubits can exist in a state of 0, 1, or any quantum superposition of these states. This unique property allows quantum computers to explore multiple solutions to a problem simultaneously, leading to exponential speedup in certain computational tasks. Additionally, quantum entanglement, another key principle in quantum mechanics, enables qubits to be interconnected in such a way that the state of one qubit is dependent on the state of another, regardless of the physical distance between them.
Artificial intelligence, on the other hand, focuses on the development of intelligent machines capable of simulating human-like behavior. By combining the computational power of quantum computers with AI algorithms, Quantum AI harnesses the potential for enhanced problem-solving, optimization, and prediction capabilities.
Quantum AI algorithms have the capacity to process and analyze vast amounts of data with unprecedented efficiency, leading to more accurate insights and predictions. The synergy between quantum computing and AI not only accelerates the pace of innovation but also unlocks new frontiers in machine learning, natural language processing, and robotics. As Quantum AI continues to evolve, it is poised to redefine the boundaries of what is possible in the realm of advanced computing and artificial intelligence.
Market analysis involves examining vast amounts of data to identify patterns, make predictions, and inform decision-making. Quantum AI offers unique advantages in this regard, revolutionizing traditional approaches and opening up new possibilities.
Quantum AI combines the principles of quantum mechanics with artificial intelligence, creating a powerful tool for market analysis. By harnessing the properties of superposition and entanglement, Quantum AI can process and analyze data in ways that classical computers cannot. This allows for more sophisticated modeling of market dynamics and more accurate predictions of future trends.
One of the key strengths of Quantum AI lies in its predictive capabilities. By leveraging the immense computational power of quantum computers, it becomes possible to analyze extensive historical data and identify complex patterns and trends. Quantum AI algorithms can uncover hidden correlations and make highly accurate predictions, empowering businesses with actionable insights.
Furthermore, Quantum AI can handle non-linear relationships and high-dimensional data with ease, providing a more comprehensive understanding of market behavior. This enhanced predictive ability enables businesses to anticipate market shifts, optimize investment strategies, and mitigate risks effectively.
Another significant advantage of Quantum AI is its ability to adapt to real-time market changes and make informed decisions on the fly. Traditional market analysis methods often struggle to keep up with rapidly evolving trends. Quantum AI, however, excels in handling large volumes of data in real-time, enabling businesses to react promptly to emerging opportunities and risks.
Moreover, Quantum AI's adaptive nature allows for dynamic decision-making processes that can adjust strategies in response to changing market conditions. This agility is crucial in today's fast-paced and volatile business environment, where timely decisions can mean the difference between success and failure.
Understanding and capitalizing on market trends is vital for businesses to stay competitive. Quantum AI offers unique advantages in identifying and leveraging emerging market trends.
By processing vast amounts of data from multiple sources, Quantum AI can detect subtle shifts and patterns that may indicate emerging market trends. This provides businesses with a competitive edge, allowing them to anticipate changes and adapt their strategies proactively.
Market forecasting is an essential aspect of market analysis, helping businesses make informed decisions about future market conditions. Quantum AI's ability to process vast amounts of data and identify hidden patterns and correlations allows for more accurate and reliable market forecasting. This assists businesses in making strategic decisions to drive growth and profitability.
As Quantum AI continues to evolve, its potential applications in market analysis are vast. However, several challenges and considerations need to be addressed to fully realize the benefits of this revolutionary technology.
One of the main challenges in adopting Quantum AI for market analysis is the need for highly specialized skills and resources. Quantum computing is a complex field that requires expertise in quantum physics and computer science. Collaboration between different disciplines and investments in research and development are crucial to overcoming these challenges.
The impact of Quantum AI in market analysis extends across various industries. From finance and healthcare to retail and manufacturing, businesses can leverage the power of Quantum AI to gain a competitive advantage. The ability to gather valuable insights and make informed decisions based on accurate market analysis has the potential to transform industries and reshape market dynamics.
In conclusion, Quantum AI represents a monumental leap forward in market analysis. By combining the computational power of quantum computing with the intelligence of AI algorithms, businesses can enhance their ability to adapt to changing market trends. The predictive capabilities, real-time adaptability, and accurate market analysis offered by Quantum AI can empower businesses to make informed decisions and stay ahead of the competition. Embracing Quantum AI is not only an investment in the future but also a means to drive innovation and growth in an ever-evolving market landscape.
