Category Archives: Quantum Computing

Finlands VTT Technical Research Centre has formed a strategic collaboration with tech startup IQM Group to build the countrys first quantum computer.

The VTT-IQM co-innovation partnership aims to deliver a 50-qubit machine by 2024, drawing on international quantum technology expertise to augment Finlands home-grown quantum capabilities.

The partnership combines VTTs expertise in supercomputing and networking systems with IQMs capacity to deliver a hardware stack for a quantum computer while working with VTT to integrate critical technologies.

The financing element of the project saw IQM launch a new series A funding round in November. The Helsinki-headquartered company raised 39m in new capital in the funding round, bringing to 71m the total amount raised by IQM for quantum computing-related research and development (R&D) project activities to date.

State-owned VTT is providing financing for the project in the form of grants totalling 20.7m from the Finnish government.

Micronova, a national research and development infrastructure resource operated jointly by VTT and Aalto University, will provide the clean room environment to build the quantum computer and associated components at a dedicated facility at Espoo, southwest of Helsinki. The build will use Micronovas specialised input and micro- and nanotechnology expertise to guide the project.

The project marks the latest phase in cooperation between VTT and Aalto University. The two partners are also involved in a joint venture to develop a new detector for measuring energy quana. As measuring the energy of qubits lies at the core of how quantum computers operate, the detector project has the potential to become a game-changer in quantum technology.

IQMs collaborative role with VTT emerged following an international public tender process. All partners expect to see robust advances in the quantum computing project in 2021, said Jan Goetz, CEO of IQM.

This project is extremely prestigious for us, said Goetz. We will be collaborating with leading experts from VTT, so this brings a great opportunity to work together in ways that help build the future of quantum technologies.

Finlands plan to build a 50-qubit machine stacks up reasonably well in terms of ambition and scope, compared with projects being run by global tech giants Google and IBM.

In 2019, Google disclosed that it had used its 53-qubit quantum computer to perform a calculation on an unidentified unique abstract problem that took 200 seconds to accomplish. Google, which hopes to build a one million-qubit quantum computer within 10 years, estimated that it would have taken the worlds most powerful supercomputer, at the time, 10,000 years to resolve and complete the same calculation.

For its part, IBM is engaged in a milestone project to build a quantum computer comprising 1,000 qubits by 2023. IBMs largest current quantum computer contains 65 qubits.

The VTT-IQM project will proceed in three stages. The first will involve the construction of a five-qubit computer by the year of 2021. The project will then be scaled up in 2022, parallel with enhancement of support infrastructure, to deliver the target 50-qubit machine in 2023.

Our focus is more on how effectively we use the qubits, rather than the number, said Goetz. We expect, that by 2024, we will be in a place where there is a high likelihood of simulating several real-world problems and start finding solutions with a quantum computer.

For instance, conducting quantum material simulations for chemistry applications such as molecule design for new drugs, or the discovery of chemical reaction processes to achieve superior battery and fertiliser production.

The Finnish governments direct funding of the project is driven by a broader mission to further elevate the countrys reputation as a European tech hub and computing superpower, said Mika Lintil, Finlands economic affairs minister.

We want Finland to harness its potential to become the European leader in quantum technologies, he added. By having this resource, we can explore the opportunities that quantum computing presents to Finnish and European businesses. We see quantum computing as a dynamic tool to drive competitiveness across the whole of the European Union.

Within VTT, the quantum computing project will run parallel with connected areas of application, including quantum sensors and quantum-encryption algorithms. Quantum sensors are becoming increasingly important tools in medical imaging and diagnostics, while quantum-encryption algorithms are being deployed more widely to protect information networks.

Quantum computing-specific applications have the capacity to empower businesses to answer complex problems in chemistry and physics that cannot be solved by current supercomputers, said VTT CEO Antti Vasara.

Investing in disruptive technologies like quantum computing means we are investing in our future ability to solve global problems and create sustainable growth, he said. Its a machine that has immense real-world applications that can make the impossible possible. It can be used to simulate or calculate how materials or medicinal drugs work at the atomic level.

In the future, quantum technologies will play a significant role in the accelerated development and delivery of new and critical vaccines.

Finlands advance into quantum computing will further enhance Helsinkis status as a Nordic and European hub for world-leading innovative ecosystems dedicated to new technologies.

The project will also bolster IQMs capacity to build Europes largest industrial quantum hardware team to support projects across Europe, said Goetz.

IQM established a strategic presence in Germany in 2020, following the German governments commitment to invest 2bn in a project to build two quantum computers.

We are witnessing a boost in deep-tech funding in Europe, said Goetz. Startups like us need access to three channels of funding to ensure healthy growth. We need research grants to stimulate new key innovations and equity investments to grow the company. We also require early adoption through acquisitions supported by the government. This combination of funding enables us to pool risk and create a new industry.

IQMs initial startup funding included a 3.3m grant from Business Finland, the governments innovation financing vehicle, in addition to 15m equity investment from the EIC (European Innovation Council) Accelerator programme.

