Category Archives: Quantum Computing

In 2011, the movie "Contagion" eerily predicted what a future world fighting a deadly pandemic would look like. In 2020, I, along with hundreds of thousands of people around the world, saw this Hollywood prediction play out by being diagnosed with COVID-19. It was a frightening year by any measure, as every person was impacted in unique ways.

Having been involved in the development of the Internet in the 1970s, Ive seen first-hand the impact of technology on peoples lives. We are now seeing another major milestone in our lifetimethe development of a COVID-19 vaccine.

What the"Contagion" didnt show is what happens after a vaccine is developed. Now, as we enter 2021, and with the first doses of a COVID-19 vaccine being administered, a return to normal feels within reach. But what will our return to normal look like really? Here are threepredictions for 2021.

1. Continuous and episodic Internet of Medical Things monitoring devices will prove popular for remote medical diagnosis. The COVID-19 pandemic has dramatically changed the practice of clinical medicine at least in the parts of the world where Internet access is widely available and at high enough speeds to support video conferencing. A video consult is often the only choice open to patients short of going to a hospital when outpatient care is insufficient. Video-medicine is unsatisfying in the absence of good clinical data (temperature, blood pressure, pulse for example). The consequence is that health monitoring and measurement devices are increasingly valued to support remote medical diagnosis.

My Prediction: While the COVID-19 pandemic persists into 2021, demand for remote monitoring and measurement will increase. In the long run, this will lead to periodic and continuous monitoring and alerting for a wide range of chronic medical conditions. Remote medicine and early warning health prediction will in turn help citizens save on health care costs and improve and further extend life expectancy.

2. Cities will (finally) adopt self-driving cars. Self-driving cars are anything but new, having emerged from a Defense Advanced Research Projects Agency Grand Challenge in 2004. Sixteen years later, many companies are competing to make this a reality but skeptics around this technology remain.

My Prediction: In the COVID-19 aftermath, I predict driverless car service will grow in 2021 as people will opt for rides that minimize exposure to drivers and self-clean after every passenger. More cities and states will embrace driverless technology to accommodate changing transportation and public transportation preferences.

3. A practical quantum computation will be demonstrated. In 2019, Google reported that it had demonstrated an important quantum supremacy milestone by showing a computation in minutes that would have taken a conventional computer thousands of years to complete. The computation, however, did not solve any particular practical problem.

My Prediction: In the intervening period, progress has been made and it seems likely that by 2021, we will see some serious application of quantum computing to solve one or more optimization problems in mechanical design, logistics scheduling or resource allocation that would be impractical with conventional supercomputing.

Despite the challenges 2020 presented, it also unlocked some opportunities like leapfrogging with tech adoption. My hope is that the public sector sustains the speed for innovation and development to unlock even greater advancements in the year ahead.

Vinton G. Cerf is vice president and chief Internet evangelist for Google. Cerf has held positions at MCI, the Corporation for National Research Initiatives, Stanford University, UCLA and IBM. Vint Cerf served as chairman of the board of the Internet Corporation for Assigned Names and Numbers (ICANN) and was founding president of the Internet Society. He served on the U.S. National Science Board from 2013-2018.

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The Year Ahead: 3 Predictions From the 'Father of the Internet' Vint Cerf - Nextgov

ST. LOUIS, Jan. 6, 2021 Harris-Stowe State University has announced a multi-million dollar collaboration with IBM on a comprehensive program designed to develop diverse and high demand skill sets that align with industry needs and trends so both students and faculty can develop the skills they need today for the jobs of tomorrow.

IBM and Harris-Stowe State University are building on the need to advance digital skills in education and are dedicated to providing future focused curriculum and educational tools to help train the diverse workforce of tomorrow in fast-growing technologies such as artificial intelligence (AI), blockchain, data science, cybersecurity, cloud and quantum.

Harris-Stowe State University is thrilled to collaborate with IBM to provide greater access to skills and training in the tech industry, said Dr. Corey S. Bradford, Sr., president of Harris-Stowe State University. As the world, more than ever relies on the use of science, technology, engineering, and mathematics to solve grand societal challenges, Harris-Stowe must continue to develop well prepared and ready graduates to join the STEM workforce. This collaboration is yet another example of our commitment to supporting student and faculty development and assisting in preparing students to compete and lead globally.

The collaboration extends IBMs recent investment in technology, assets, resources and skills development with HBCUs across the United States through the IBM Skills Academy and enhanced IBM Academic Initiative.

Equal access to skills and jobs is the key to unlocking economic opportunity and prosperity for diverse populations, said Valinda Scarbro Kennedy, HBCU Program Lead, IBM Global University Programs. As we announced earlier this fall, IBM is deeply committed to helping HBCU students build their skills to better prepare for the future of work. Through this collaboration, Harris-Stowe State University students will have an opportunity to gain modern skills in emerging technologies across hybrid cloud, quantum and AI so they can be better prepared for the future of work in the digital economy.