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How Quantum AI Adapts to Changing Market Trends - Native News Online
Assessing the post-quantum threat 3 tips to be ready – SDxCentral
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Assessing the post-quantum threat 3 tips to be ready - SDxCentral
Are We Ready for the Quantum Age? Preparing for the Risks of Quantum Technologies with Rights-Respecting Policy … – Tech Policy Press
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At what point will we declare that quantum technologies are no longer emerging, but have fully arrived? Whatever the breakthrough is that signals the tipping point, legal frameworks are not yet ready to handle the impacts of widespread quantum computing on people, societies and the rights they hold. Recent developments in the artificial intelligence (AI) policy space provide a useful roadmap for anticipating the evolution of policy approaches for regulating quantum technologies and the universe of risks they will bring with them.
Yet, as with AI, the risks are still under examined. Though we know that they will emanate from the ways in which quantum computing will amplify existing technologiessuch as AI and surveillance it is also clear they will stem from brand new capabilities, like breaking all current encryption or the application of quantum sensing (which will bring the ability to see through barriers, around corners, and potentially into the body or mind). This paper aims to shine a light on these risks, as well as the practical steps that can be taken today to address them.
The widespread release of generative AI models and applications in 2023 sent shockwaves through popular culture and signaled to world leaders and policymakers that the risks of artificial intelligence (AI) outstripped many of our existing risk management frameworks. It triggered an unprecedented wave of new efforts to plug the gaps, including The Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, The Voluntary Commitments from Leading Artificial Intelligence Companies, The Bletchley Declaration, The Hiroshima Process, and the UN Advisory Body on AI Interim Report on Governing AI for Humanity, the NIST AI Risk Management Framework, and the EU AI Act, as well as the forthcoming Council of Europes Convention on Artificial Intelligence, Human Rights, Democracy and the Rule of Law.
Stakeholders point out that the fourth-quarter rush to better govern AI parallels the pace of efforts to govern social media and the digital economy. They continue to urge policymakers to act with greater speed to safeguard against AI risks, including stronger application of existing human rights frameworks to manage AI risks. The wait-and-see approach to regulation is only justifiable when the benefits of innovation are clear and the risks are low, ill-defined or under examined. However, quantum computing, particularly in conjunction with AI, has many foreseeable dangers. Hard won lessons from recent tech policy history show us how critical it is for policymakers to safeguard quantum technologies before they are more widely deployed and accessible.
The risks that over-regulation can stifle innovation and cause technological leaders among nations, like the US, to be less competitive in a complicated geopolitical environment are real, and policy recommendations must balance these considerations. Considering quantum regulation now provides an opportunity to develop forward-looking, intentional policy frameworks that better balance the need for innovation with the need to safeguard human rights. Now is the time to begin these conversations before yet another Pandora opens a box of societal ills.
IBM, the United States foremost quantum developer, estimates that by 2030 the full power of quantum computing will be unlocked. If the companys estimates are accurate, there could be as little as six years to build the international consensus needed to establish guardrails for responsible and rights-respecting quantum computing, including updated standards for cryptography. If the past is precedent, it will take time for the global community to coalesce around approaches for integrating key human rights principles into innovation-friendly risk management frameworks for quantum, and it will take even longer for new and updated standards to be implemented. For example, in 2022 the Biden Administrations National Security Memorandum 10 on Promoting United States Leadership in Quantum Computing While Mitigating Risks to Vulnerable Cryptographic Systems, establishes 2035 as the date by which US Government entities should achieve a timely and equitable transition to quantum resistant cryptography to mitigate as much risk as possible. The time to start building consensus is now. What risks should policymakers and companies prioritize and what can be done to manage them?
To underscore the urgency of preventative policy action, we present three concrete examples of the potential dangers posed by quantum computing if we fail to take precautionary steps now. These three risks are among the most nearterm issues the world will confront as quantum technologies are deployed for everyday use: encryption breaking quantum computing, the pairing of quantum technologies with artificial intelligence for digital repression, and the application of quantum technologies to make thoughts legible to external observers (also known as mind reading).
First, a quick overview of what quantum technologies mean at this moment in time. In their groundbreaking 2021 book Law and Policy for the Quantum Age, Chris Jay Hoofnagle and Simson L. Garfinkel outline three areas in which quantum information science (QIS) will have the biggest nearterm impacts on nation states, decisionmakers (including investors), and individuals lives. Those areas are: quantum sensing, quantum computing, and quantum communications, which are defined below. The authors highlight that the nexus of these QIS sectors present a number of potential civil and political rights implications that existing policy frameworks do not yet address. Fundamental human rights standards can and will eventually be applied to prevent and address the application of QIS technologies in harmful ways. However, the slow, halting application of such standards in the social media and AI spaces, often in the wake of avoidable tragedies, teaches us that additional international consensus is required to better define and guide how human rights shape technology governance. The absence of fit-for-purpose frameworks enables bad or negligent actors to take advantage of the gray space to societys collective detriment.