The 71m harvested by IQM in 2020 ranks among the highest capital fund raising rounds by a European deep-tech startup in such a short period.

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Tech partnership to drive Finlands quantum computing project - ComputerWeekly.com

The year 2020 was profoundly challenging for citizens, companies, and governments around the world. As covid-19 spread, requiring far-reaching health and safety restrictions, artificial intelligence (AI) applications played a crucial role in saving lives and fostering economic resilience. Research and development (R&D) to enhance core AI capabilities, from autonomous driving and natural language processing to quantum computing, continued unabated.

Baidu was at the forefront of many important AI breakthroughs in 2020. This article outlines five significant advances with implications for combating covid-19 as well as transforming the future of our economies and society.

The trendand why it matters. It typically takes years, if not decades, to develop a new vaccine. But by March 2020, vaccine candidates to fight covid-19 were already undergoing human tests, just three months after the first reported cases. The record speed of vaccine development was partly thanks to AI models that helped researchers analyze vast amounts of data about coronavirus.

There are tens of thousands of subcomponents to the outer proteins of a virus. Machine learning models can sort through this blizzard of data and predict which subcomponents are the most immunogenici.e., capable of producing an immune responseand thereby guide researchers in designing targeted vaccines. The use of AI in vaccine development may revolutionize the way all vaccines are created in the future.

Baidus innovations. In February, Baidu opened its LinearFold AI algorithm for scientific and medical teams working to fight the virus. LinearFold predicts the secondary structure of the ribonucleic acid (RNA) sequence of a virusand does so significantly faster than traditional RNA folding algorithms. LinearFold was able to predict the secondary structure of the SARS-CoV-2 RNAsequence in only 27 seconds, 120 times faster than other methods. This is significant, because the key breakthrough of covid-19 vaccines has been the development of messenger RNA (mRNA) vaccines. Instead of conventional approaches, which insert a small portion of a virus to trigger a human immune response, mRNA teaches cells how to make a protein that can prompt an immune response, which greatly shortens the time span involved in development and approval.

To support mRNA vaccine development, Baidu later developed and released an AI algorithm for optimizing mRNA sequence design called LinearDesign, which aims to solve the problem of unstable and unproductive mRNA sequences in candidate vaccines.

In addition to opening up access to LinearFold and LinearDesign for researchers around the world, Baidu also formed a strategic partnership with the National Institute for Viral Disease Control and Prevention, part of the Chinese Center for Disease Control and Prevention. Following an outbreak at Beijings Xinfadi market in June, Baidus AI technology allowed authorities to complete genome sequencing of the coronavirus strain within 10 hours, helping curb the outbreak. In December, Baidu unveiled PaddleHelix, a machine learning-based bio-computing framework aimed at facilitating the development of vaccine design, drug discovery, and precision medicine.

The trendand why it matters. Autonomous driving technology continued to mature in 2020, with the industrys leading companies testing driverless cars and opening up robotaxi services to the public in various cities. Fully automated driving, which enables rides without a human safety driver on board, will be necessary for the scalability and commercialization of autonomous driving.

Baidus innovations. Over the past year, Baidu launched the Apollo Go Robotaxi service in the Chinese cities of Changsha, Cangzhou, and Beijingincluding in busy commercial areasbecoming the only company in China to start robotaxi trial operations in multiple cities.

These developments are a result of Baidus continuous innovation in developing AI systems that can safely control a vehicle in complex road conditions and solve the majority of possible issues on the road, independent of a human driver.

At Baidu World 2020, its annual technology conference, Baidu also demonstrated its fully automated driving capabilitywhere the AI system drives independently without an in-vehicle safety driver. To support fully automated driving, Baidu developed the 5G Remote Driving Service, a safety measure whereby remote human operators can take control of a vehicle in the event of an exceptional emergency. Baidus achievement of fully automated driving, and the rollout of its robotaxis, suggests a positive outlook for the commercialization of the technology in the near future.

The trendand why it matters. In 2020, natural language systems became significantly more advanced at processing aspects of human language like sentiment and intent, generating language that aligns with human speaking and writing patterns, and even visual understanding, meaning the capability to express understanding about an image through language. These natural language models are powering more accurate search results and more sophisticated chatbots and virtual assistants, leading to better user experiences and creating value for businesses.

Baidus innovations. Baidu released a new multiflow sequence framework for language generation called ERNIE-GEN. By training the model to predict semantically complete blocks of text, ERNIE-GEN performs at an elite level across a range of language generation tasks, including dialogue engagement, question generation, and abstractive summarization.

Baidus vision-language model ERNIE-ViL also achieved significant progress in visual understanding, ranking first on the VCR leaderboard, a dataset of 290,000 questions built by the University of Washington and the Allen Institute for AI, that aims to test visual understanding ability. ERNIE-ViL also achieved state-of-the-art performance on five vision-language downstream tasks. Visual understanding lays the foundation for computer systems to physically interact in everyday scenes, as it involves both understanding visual content and expressing it through language. It will be crucial for improving the quality of human-machine interaction.