As part of its multi-year Global University Programs, which include the IBM Academic Initiative and the IBM Skills Academy, IBM is providing more than $100M in assets, faculty training, pre-built and maintained curriculum content, hands on labs, use cases, digital badges and software to participating HBCUs. The IBM Academic Initiative provides access to resources at no-charge for teaching, learning and non-commercial research with recent enhancements including access to guest lectures. The IBM Skills Academy is a comprehensive, integrated program through an education portal designed to create a foundation of diverse and high demand skill sets that directly correlate to what students will need in the workplace. The learning tracks address topics such as artificial intelligence, cybersecurity, blockchain, data science and quantum computing.

IBMs investment in HBCUs like Harris-Stowe State University is part of the companys dedicated work to promote social justice and racial equality by creating equitable, innovative experiences for HBCU students to acquire the necessary skills to help unlock economic opportunity and prosperity.

About IBM

IBM is a global leader in business transformation, serving clients in more than 170 countries around the world with open hybrid cloud and AI technology. For more information, please visit here.

About Harris-Stowe State University

Harris-Stowe State University (HSSU), located in midtown St. Louis offers the most affordable bachelors degree in the state of Missouri. The University is a fully accredited four-year institution with more than 50 majors, minors and certificate programs in education, business and arts and sciences. Harris-Stowes mission is to provide outstanding educational opportunities for individuals seeking a rich and engaging academic experience. HSSUs programs are designed to nurture intellectual curiosity and build authentic skills that prepare students for leadership roles in a global society.

Source: IBM

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IBM Provides Harris-Stowe State University with $2M in AI, Cloud Resources for Student Skill Building - HPCwire

A multinational team of researchers has developed a photonic processor that uses light instead of electronics and could help usher in a new dawn in computing.

Current computing relies on electrical current passed through circuitry on ever-smaller chips, but in recent years this technology has been bumping up against its physical limits.

To facilitate the next generation of computation-hungry technology such as artificial intelligence and autonomous vehicles, researchers have been searching for new methods to process and store data that circumvent those limits, and photonic processors are the obvious candidate.

Funding boost for UK quantum computing

Featuring scientists from the Universities of Oxford, Mnster, Exeter, Pittsburgh, cole Polytechnique Fdrale (EPFL) and IBM Research Europe, the team developed a new approach and processor architecture.

The photonic prototype essentially combines processing and data storage functionalities onto a single chip so-called in-memory processing, but using light.

Light-based processors for speeding up tasks in the field of machine learning enable complex mathematical tasks to be processed at high speeds and throughputs, said Mnster Universitys Wolfram Pernice, one of the professors who led the research.

This is much faster than conventional chips which rely on electronic data transfer, such as graphic cards or specialised hardware like TPUs [Tensor Processing Unit].

Led by Pernice, the team combined integrated photonic devices with phase-change materials (PCMs) to deliver super-fast, energy-efficient matrix-vector (MV) multiplications. MV multiplications underpin much of modern computing from AI to machine learning and neural network processing and the imperative to carry out such calculations at ever-increasing speeds, but with lower energy consumption, is driving the development of a whole new class of processor chips, so-called tensor processing units (TPUs).

The team developed a new type of photonic TPU capable of carrying out multiple MV multiplications simultaneously and in parallel. This was facilitated by using a chip-based frequency comb as a light source, which enabled the team to use multiple wavelengths of light to do parallel calculations since light has the property of having different colours that do not interfere.

Our study is the first to apply frequency combs in the field of artificially neural networks, said Tobias Kippenberg, Professor at EPFL

The frequency comb provides a variety of optical wavelengths which are processed independently of one another in the same photonic chip.

Described in Nature, the photonic processor is part of a new wave of light-based computing that could fundamentally reshape the digital world and prompt major advances in a range of areas, from AI and neural networks to medical diagnosis.

Our results could have a wide range of applications, said Prof Harish Bhaskaran from the University of Oxford.

A photonic TPU could quickly and efficiently process huge data sets used for medical diagnoses, such as those from CT, MRI and PET scanners.

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Photonic processor heralds new computing era | The Engineer The Engineer - The Engineer

If 2020 had you wishing you could say Beam me up, Scotty, youre not alone. You may be one tiny step closer to getting your wish in a few decades or so.

Scientists from Fermilab, Caltech, NASAs Jet Propulsion Laboratory and the University of Calgary achieved long-distance quantum teleportation in mid-2020, they confirmed in an academic journal article published last month. Its another step toward realizing whats often called quantum computing, and also toward understanding physics on a different level than we do now, perhaps well enough to someday teleport humans. And while there is no ETF specifically for that yet, here are some broad guidelines for thinking about how to invest in very nascent technologies.