For many readers, QIS technologies are likely not yet well known. Here are some basics:
While we are focused on the potential human rights risks that could result from more generally accessible quantum technologies, human-rights based risk frameworks can and should be developed to consider the broader range of risks relating to the application of QIS technologies across the tech stack and across all sectors of society, industry and national defense. This article outlines some of the most troubling risks, largely outside of the national security context, and suggests potential policy approaches that policymakers can prioritize in the coming decade.
In this age of hyper-connectivity, the sanctity of personal information underpins not only individual privacy but also the pillars of national security and global diplomacy. This sanctity is often secured by RSA encryption. In basic terms, RSA encryption involves two keys: a public key, which can be shared with everyone, and a private key, which is kept secret. When a message is sent, it is encrypted using the recipient's public key. This encrypted message can only be decrypted with the corresponding private key. The security of RSA stems from the fact that, while it's relatively easy to multiply two large prime numbers together to create a product, it's extremely difficult to do the reversethat is, to start with the product and find the original prime numbers. This one-way function is what makes RSA encryption among our most robust data privacy protections. The greatest supercomputers on the planet today would take millions of years to break this code. A seemingly invincible algorithm will meet its match, though, in the coming age of quantum computing.
Quantum computers are uniquely advantaged in solving this problem due to their fundamentally different approach to processing information. Qubits within a quantum computer exist in multiple states at once, in stark contrast to the binary nature of traditional bits. Quantum programs such as Shors Factoring Algorithm take advantage of this property in order to test an array of potential factors in the public key all at once. This fundamental distinction and other qualities allow these devices to determine the correct factors much faster than traditional computers. A sufficiently powerful quantum computer could cut the time needed to decode RSA encryption from eons to minutes.
Some experts hold that RSAs demise is a distant problem, given the current capabilities of quantum computers. While we are still jumping the technological hurdle of scaling quantum devices, and although Shors algorithm is computationally taxing, recent research such as that by NYU researcher Oded Regev may bring about quantum code-breaking much sooner than we once thought. Given the rapidly changing quantum landscape, with new research constantly being published, the uncertain timeline for these algorithms is all the more reason to be prepared.
The threats that this development poses to our data infrastructure are glaringly obvious. In addition to threatening the security of government secrets and citizens private information, an RSA breach could have significant human rights implications. Consider the nature of end to end encryption over messaging services that use RSA encryption such as Skype, Apple iMessage and Telegram. These tools provide human rights defenders and activists with a means of communication that is less vulnerable to unwarranted surveillance practices, enabling them to avoid arrest or detention for exercising protected civil and political rights. As quantum computers extend encryption breaking capabilities to repressive regimes, human rights defenders will become easy targets for government surveillance and repression. Repressive regimes may already be collecting currently uncrackable message contents in hopes they may be readable down the road using a Harvest Now, Decrypt Later methodology, a scenario that has already prompted some tech firms to act.
Adopting post-quantum cryptography will be logistically challenging and resource intensive, but it is an issue we must address urgently. The path is clear: establish a more forward-looking quantum policy agenda that mandates the overhaul of our encryption standards and software to elevate the use of algorithms that are safe against classical and quantum computation. The United States has already taken decisive action in this area. In 2022 the Biden Administrations National Security Memorandum 10 on Promoting United States Leadership in Quantum Computing While Mitigating Risks to Vulnerable Cryptographic Systems established 2035 as the date by which US Government entities should achieve a timely and equitable transition to quantum resistant cryptography to mitigate as much risk as possible. To support implementation of NSM-10, the US is developing standards for post-quantum encryption methods through The National Institute of Standards and Technology (NIST), which has already selected four quantum-proof encryption algorithms.
The development and integration of these standards into software and hardware requires concerted efforts from manufacturers and developers, including rigorous security and interoperability testing. Moreover, the update of critical infrastructure and services must be prioritized to uphold security and trust. Regulatory adjustments by governments to foster or enforce the adoption of these new encryption standards are essential, alongside public education initiatives to highlight the importance of embracing these updates for enhanced security. Continuous research and adaptation are imperative to counteract evolving cyber threats and technological innovations, effectively future-proofing encryption methods. The degree to which new standards are implemented depends upon the availability of sufficient resources to convert encryption systems. Those resources will only be made available if government and private sector stakeholders are sufficiently aware of impending risks and motivated to prioritize often scarce resources.