The trendand why it matters. Quantum computing made significant inroads in 2020, including the Jiuzhang computers achievement of quantum supremacy. This carries significance for AI, since quantum computing has the potential to supercharge AI applications compared to binary-based classical computers. For example, quantum computing could be used to run a generative machine learning model through a larger dataset than a classical computer can process, thus making the model more accurate and useful in real-world settings. Advanced technologies such as deep learning algorithms are also playing an increasingly critical role in the development of quantum computing research.

Baidus innovations. Baidu achieved a number of technical breakthroughs in 2020 that promise to bridge AI and quantum computing. In May, Baidu launched Paddle Quantum, a quantum machine learning development toolkit that can help scientists and developers quickly build and train quantum neural network models and provide advanced quantum computing applications. The open-source toolkit both supports developers building quantum AI applications, and helps deep learning enthusiasts develop quantum computing. In September, Baidu entered cloud-based quantum computing with the launch of Quantum Leaf, which provides quantum development kits such as QCompute, and can shorten the life cycle of quantum programming and help realize a closed-loop quantum tool chain.

The trendand why it matters. AI hardware continued to develop in 2020, with the launch of several AI chips customized for specialized tasks. While an ordinary processor is capable of supporting AI tasks, AI-specific processors are modified with particular systems that can optimize performance for tasks like deep learning. As AI applications become more widespread, any increase in performance or reduction in cost can unlock more value for companies that operate a wide network of data centers for commercial cloud services, and can facilitate the companys internal operations.

Baidus innovations. At Baidu World 2020, the company offered a glimpse into its next-generation AI processor, the Kunlun 2, which it plans to put into mass production in early 2021. The chip uses 7 nanometer (nm) processing technology and its maximum computational capability is over three times that of the previous generation, the Kunlun 1. The Kunlun chips are characterized by high performance, low cost, and high flexibility, which can support a broad range of AI applications and scenarios, helping foster greater AI adoption and reducing usage costs. More than 20,000 Kunlun 1 chips have now been deployed to support Baidus search engine and Baidu Cloud partners since they launched in 2018, empowering industrial manufacturing, smart cities, smart transportation, and other fields.

This content was produced by Baidu. It was not written by MIT Technology Reviews editorial staff.

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These five AI developments will shape 2021 and beyond - MIT Technology Review

An IBM patent shows a hexagonal array of qubits in a quantum computer, arranged to minimize problems controlling the finicky data processing elements.

IBM secured 9,130 US patents in 2020, more than any other company as measured by an annual ranking, and this year quantum computing showed up as part of Big Blue's research effort. The company wouldn't disclose how many of the patents were related to quantum computing -- certainly fewer than the 2,300 it received for artificial intelligence work and 3,000 for cloud computing -- but it's clear the company sees them as key to the future of computing.

The IFI Claims patent monitoring service compiles the list annually, and IBM is a fixture at the top. The IBM Research division, with labs around the globe, has for decades invested in projects that are far away from commercialization. Even though the work doesn't always pay dividends, it's produced Nobel prizes and led to entire industries like hard drives, computer memory and database software.

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"A lot of the work we do in R&D really is not just about the number of patents, but a way of thinking," Jerry Chow, director of quantum hardware system development, said in an exclusive interview. "New ideas come out of it."

IFI's US patent list is dominated by computer technology companies. Second place went to Samsung with 6,415 patents, followed by Canon with 3,225, Microsoft with 2,905 and Intel with 2,867. Next on the list are Taiwan Semiconductor Manufacturing Corp., LG, Apple, Huawei and Qualcomm. The first non-computing company is Toyota, in 14th place.

Internationally, IBM ranked second to Samsung in patents for 2020, and industrial companies Bosch and General Electric cracked the top 10. Many patents are duplicative internationally since it's possible to file for a single patent in 153 countries.

Quantum computing holds the potential to tackle computing problems out of reach of conventional computers. During a time when it's getting harder to improve ordinary microprocessors, quantum computers could pioneer new high-tech materials for solar panels and batteries, improve chemical processes, speed up package delivery, make factories more efficient and lower financial risks for investors.

Industrywide, quantum computing is a top research priority, with dozens of companies investing millions of dollars even though most don't expect a payoff for years. The US government is bolstering that effort with a massive multilab research effort. It's even become a headline event at this year's CES, a conference that more typically focuses on new TVs, laptops and other consumer products.

"Tactical and strategic funding is critical" to quantum computing's success, said Hyperion Research analyst Bob Sorensen. That's because, unlike more mature technologies, there's not yet any virtuous cycle where profits from today's quantum computing products and services fund the development of tomorrow's more capable successors.

IBM has taken a strong early position in quantum computing, but it's too early to pick winners in the market, Sorensen added.