For starters, its good to understand the broad contours of the industry supporting the idea. A 2020 market research analysis estimates the quantum computing market will top $65 billion per year by 2030, while a 2019 BCG report makes the case for investing now, rather than waiting for things to take off. As MarketWatch reported in late 2019, quantum computing is expected to remake everything from pharmaceuticals to cybersecurity.

Right now, there are several blue-chip biggies involved in the quantum race. Scientists from AT&T were involved in the 2020 experiments, and big companies like Microsoft MSFT, -2.13%, Tencent TCEHY, +1.34%, and IBM IBM, -1.54% all have initiatives.

Its easy enough to find exchange-traded funds with big holdings of those giants likely easier than finding publicly-traded small companies on the bleeding edge of these technologies but its also important to remember how small a share of their revenues experimental ventures like these are.

There are still some good models for funds constructed around developing industries like this one, noted Todd Rosenbluth, head of mutual fund and ETF research at CFRA. One is the Procure Space ETF UFO, -1.49%, which sports the ticker UFO. UFO launched before Virgin Galactic SPCE, -2.19% went public, at a moment when it was hard to call it a true pure-play space fund. As MarketWatch noted at the time, UFO is composed of companies involved in existing space-related business lines: ground equipment manufacturing that uses satellite systems, rocket and satellite manufacturing and operation, satellite-based telecommunications and broadcasting, and so on.

The one ETF that might now be said to be closest to offering access to quantum technology takes a similar approach. The Defiance Quantum ETF QTUM, +0.71% has quantum in its name, but says it provides exposure to companies on the forefront of cloud computing, quantum computing, machine learning, and other transformative computing technologies.

Another consideration might be an ETF specializing in very early-stage technology. In December, MarketWatch profiled the Innovator Loup Frontier Technology ETF LOUP, -0.08%. Rosenbluth has also been watching the Direxion Moonshot Innovators ETF MOON, -0.66%.

Disruptive technology themes have gotten a boost from one of biggest success stories of 2020, he said in an interview. ARK Invests fund lineup took in billions of dollars and enjoyed triple-digit gains as their bets on technology had a moment.

The next-gen narrative seems to resonate with investors, and complex themes like these make a good case for investing in actively-managed funds that benefit from researchers expertise. That means that when it succeeds, Theres a snowball effect of investors coming to see the benefits of using ETFs for these kinds of themes, Rosenbluth said.

I think the future is bright for these types of ETFs, Rosenbluth told MarketWatch. Theres less white space in the ETF world than there was before, but its inevitable that there will be a teleportation-related ETF.

Read next: What will 2021 bring for ETFs?

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Quantum computing is so last-decade. Get ready to invest in the final frontier... teleportation - MarketWatch

Quantum computing has opened multiple doors of possibilities for quick and accurate computation for complex problems, something which traditional methods fail at doing. The pace of experimentation in quantum computing has very naturally increased in recent years. 2020 too saw its share of such breakthroughs, which lays the groundwork for future innovations. We list some of the significant quantum computing projects and experiments of 2020.

IT services company Atos devised Q-Score for measuring quantum performance. As per the company, this is the first universal quantum metric that applies to all programmable quantum processors. The company said that in comparison to qubits, the standard figure of merit for performance assessment, Q-Score provides explicit, reliable, objective, and comparable results when solving real-world optimisation problems.

The Q-Score is calculated against three parameters: application-driven, ease of use, and objectiveness and reliability.

Googles AI Quantum team performed the largest chemical simulation, to date, on a quantum computer. Explaining the experiment in a paper titled, Hartree-Fock on a superconducting qubit quantum computer, the team said it used variational quantum eigensolver (VQE) to simulate chemical mechanisms using quantum algorithms.

It was found that the calculations performed in this experiment were two times larger than the previous similar experiments and contained about ten times the number of quantum gate operations.

The University of Sydney developed an algorithm for characterising noise in large scale quantum computers. Noise is one of the major obstacles in building quantum computers. With this newly developed algorithm, they have tried to tame the noise by reducing interference and instability.

A new method was introduced to return an estimate of the effective noise with relative precision. The method could also detect all correlated errors, enabling the discovery of long-range two-qubit correlations in the 14 qubit device. In comparison, the previous methods would render infeasible for device size above 10 qubits.

The tool is highly scalable, and it has been tested successfully on the IBM Quantum Experience device. The team believes that with this, the efficiency of quantum computers in solving computing problems will be addressed.

Canadian quantum computing D-Wave Systems announced the general availability of its next-generation quantum computing platform. This platform offers new hardware, software, and tools for accelerating the delivery of quantum computing applications. The platform is now available in the Leap quantum cloud service and has additions such as Advantage quantum system with 5000 qubits and 15-way qubit connectivity.