Academics, policymakers and civil society groups have raised alarm bells in recent years to draw attention to the risks posed by the misuse of technology, including artificial intelligence, to repress political opposition, surveil activists and control populations. As authoritarian (and some democratic) regimes increasingly harness technology to repress the public and retain or expand power, threats to fundamental civil and political rights are growing. While policymakers currently have their hands full developing human rights frameworks and safeguarding tools to better identify and manage the risks of artificial intelligence, advances in QIS will not wait. As human rights and technology scholar Vivek Krishnamurthy warns us, Quantum technologies may not yet be at the level of development where their potential impacts can be examined in detail. Even so, now is the time for the [quantum science and technology] and human rights communities to begin a dialogue to prepare for the deployment and commercialization of these technologies in a rights-respecting manner.
While many unknowns remain, there are a number of risks that are more foreseeable, as described below. Is there a way to shape evolving AI risk management frameworks to account for the additional impacts of AI combined with quantum technologies? For example, guardrails that mitigate the risks of AI-powered data fusion and social scoring would go a long way to mitigating the compounded impacts when AI is combined with quantum technologies. In addition to building upon the policy roadmap provided by AI governance frameworks in the future, is it possible to embed additional, quantum-facing risk management measures now?
AI is already being used by autocratic governments to better track political opposition and activists, and to coerce support for autocratic regimes through denial of needed government services. As noted in the 2020 Senate Foreign Relations Committee report on the use of surveillance and big data analytics in the Peoples Republic of China, artificial intelligence, facial recognition technologies, biometrics, surveillance cameras, and big data analytics [are being used] to profile and categorize individuals quickly, track movements, predict activities, and preemptively take action against those considered a threat in both the real world and online. Through big data analytics, algorithms conglomerate personal data and surveillance data surrounding ones behavior, activities, and social interactions in order to track or even score individuals. This process requires the analysis of a huge amount of data, which is challenging for classical computers on a massive scale, but ideal for quantum systems. Quantum computers ability to handle vast amounts of data at high speeds will enable disturbingly sophisticated and invasive analysis of personal behaviors and social interactions. This increased computational power allows for the real-time monitoring and scoring of individuals on a more granular level, super-sizing tactics for authoritarian control and surveillance.
As alluded to above, real-time remote biometric surveillance equipment creates the capacity to track individuals. Digital identification and centralized databases for this information create the potential for governments and for-profit enterprises to misuse such systems to monitor individuals through the use of big data analytics. Artificial intelligence can make sense of this data in order to create profiles of citizens which aim to distinguish one person from another based on collected biometric information. The Carnegie Council estimates that over 100 US cities are currently using data fusion technologies to track individuals through doorbell cameras, license plate readers, digital utility meters, street cameras, and GPS technologies, in a way that can create extensive individual profiles. Data fusion is defined as bringing data points together to create a swarm of information that can reveal a great deal about a traceable individual. The Carnegie Councils Data Fusion Mapping Tool provides an overview of the impacts of data fusion on the exercise of civil liberties in the US and highlights the risks of allowing data fusion to be used in jurisdictions without adequate due process or other risk mitigation measures.
AI-powered data fusion is not yet universally used. Now is the time to consider the implications of a super-sized universal data fusion capacity powered by quantum computing technology. Quantum-powered data fusion could make it impossible for an individual to evade tracking due to the power to process massive amounts of data pulled from unlimited public or private sector sources. Quantum computers will further expand the ability of surveillance systems to recognize your gait across millions of hours of surveillance footage, single out your voice from an audio recording of a crowded room, or identify you from the cadence of your keystrokes, without needing to read the text you send. Whether moving through city streets, participating in protest, or simply enjoying the supposed solitude of open spaces, the shadow of surveillance looms large, with quantum-enhanced systems capable of sifting through the haystack of data to pinpoint the needle of an individual identity with astonishing precision. In short, the birth of quantum computing may signal the death of anonymity.