The long-term goal is what's called a fault tolerant quantum computer, one that uses error correction to keep calculations humming even when individual qubits, the data processing element at the heart of quantum computers, are perturbed. In the nearer term, some customers like financial services giant JPMorgan Chase, carmaker Daimler and aerospace company Airbus are investing in quantum computing work today with the hope that it'll pay off later.

Quantum computing is complicated to say the least, but a few patents illustrate what's going on in IBM's labs.

Patent No. 10,622,536 governs different lattices in which IBM lays out its qubits. Today's 27-qubit "Falcon" quantum computers use this approach, as do the newer 65-qubit "Hummingbird" machines and the much more powerful 1,121-qubit "Condor" systems due in 2023.

A close-up view of an IBM quantum computer. The processor is in the silver-colored cylinder.

IBM's lattices are designed to minimize "crosstalk," in which a control signal for one qubit ends up influencing others, too. That's key to IBM's ability to manufacture working quantum processors and will become more important as qubit counts increase, letting quantum computers tackle harder problems and incorporate error correction, Chow said.

Patent No. 10,810,665 governs a higher-level quantum computing application for assessing risk -- a key part of financial services companies figuring out how to invest money. The more complex the options being judged, the slower the computation, but the IBM approach still outpaces classical computers.

Patent No. 10,599,989 describes a way of speeding up some molecular simulations, a key potential promise of quantum computers, by finding symmetries in molecules that can reduce computational complexity.

Most customers will tap into the new technology throughquantum computing as a service. Because quantum computers typically must be supercooled to within a hair's breadth of absolute zero to avoid perturbing the qubits, and require spools of complicated wiring, most quantum computing customers are likely to tap into online services from companies like IBM, Google, Amazon and Microsoft that offer access to their own carefully managed machines.

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Quantum computing research helps IBM win top spot in patent race - CNET

90 entrepreneurs and researchers from the Netherlands want to solve all the world's problems with collaboration and innovation.

The Lightyear One charges its own batteries via five square meters of solar panels built into the car itself.

Image: Lightyear One

The 90 Dutch companies in the NL Tech Pavilion at CES 2021 represent every possible use of technology as a problem-solving tool, from air quality and cars to sustainability and violence.

This collection of companies is one of the largest private sector delegations at this year's virtual CES.

The companies represent 13 sectors including advanced materials; artificial intelligence, big data and quantum computing; energy power and climate change; enterprise solutions; robotics and future work; digital health and wellness; cybersecurity and resilience; smart cities and mobility; sustainability and circularity; and 5G, IoT sensors, photonics and nanotech.

This year, Dutch organizers wanted to highlight how companies must work together to create economic, environmental, and social change by using partnerships between government, private and public companies, and research and knowledge institutions.

SEE: CES 2021: The big trends for business (ZDNet/TechRepublic special feature)

The quantum computing contingent at CES is one example of that collaboration. In addition to three companies, the Pavilion is hosting Quantum Delta NL as well. The organization supports networking among researchers and educational efforts around quantum computing.

"As global power players race toward building the first quantum computer, we continue to encourage productive collaboration between Dutch research institutes like QuTech, our national ecosystem for excellence Quantum Delta and groundbreaking startups like Qblox who all play an equally essential role in establishing the Netherlands as a leader in the evolution of quantum innovation," said Mona Keijzer, State Secretary for Economic Affairs and Climate Policy.

These six companies in the delegation are working in artificial intelligence, data centers, energy use, digital health, blockchain, and solar-powered cars:

Here's a look at how these six companies are using technology to solve old and new problems.

Incooling and Lightyear are taking on energy use in two different sectors. Incooling SVC is a compressor-based cooling system to cool high-performance servers by focusing on the CPU. This closed-loop system can be inserted directly into servers, according to the company, and can respond quickly to changing temperatures. The system uses two-phase cooling. With this system, the coolant is heated and subjected to phase change. This means that when the cooling material is heated to the boiling point, it can change from a liquid to a gas. This allows the cooling system to absorb more heat.

The Lightyear One charges its own batteries via five square meters of solar panels built into the car itself. The solar cells on the hood and the roof are encased in safety glass. The car also has four independent in-wheel motors that provide power when and where it is needed. This long-range solar electric car is two to three times more energy efficient than the current crop of electric vehicles, according to the company. Lightyear One uses 83 watts per kilometer, which will cover a range of 725 kilometers, or 450 miles. The Lightyear One goes on sale in late 2021 in Europe for 150,000 euros, or about $182,395.

Oddity is working on a commercial violence recognition algorithm with advanced deep learning techniques. The algorithm monitors video feeds in real time to watch for potential violence and alert security officers. The company claims the system has a detection speed of less than half a second. The company also states that the algorithms analyze subjects in full anonymity and deploy on premises to protect privacy.

Verisign reports that there are about 330 million registered domain names but a significant portion of those are not active. Dan.com is using blockchain to make it easier for businesses and individuals to find, buy, and transfer these unused domains. Dan.com used IBM's blockchain technology to automate domain name processes such as transferring a name to a new owner and to power new services such as domain name rental and lease to own.