It also has an expanded solver service that can perform calculations of up to one million variables. With these capabilities, the platform is expected to assist businesses that are running real-time quantum applications for the first time.

Physicists at MIT reported evidence of Majorana fermions on the surface of gold. Majorana fermions are particles that are theoretically their own antiparticle; it is the first time these have been observed on metal as common as gold. With this discovery, physicists believe that this could prove to be a breakthrough for stable and error-free qubits for quantum computing.

The future innovation in this direction would be based on the idea that combinations of Majorana fermions pairs can build qubit in such a way that if noise error affects one of them, the other would still remain unaffected, thereby preserving the integrity of the computations.

In December, Intel introduced Horse Ridge II. It is the second generation of its cryogenic control chip, considered a milestone towards developing scalable quantum computers. Based on its predecessor, Horse Ridge I, it supports a higher level of integration for the quantum systems control. It can read qubit states and control several gates simultaneously to entangle multiple qubits. One of its key features is the Qubit readout that provides the ability to read the current qubit state.

With this feature, Horse Ridge II allows for faster on-chip, low latency qubit state detection. Its multigate pulsing helps in controlling the potential of qubit gates. This ability allows for the scalability of quantum computers.

I am a journalist with a postgraduate degree in computer network engineering. When not reading or writing, one can find me doodling away to my hearts content.

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Major Quantum Computing Projects And Innovations Of 2020 - Analytics India Magazine

Mergingquantum computing with artificial intelligence (AI)has been on the priority list for researchers and scientists. Even though quantum computing is still in the early phases of development, there have been many innovations and breakthrough. However, it is still unclear on whether the world will change for good or bad when AI is totally influenced by quantum computing.

Quantum computingis similar to traditional computing. It relies on bits, which are 0s and 1s to encode information. The data keeps growing despite limiting it. Moores law has observed that the number of transistors on integrated circuits wills double every two years, making way for tech giants to run the race of making the smallest chips. This has also induced tech companies to compete for the first launch of a viable quantum computer that would be exponentially more powerful than todays computers. The futuristic computer will process all the data we generate and solve increasingly complex problems.

Remarkably, the use ofquantum algorithms in artificial intelligencetechniques will boost machines learning abilities. This will lead to improvements in an unprecedented way. The main goal of the merger is to achieve a so-calledquantum advantage, where complex algorithms can be calculated significantly faster than with the best classical computer. The expected change will be a breakthrough in AI. Experts and business leaders predict thatquantum computings processing powercould begin to improve AI systems within about five years. However, combining AI and quantum is considered scary from an angle. The late researcher and scientist Stephen Hawking has said that the development of full AI could spell the end of the human race. Once humans develop AI, it will take off on its own and redesign itself at an ever-increasing rate. Humans, who are limited by slow biological evolution couldnt compete and would supersede.

Can solve complex problems quickly

One of the major expectations that people have fromquantum computingis to have increased computational skill. It is predicted that quantum computers will be able to complete calculations within seconds that would take thousands of years to calculate. Google claims that the company has a quantum computer that is 100 million times faster than any existing computer. This futuristic and quick way of calculating will solve all the data problems in minutes if not seconds. The key to availing the transition is by converting all the existing data into quantum language.

Enhance warfighter capabilities

Even though the improvement of quantum computing is in the initial stage, it is expected to enhance warfighter capabilities significantly in the future. It is predicted that quantum computing is likely to impact ISR (intelligence, surveillance and reconnaissance), solving logistic problems more quickly. While we know the types of problems and general application space, optimisation problems will be some of the first where we will see advantages.

Applications in the banking sector

Malpractice and constant forgeries are common in the banking and financial sector. Fortunately, the combination of AI with quantum computing might help improve and combat fraud detection. Models trained using a quantum computer will be capable of detecting patterns that are hard to spot using conventional equipment. Meanwhile, the acceleration of algorithms will yield great advantages in terms of the volume of information that the machines handle for this purpose.

Help integrate data from different datasets

Quantum computers are anticipated to be experts in merging different datasets. Although this seems quite impossible without human intervention in the initial phase, computers will eventually learn to integrate data in the future. Henceforth, if there are different raw data sources with unique schema attached to them and a research team wants to compare them, a computer would have to understand the relationship between the schemas before the data could be compared.

All is not good though

In some way, AI and quantum computing worry people with an equal amount of expectations it gives. Quantum computing technology will be very futuristic, but we cant assure you that it is human-friendly. It could be far better than humans suppressing people in their jobs. Quantum computing also poses athreat to security. The latest Thales Data Threat report says that 72% of surveyed security experts worldwide believe quantum computing will have a negative impact on data security within the next five years.

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Quantum Computing Entwined with AI is Driving the Impossible to Possible - Analytics Insight