Due to their ability to analyze huge data sets and recognize patterns or deviations from those patterns, quantum computers detect anomalies far more effectively than do classical computers. When fed surveillance data regarding the behavior of an individual, a future quantum computer would have the power to determine if that behavior deviates from their usual conduct, and ascertain what future actions will likely stem from this abnormality. Human rights concerns arise if and when this technology is applied for the purpose of predictive policing. Detaining or questioning individuals based on predicted future actions blurs the line between potential and actual wrongdoing. If left unchecked, this predictive technology could be used to further erode the line between intent to potentially commit a crime and the criminal act itself.
Lawmakers are working to enact safeguards needed to address risks that can result from the application of artificial intelligence for certain uses and in certain contexts. For example, the EU AI Act will prohibit social scoring, certain applications of predictive policing, and remote biometric identification for law enforcement purposes in public settings. There is not yet global consensus supporting prohibition of these uses of AI, and there are clear concerns that such prohibitions will stifle innovation or constrain law enforcement. The fact remains that international consensus for innovation-friendly AI safeguards are urgently needed before the riskiest use cases outlined above become commonly accepted practice. Such guidelines, many of which are under development by the United Nations, OECD (in multiple papers), and other international bodies, will provide an invaluable roadmap for launching similar efforts to constrain the misuse of quantum-based technologies for digital repression.
Beyond the policy realm, are companies taking up the challenge to design, develop and deploy QIS in ways that protects us from extreme misuse cases? If QIS is deployed in tandem with data-driven AI technologies, then the biases and inaccuracies that can emerge from AI applications would be substantially scaled beyond what we see today. How will existing algorithmic bias audits or similar safeguards be tweaked to consider the potential impacts of the quantum age? What role can regulation play in prompting companies to take such steps without stifling innovation or hampering law enforcement? How can we advance such efforts now, before pandora opens the box? And perhaps most urgently, can we apply a quantum lens to the development of AI governance frameworks today that may help us mitigate tomorrows risks?
We are already living in a time when machines are capable of translating your brain activity, as seen through an MRI, into words. Your very thoughts are now legible. Surveillance cameras are similarly trained to register your emotionsthis is a form of emotional AI, which companies are already using to improve targeted sales. Do you have the right not to have your mind or emotions read? This is a question we will need to resolve before quantum computing amplifies the capabilities of mentally intrusive technologies.
Quantum computers are likely to further amplify the power that classical computers already have to identify patterns and correlations in MRI brain scan images that classical computers cannot. Consider again the question of arrests made possible by quantum computing. Is a quantum powered lie detector testone using an MRI machine and a sufficiently powerful quantum AI algorithm, instead of a heart rate monitoradmissible in court? To take it a step further, is intent to commit a crime, if recognized through the power of a quantum mind-reader, grounds for legal intervention? And what guardrails would be required to ensure that the data sets upon which such algorithms are based are free from bias and inaccuracy? While these applications of quantum computing are more speculative than the inferences made above, they are potentially more urgent given the degree of possible harm and the absence of targeted human-rights frameworks or safeguards.
Critical questions about the limits of brain legibility do not appear to be at the forefront of most AI policy conversations, which leads one to conclude they will be similarly sidelined in future engagements on the intersection of human rights and quantum computing. Policies that establish human rights-based neurological safeguards are still underdeveloped. Now is the time to better define them. While we are far from an international consensus, one initial effort to define neurorights identified five categories that could be helpful in considering the impact of quantum-powered brain legibility. Those rights are: the right to mental privacy so that our brain data cannot be used without our consent; the right to free will, so we can make decisions without neuro technological influence, the right to personal identity so that technology cannot change our sense of self, the right to protection from discrimination based on brain data, and not least, the right to equal access to neural augmentation. International policy conversations outlining the application of human rights in this context are urgently needed and long overdue. It is unclear whether the neurorights discussion will attract global attention. Fortunately, policymakers have a wealth of existing human rights to consider in connection with emerging quantum mind-reading risks, including the right to bodily integrity that protects autonomy over ones body.
It is too early to identify the full range of potential impacts that QIS technologies may have on individuals and societies. However, experience establishing safeguards in connection with the internet, social media and artificial intelligence shows how difficult it can be to erect risk management efforts after economic models are entrenched or unregulated behaviors coalesce into accepted practice, regardless of their impacts. Now is the time to raise awareness of the foreseeable risks and increase research on risks that are less well understood. Increased advocacy by stakeholders from civil society, consumer protection organizations and academic institutions will help to justify allocation of the resources needed to achieve the recommendations outlined above. Financial commitments by public and private sector entities will be necessary to support a transition to quantum-ready encryption by 2035. Resources will also be needed to support policy analysts in considering if and how quantum considerations can be accommodated in todays AI risk management frameworks. And perhaps most importantly, QIS developers must allocate sufficient resources to understand the impacts that brand new capabilitieslike quantum sensingwill have on individuals and society as a whole.