Music has the power to influence emotions and AlphaBeats is using that power to help individuals relax. The company's app measures stress via breathing, heart rate variability, and brainwaves. The sound quality from the ear buds changes based on the level of stress the biofeedback algorithms detect. As a person relaxes, the quality of the music improves. AlphaBeats is licensing a neurofeedback algorithm from Philips to power the app. AlphaBeats claims that 10 minute training sessions will help users train themselves to relax on command. The company is signing up beta testers for the iOS and Android apps.

Breath in Balanz also wants to train users to be healthier and its focus is breathing. The coaching system uses an app and a belt to improve breathing patterns to prevent hyperventilation. Breathing too shallowly or too fast can affect a person's overall health, including sleep and heart conditions. Breath in Balanz offers an 80-day training program that is divided into seven segments. The idea is to train the variety of muscles used to breathe via the app and a sensor.

The Netherlands Pavilion includes a quantum computing cohort this year with three companies and one industry organization attending. Orange Quantum System helps R&D labs with quantum research. Qblox is advancing quantum technology with scalable and low-latency qubit control equipment. Quantum Inspire is a multi-hardware quantum technology platform.

Quantum Delta NL supports the broader quantum ecosystem by encouraging collaboration among the country's five major quantum research hubs, strengthening large-scale facilities across the country for nanotech research, and accelerating education efforts to support a quantum economy. The organization's catalyst programs include building the first European quantum computing platform, establishing a national quantum network, and supporting companies that could build quantum sensing applications. Intel's quantum researchers work with the Dutch company QuTech to test quantum chips that the hardware company is developing.

Our editors highlight the TechRepublic articles, downloads, and galleries that you cannot miss to stay current on the latest IT news, innovations, and tips. Fridays

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You can find a $180K solar-powered car, qubit controls, and breathing tips at the NL Tech Pavilion at CES 2021 - TechRepublic

The plans have been adjusted a bit for virtual participation, but all systems are go for Research Week 2021 at Duke, Jan. 25-29.

This first-ever event will include the inaugural Ingrid Daubechies Lecture and updates from Duke researchers working on the frontiers of political science, Covid, Quantum computing, CRISPR gene editing and artificial intelligence. Participants can earn some Responsible Conduct of Research training credits and hear a sampling of work from our students and postdocs.

The Office of Research, which is hosting the event, will also be unveiling a powerful new platform for research planning and administration, myRESEARCHsuite.

And the Office of Licensing and Ventures will be hosting its annual showcase of Duke-grown startup companies.

This is a sort of a celebration, said Vice President for Research Larry Carin. Dukes researchers, from senior faculty to undergraduates, have risen above the challenges faced in this new world of social distancing, infectious disease controls, and surveillance testing.

Duke Research Week is an opportunity to showcase the extraordinary research accomplishments our faculty and students achieved under unimaginable challenges and constraints, Carin said.

Monday, Jan. 25: SARS-CoV-2 testing and modeling; Young voters in 2021 and beyond.

Tuesday, Jan. 26: Introduction to myRESEARCHsuite; Daubechies Lecture: Waves: Building Blocks in Nature and Mathematics, with Gigliola Staffilani of MIT; Grad student and postdoc mini-talks.

Wednesday, Jan. 27: FlyRDU design challenge winners; Undergraduate research virtual poster session; Research Town Hall Fundamentals of the Scientific Process panel discussions; Invented at Duke showcase.

Thursday, Jan. 28: Introduction to the Duke Quantum Center; The Human genome and CRISPR technologies.

Friday, Jan. 29: Artificial Intelligence and Health, a half-day symposium in three parts.

Registration is required to access the online content. Please see https://dukeresearchweek.vfairs.com/

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Research Week Features Hot Topics and New Tools - Duke Today

In one of the most significant departures from the Trump Administration, President-elect Joe Biden vowed to make science a central theme of his administration enlisting scientists to solve problems at home and across the globe, and giving them unprecedented influence in his administration.

As president, Ill pay great attention to science and scientists, Biden said January 16 in an online briefing introducing his team of top five science advisors. He confirmed his plan to name his chief scientific advisor, geneticist Eric Lander, to cabinet-level rank the first time in US history, because we think its that important.

He also said he will focus his administrations scientific efforts on five main issues: the pandemic, the economy and economic equality, the climate crisis, technological and industrial leadership, and restoring trust in science.

In a similar vein, a day earlier when discussing his COVID-19 plans, Biden vowed that our administration will lead with science and scientists, with a CDC, an NIH, that will be free, totally free from political influence, a surgeon general who is independent, an FDA whose decisions are based on science and science alone. The Centres for Disease Control, National Institutes of Health and Food and Drug Administration became political casualties of the Trump Administrations fumbling pandemic response, as political appointees frequently overruled career scientists.

A signal to the world

Taken together, the five appointments and the impassioned rhetoric send a powerful signal to other world leaders that there will be a new boss and a new agenda in Washington from noon on January 20, Inauguration Day. In several capitals, expectations have risen for the US returning to its former prominent role on global climate policy, health research, environmental protection. Indeed, some have started calling for a global summit on science, to better coordinate how humanity should respond to those issues, and the impact of emerging technologies like artificial intelligence and quantum computing.

Certainly, watching the Biden briefings over the weekend, an observer couldnt help but be struck by the contrast with the departing Trump Administration. Trump famously called climate science a Chinese hoax, speculated aloud about the possibility of administering bleach to COVID patients, took a felt-tip marker to a government weather map to make a hurricanes path appear less threatening, and enacted a long series of administrative changes that downgraded the impact of scientific evidence on US policy in many domains.

By contrast, we are going to make sure the United States of America once again leads the way in science and innovation, said Kamala Harris, the vice president-elect, at the briefing.

Echoing Bidens enthusiasm for the scientific appointments, Harris joked that she and Biden can nerd out a little at times. She went on to describe how she learned from her mother, an endocrinologist, about the scientific method as a way of life, of forming a hypothesis and recognising that its not a failure to revaluate that hypothesis when the facts dont add up making a decision based not on ideology but on evidence.

So far, the full sweep of Bidens planned science-related policies arent yet clear though he has in the past month laid out specific new measures, based on scientific advice, to tackle the pandemic, improve environmental protection and revive and restructure the economy.

A slim Democratic majority in the House of Representatives, and a 50-50 Democratic-Republican split in the Senate (with Harris as the tie-breaker), will permit many changes. And his executive powers to enact change especially in the inner workings of key agencies like the FDA and the departments of energy and agriculture are extensive. But the Democratic party itself is riven by internal dissension, and the chance of bipartisan agreement diminished greatly after the House voted to impeach Trump for an historic second time last week.

Science for equality

A few messages came clearly through the Biden science briefings. One was on the need to apply science to helping fix Americas appalling inequalities of income and race. Alondra Nelson, a Princeton University social scientist who was named Bidens deputy science advisor, said that science at its core is a social phenomenon, a reflection of the people. How we build AI algorithms, provide health care, are human choices. It matters who makes these choicesAs a Black woman researcher, I am keenly aware of who is missing from such decisions at present.

Likewise, Landers, the new chief science advisor, said we have to be sure not only that everybody has a seat at the table, but a place at the lab bench.

Another theme was listening to science to improve the chaotic US pandemic response. At the Jan. 15 briefing on COVID, Biden said that from the moment of his inauguration he will make mask-wearing mandatory on federal property, and on interstate planes and trains. Mask wearing, he said, has become a partisan issue. But what a stupid, stupid thing for it to happen. He said wearing masks in his first 100 days could save 50,000 lives.

Referring to the Capital siege in which legislators were forced to shelter together some with, and some without, masks, Biden called it shocking to see members of Congress refuse to wear masks. What the hells the matter with you?

Of the five top science appointees, most are familiar faces from the Obama Administration and in one case, from both the Trump and Obama eras:

Eric S. Lander, presidential science advisor and director of the Office of Science and Technology Policy (OSTP). A leader of the successful 1990s US Human Genome Project that sequenced the first full human genome, and currently head of the Broad Institute, a genetics research centre run jointly by Harvard University and the Massachusetts Institute of Technology. Also, in the Obama-Biden administration, co-chair of the Presidents Council of Advisors on Science and Technology.

Alondra Nelson, OSTP deputy director for science and society. Currently president of the Social Science Research Council and a sociology professor at Princetons Institute for Advanced Study.

Frances H. Arnold, co-chair of the Presidents Council of Advisors on Science and Technology. A California Institute of Technology professor who in 2018 was the first American woman to win a Nobel in chemistry. She co-founded three biotech companies and is a director of Alphabet, the parent company of Google currently fighting antitrust charges from the US Department of Justice.

Maria Zuber, co-chair of the Presidents Council of Advisors on Science and Technology. A geophysicist who is currently MIT vice president for research, and head of MITs famous Lincoln Laboratory. She has been involved in scientific aspects of 10 US space missions. She was named in 2013 by then-President Obama to the National Science Board, and was reappointed under Trump as board chair from 2016 to 2018.

Francis S. Collins, director of the National Institutes of Health. A hold-over from the Trump Administration, and first named to the post in 2009 by then-President Obama. He is a physician and geneticist, who was also with Lander a leader of the Human Genome Project.

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Biden puts science at the top of his agenda - Science Business

Dell Technologies have presented what they think about the year 2021 in terms of technologies and the companys view and strategy towards said elements.

For the main discussions, they have shared their insights, analytics, and predictions for the top 4 emerging technologies of 2021, namely quantum computing, silicon chips, 5G, multi-cloud edge solutions.