The quantum computing community has a great deal to learn from recent efforts to apply the UN Guiding Principles for Business and Human Rights to generative AI models and applications. Such efforts provide a roadmap for better weaving human rights-based enterprise risk management approaches to govern QIS for governments and businesses alike. QIS stakeholders are fortunate to have an opportunity to build upon the evolving international consensus being hammered out now for AI.
The risk quantum computing poses to RSA encryption is already well understood, and NIST has established important guidelines for bringing encryption standards into the quantum age. However, as noted above, this shift will require significant policy support and even public funding to ensure that the pace of transition matches evolving quantum capabilities.
While world leaders and policymakers have their hands full addressing the most urgent AI-related risks, parallel questions in the QIS space will become increasingly urgent as we near 2030. Bandwidth among policymakers in the technology space is more limited than ever, and one can argue that regulating quantum risks should take a backseat when compared with the urgency of present day impacts of AI. While the risks may be years awaythey will also be significant. This moment offers an important opportunity for the legions of organizations, think tanks and academics who moved quickly to respond to evolving risks of generative AI to now turn their attention to the QIS horizon. This is the time to prepare the same level of thoroughly researched, insightful and practical recommendations for innovation-friendly QIS risk management that will enable policymakers and companies to take action beforeglobal society becomes a real-time testbed for identifying QIS impacts.
This article represents the opinions of the authors and in no way reflects the position of the United States Government or USAID. Thanks go to Stanley Byers, Chris Doten and Paul Nelson for their contributions to this article.
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Google Is Ready To Burn $5M To Learn How To Use Quantum Computing – Dataconomy
Posted: at 2:40 am
Quantum computing is a million-dollar question, even for Google. Thats why they started the XPRIZE Quantum Applications competition with GESDA. Theyre looking for ideas from people all over the world on how quantum computing can help solve things like healthcare, finance, and more. Google hopes this will lead to practical uses for quantum technology, making life better for everyone.
The XPRIZE Quantum Applications competition, launched by Google in collaboration with the Geneva Science and Diplomacy Anticipator (GESDA), is a global initiative aimed at discovering real-world applications for quantum computing technology. Heres a detailed explanation of how the competition works:
While the immediate goal of the competition is to identify and reward innovative quantum computing applications, its broader impact lies in accelerating the development and adoption of quantum technologies. By incentivizing research and development in this emerging field, the competition aims to unlock new possibilities for solving complex problems and driving societal progress.
Overall, the XPRIZE Quantum Applications competition represents a collaborative effort to harness the transformative power of quantum computing for the benefit of humanity. Through targeted investments, rigorous evaluation, and global participation, the competition endeavors to chart a path towards a future where quantum technologies play a central role in addressing some of the worlds most pressing challenges.
Quantum computing is like a puzzle waiting to be solved we know its powerful, but figuring out exactly how to use it in the real world is still a bit of a mystery. However, weve got some exciting ideas brewing.
Imagine if we could speed up the process of finding new medicines by using quantum computers to simulate how molecules interact. It could help us discover life-saving drugs faster than ever before. Want to learn the role of generative AI in drug discovery? Visit the related article and explore.
Quantum computers have a knack for solving complex puzzles, like figuring out the most efficient routes for delivery trucks or finding the best investment strategies in finance. Its like having a supercharged brain for solving problems.
Traditional encryption methods might not stand a chance against quantum computers, but on the flip side, we can use quantum principles to create ultra-secure communication channels. Its like turning the tables on hackers and making our data safer than ever.
Quantum algorithms could revolutionize machine learning, allowing us to crunch through mountains of data at lightning speed. The possibilities are endless, from recognizing images to understanding languages.
By harnessing the immense computational power of quantum computers, we could create more accurate climate change models. This could give us a better understanding of environmental processes and help us find ways to protect our planet.
So, while were still figuring out all the ins and outs of quantum computing, theres no shortage of exciting possibilities on the horizon. Who knows what other amazing applications well discover as we continue to unlock the mysteries of this cutting-edge technology? Probably, the winner of XPRIZE Quantum Applications competition.