For starters, the company recognizes the existence and ability of quantum computing but it is not yet practical at least for a couple of years and it should be positioned as an augmentation of conventional computing such as an addition of a new tier towards the highest point of a pyramid hierarchy. They are also impressed by the fact that the cryptography sector has finally met its real challenger in terms of pure brute force speed and have started investing R&D resources to refine modern-day security solutions to match them. Recommendation wise, they are encouraging the development of a simulator and language tailored specifically for quantum computing to train and produce sufficient experts in the future.

Onto semiconductors, they have seen global leaders such as Apple, Intel, and AMD all made their own moves of incorporating their own heterogeneous architectures such as big.LITTLE in their processors one way or another and with NVIDIA purchasing ARM and AMD getting its hands on Xylinx, Dell Technologies are pretty sure future servers are going to follow suit and similar architectures as well, focusing on software modernization, integration platform in conjunction with the silicon chip itself.

The enterprise use of 5G also stemmed the organizations interest as they have predicted that the new standards will really take off during this year as true SA-5G specifications such as mMTC, UR-LLC and MEC provide the groundwork for telecommunications parties to learn, adapt and deploy them in both public and private use cases. Software solutions providers such as Dell Technologies themselves, Microsoft, and more will chime in to continuously refine 5G to be open yet standardized.

Finally, multi-cloud assimilation will solve the issue of edge proliferation which is the excessive independent edge system that currently existed in the ecosystem by clearly classifying resource pools and workload extensions into 2 unique individual categories. In a simpler sense, more workloads and resources targeting public clouds and SaaS edges will involve more logical partitioning compared to the past.

Amit Midha, President of the APAC and Japan region, also added that the entire world is slowly shifting its focus to Asia in terms of business and the technology it carries along and forward into the future. Discussing the companys progress for the social impact aimed for the year 2030 with 9 years to go, they are in the driver seat to achieve a 1:1 ratio of using recycled materials for manufacturing and gender representation for its employees alongside affecting more than 1 billion of lives for a greater good.

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Find out what Dell Technologies has to say about quantum computing, 5G and more for this year - Nasi Lemak Tech

Modern cryptography is still a relatively young scientific discipline, but its history shows a significant pattern. Most developments are based on research that took place years or even decades before. Theres a good reason for this glacial pace of movement. Just as drugs and vaccines undergo years of rigorous testing before they reach the market, cryptography applications must be based on proven and thoroughly analyzed methods.

Blockchain is one such example of the development cycle in action. Satoshi Nakamotos work on Bitcoin was the application of principles first described by David Chaum in the early 1980s. Similarly, recent deployments of multiparty computation (MPC) for securing private keys or sealed-bid auctions make use of ideas developed around the same time. Now, as the threat of quantum machines looms over modern computers, the need for newer and stronger forms of cryptography has never been greater.

Torben Pryds Pedersen is chief technology officer of Concordium and was previously head of Cryptomathics R&D division.

Nobody knows precisely when or if quantum computers will prove capable of cracking todays encryption methods. However, the threat alone currently drives extensive work in developing alternatives that will prove robust enough to withstand a quantum attack.

A compressed timeline

Finding a replacement for existing encryption methods isnt a trivial task. For the past three years, the National Institute of Standards and Technology (NIST) has worked to research and advance alternative algorithms, or the backbone of any cryptographic system. This July, it announced a shortlist of 15 proposals in an ongoing project looking for quantum-resistant encryption standards..

But many of these proposals are unattractive due to unworkable key sizes or overall efficiency.Whats more, these alternatives must undergo sufficient testing and scrutiny to ensure they withstand the test of time.

Im sure well see further developments in this area. However, the development of better cryptographic algorithms is only one piece of the puzzle. Once an alternative is defined, theres a much bigger job in ensuring that all existing applications get updated to the new standard. The scope of this is massive, covering virtually every use case on the entire internet, across all of finance and in blockchains.

Given the scale of the task, plans and measures to migrate existing data must be in place long before the quantum threat becomes a reality.

Digital signatures for self-sovereign data

Governments and banking institutions are not naive. According to the 2020 UN E-Government Survey, 65% of member governments are thinking seriously about governance in the digital age, according to the agencys own metrics. Personal data privacy is a growing concern, reflected by the inclusion of data protection mechanisms and methods for digital signatures on the development agenda for e-government applications.

The technology behind digital signatures is generally well-understood by governments. For example, in Europe, the eIDAS regulation puts a responsibility on organizations in member states to implement unified standards for electronic signatures, qualified digital certificates and other authentication mechanisms for electronic transactions. However, theres also a recognition on the part of the European Union that updates will be required to protect against the quantum computer threat.

It seems likely that future methods for protecting personal data will be steered by the principle that users own their own data. In the banking world PSD2, a payments directive for how financial institutions treat data, has been a catalyst for this principle. Once users hold the rights to share their own data, it becomes easier to facilitate data sharing across multiple banking institutions.