Featured image credit: Jp Valery/Unsplash
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Google Is Ready To Burn $5M To Learn How To Use Quantum Computing - Dataconomy
Tabor Electronics and FormFactor Unveil Full Stack 5-Qubit Quantum Computer Project Powered by QuantWare – Quantum Computing Report
Posted: at 2:40 am
Tabor Electronics, in collaboration with FormFactor, is demonstrating the first phase of the Echo-5Q project, a full stack 5-Qubit Quantum Computer powered by QuantWares Quantum Processing Unit (QPU). This achievement showcases a significant 250% enhancement in T1 times compared to similar systems, ensuring higher qubit fidelity and increased quantum operations per cycle. The Echo-5Q project addresses the growing demand for practical quantum computing test beds and a skilled workforce. Key components of this solution include FormFactors LF-600 Cryogen-free Dilution Refrigerator, Tabor Electronics Proteus Direct to RF Control Electronics, and QuantWares Soprano-D QPU. The collaboration leverages decades of experience from both Tabor Electronics and FormFactor, resulting in good performance from the QuantWare QPU. For additional information, you can access the press release posted on the Tabor website here and the Echo-5Q Overview sheet here.
March 7, 2024
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OQC Welcomes Chevron Technology Ventures in $100M Series B Funding to Enhance Quantum Computing in the … – HPCwire
Posted: at 2:40 am
READING, England, March 5, 2024 OQC, a global leader in quantum computing-as-a-service (QCaaS), today announced that Chevron Technology Ventures, part of Chevron Corporation (CVX: NYSE), has joined its $100m Series B funding round.
Quantum computing in the energy market is expected to grow at a CAGR of 37.9%, owing to the increasing demand for efficient optimization and simulation across the sector. Chevrons investment marks a significant move by a supermajor into the rapidly evolving field of quantum computing.
OQCs development of the quantum computer has the potential to change the information processing landscape by merging the bounds of engineering and physics, said Jim Gable, Vice President, Innovation and President of Technology Ventures at Chevron. This is the latest investment from our Core Energy Fund, which focuses on high-tech, high-growth startups and breakthrough technologies that could improve Chevrons core oil and gas business performance as well as create new opportunities for growth.
OQC recently launched OQC Toshiko, an upgradable 32-qubit platform and the worlds first Enterprise Ready Quantum Computing Platform. As the first company in the world to integrate quantum computing into commercial data centers, OQC is bringing quantum out of the lab and into the data centre. The company aims to make it possible to offer hybrid computing, integrated quantum and high-performance computing, to the market.
A Quantum Future for Energy
OQCs technology provides several potential groundbreaking opportunities for the energy sector, including the development and optimization of catalysts and the efficiency of transportation and distribution networks. Quantum is anticipated to accelerate the energy industrys discovery and development of new materials through the simulation of complex molecules to lower carbon products.
To realize this future, the energy industry requires secure, accessible and powerful quantum computing that is integrated with existing high-performance computing. Prior to the launch of OQC Toshiko, quantum computers were only available in labs, making secure access for companies and integration with existing high-performance computing the largest barriers to wider business adoption of this groundbreaking technology.
Spearheading Industry-Leading R&D
OQC recently announced that SBI Investment, Japans premier venture capital fund, is leading OQCs $100m Series B raise. Existing investors Oxford Science Enterprises (OSE), The University of Tokyo Edge Capital Partners (UTEC), Lansdowne Partners, and OTIF, acted by manager Oxford Investment Consultants (OIC), are also participating.
The ongoing round is the UKs largest ever Series B in quantum computing enabling industry-leading R&D that could pave the way to quantum advantage and furthers OQCs ability to bring next generation platforms of hundreds of qubits to businesses globally.
Commenting on the news, Ilana Wisby, Chief Executive Officer at OQC, said: Chevrons investment marks a significant milestone in harnessing quantum computing for the energy sector. Were excited to drive innovation and efficiency in exploration and renewables and pioneer enterprise-ready quantum in the energy sector.
About Chevron Technology Ventures
Chevron Technology Ventures identifies and invests in externally developed technologies and new business solutions with the potential to enhance the way Chevron produces and delivers affordable, reliable, and ever-cleaner energy. CTV has more than two decades of being the primary on-ramp for external innovation into Chevron. For more information, visit http://www.chevron.com/technology/technology-ventures.
About OQC
OQC is a global leader in quantum computing-as-a-service, building a brighter future by providing enterprise-ready quantum solutions that seamlessly integrate into digital infrastructures and customer workflows. Its award-winning and world-first integration of quantum computing into colocation facilities removes technical, financial, and geographical barriers to quantum; offering every enterprise a chance to seize a competitive edge. Prior to Series B, OQC raised $52 million including the largest Series A in quantum in the UK at that time. In 2023, OQCs team grew to over 100, attracting talent from across the globe. The team has built and deployed OQC Toshiko platforms to colocation data centers expanding its operations in the UK, Japan and Spain. OQC Toshiko is the worlds first and only enterprise ready platform: a powerful next generation system, deployed to commercial data-centres, enabling businesses to securely tap into ground-breaking technology from anywhere in the world. This new technology is now in private preview and coming soon on public cloud and data centre fabric.
Source: OQC
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ChatGPT Stock Predictions: 3 Quantum Computing Companies the AI Bot Thinks Have 10X Potential – InvestorPlace
Posted: at 2:40 am
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The field ofquantum computingmay be just the next big thing. This novel field has the potential to solve complex problems that generally slow down classical computers, such as optimization, cryptography, machine learning, and simulation. To function, quantum computers use subatomic particles, such as electrons or photons, to represent and manipulate information in quantum bits (qubits). This technique gives quantum computing companies a potential speed advantage over traditional computing, especially for certain types of problems that involve large amounts of data, intricate predictions, cryptography and artificial intelligence, establishing them as leading quantum stocks. Now, we can pick some solid stocks ourselves, but what are the top ChatGPT stock predictions?
Though quantum computing technology may still be in its infancy, that hasnt stopped generative AI bots like ChatGPT from weighing in on which stocks will reap investors a 10 times return. Thus, we created this list of ChatGPT stock predictions.
I asked ChatGPT for its list of top three quantum computing stocks with the most share price return potential, and it came up with the following ChatGPT stock predictions.
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The first company on ChatGPTs list was International Business Machines(NYSE:IBM). Given IBM has benefitted from being one of the most established companies in the tech industry, with a history of innovation and research in various fields, ChatGPTs pick is not so surprising. In the early 2000s, IBM researchers werealready performingquantum computing techniques calculations to solve cryptography problems. IBMs quantum computer consists of superconducting qubits that operate at near-zero temperatures. Similar to Google and other quantum computing players, IBM offers a cloud-based quantum computing service calledIBM Quantum Experience, which allows customers and researchers to access its quantum hardware and software.
In recent years, IBM has endured single-digit revenue growth, including in 2023, but I have always contended that the tech giants innovative edge, especially in quantum computing, could spur revenue growth in the future. This would make IBM a compelling long-term hold. If you want to grab any of these ChatGPT stock predictions, start with this one.
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D-Wave Quantum(NYSE:QBTS) is another well-established quantum computing firm that made ChatGPTs list. The firm specializes inquantum annealing, a computing technique used to find the optimal solution for a given problem. ChatGPT noted that D-Wave quantum computing technique differs from the gate-based techniques that both IBM and Google (NASDAQ:GOOG) employ. The quantum computing firm has successfully built several quantum annealers withmore than 5,000 qubits, which allows greater potential for commercial applications.
The power of D-Wave Quantums annealers and software tools are accessible through the companys cloud platform, Leap. QBTS also offers a suite of developer tools called Ocean, which helps users design, develop, and deploy quantum applications. Most recently, D-Wavereleasedits 1200+ qubit Advantage2 quantum computing machine prototype. Those already subscribed to the D-Wave Leap platform can access the prototype and test out its capabilities.
The market seems excited about D-Wave Quantums prospects. The firms share price has nearly doubled on a year-to-date basis making a 10 times long-term return more of a reality.
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Nvidias(NASDAQ:NVDA) shares are already off to a great start in 2024, so much so that it could be another record year for Nvidias share price. The chipmakers share price has risen more than 66% since the start of trading in January. The chipmaker continues to ride high on the booming demand for its AI solutions, which power some of the most advanced and popular applications in the world, such asOpenAIsChatGPT and other generative AI platforms. Its probably not that much of a surprise ChatGPT included Nvidia on its list of quantum computing stocks with 10X potential.
However, Nvidia is also one of the key players in quantum computing, with itsTensor CoreGPUs used to power some of the most advanced quantum simulators and algorithms. Furthermore, Nvidia has developed its own quantum software development kit and platform calledcuQuantum, which leverages its CUDA programming model and libraries to enable developers to create and run quantum applications on Nvidia GPUs.
I think there is little doubt that when quantum computing eventually takes off, Nvidia could very well rise above the rest.
On the date of publication, Tyrik Torres did not hold (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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