Cryptography plays a significant role in the principle of self-sovereign data today, but I believe we will see this concept become more prevalent in Web 3.0 applications. Ideally, users will control their data across any Web 3.0 application, providing full interoperability and ease of use.

Enhancing security and trustlessness with multi-party computation

Similar to the rise of digital signatures, there will be more applications of multiparty computation. From being a purely theoretic construction 30 years ago, we now see MPC applied in more real-world use cases. For example, several institutional-grade asset security platforms, including Unbound Tech, Sepior, Curv and Fireblocks, are already using variations of MPC to keep private keys secure.

Blockchains have yet to fulfill their true potential, evidenced by the lack of compelling use cases.

Due to the vast security potential of MPC, we will continue to see improvements in this technology. It also fits well with the principles of decentralizing trust, given it removes single points of attack and reduces dependency on single trusted entities. In the future, a single individuals private key could be stored in multiple decentralized locations, but still deployed instantly when the user demands.

Blockchains for individuals and enterprises

Blockchain technology is still in a low state of maturity. It theoretically offers significant promise to help individuals and enterprises gain control over their data. But the fact remains todays blockchains and related distributed ledger technologies have yet to fulfill their true potential, evidenced by the lack of compelling use cases.

However, in light of the evolution of other usages of cryptography, such as digital signatures and multiparty computation, its reasonable to expect blockchain technology will improve significantly, become more efficient and accessible and therefore gain more traction in the coming years.

The concept of blockchains is not in itself threatened by quantum computers. Blockchains are, first of all, used to securely register data (or digests of data) and we know already now how to secure the basic functionality of blockchains (immutability of registered data) with cryptographic primitives that are secure in the quantum era (hash functions and digital signature schemes).

But more work is required to handle more advanced protocols in an efficient way and more work is needed to continuously improve the security and efficiency of cryptographic primitives to make the blockchain more and more efficient.

In light of this, we will see a gradual improvement of distributed systems so that they remain secure. We will probably like to keep the smart and good properties of the current cryptographic algorithms and gradually update these as necessary. Planning of this process must be done very carefully as each update must be done well in advance before the current version becomes insecure.

Furthermore, blockchain-enabled payment systems, with robust post-quantum security, can play a significant role in the future of online retail.

Regardless of the use case for cryptography, the user experience will be a critical driver for adoption. A lack of usability has been a massive problem for most cryptography applications so far and this is also true for blockchains. Most platforms are simply infrastructural solutions and, as such, involve a high degree of friction for end users.

Ultimately, blockchain applications need to become as usable as the internet and smartphone applications are today. Usability and quantum-proof security are essential for the future of government, commerce and Web 3.0.

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Torben Pryds Pedersen: The Future of Cryptographic Security in the Age of Quantum - CoinDesk - CoinDesk

Quantum computing is emerging as a subfield of quantum information science. This technology has already started attracting interest from researchers and technology companies with almost feverish excitement and activity. Companies have even begun racing to achieve quantum supremacy. In 2019, Google officially announced that it achieved quantum supremacy. Quantum computing promises great potential in diverse areas, including medical research, financial modeling, traffic optimization, artificial intelligence, weather forecasting, and more.

Quantum computing can be a ground-breaking technology for cybersecurity, enabling companies to improve their cybersecurity strategies. It will help detect and deflect quantum computing-based attacks before they cause harm to groups and individuals.

Quantum cybersecurity is the field of study of all aspects affecting the security and privacy of communications and computations owing to the development of quantum technologies. Quantum computers are likely to solve problems that cannot be done by traditional computers, such as solving the algorithms behind encryption keys that safeguard data and the internets infrastructure. Moreover, as most of todays encryption relies heavily on mathematical formulas that would take impractically much time to decode using todays computers, a quantum computer can easily factor those formulas and break the code.

Over 20 years ago, Peter Shor, an MIT professor of applied mathematics, developed a quantum algorithm that could easily factor large numbers far more quickly than a conventional computer. Since then, scientists have been working on developing quantum computers that can break asymmetric encryption.

The development of large quantum computers could have calamitous consequences for cybersecurity. In this context, thinking quantum cybersecurity solutions will be an advantageous edge. Quantum cybersecurity can pave more robust and compelling opportunities for the security of critical and personal data. It will particularly be useful in quantum machine learning and quantum random number generation, as noted byIBM.

The pace of quantum research undoubtedly continues to accelerate in the years ahead. But it will also pose challenges and vulnerabilities to mission-critical information needed to retain its secrecy. Adapting to advanced cryptography to address these threats could be an obvious solution. The quantum cryptography approach is based on creating algorithms that are hard to break even for quantum computers. This approach can also work with conventional computers.

Another security approach against quantum computing attacks is lattice-based cryptography. Conventional cryptographic algorithms can be replaced with lattice-based algorithms that are designed with proven security. These new algorithms can conceal data inside complex math problems called lattices. Google already has begun testing post-quantum cryptography methods that integrate lattice-based algorithms. According to IBM researcher Cecilia Boschini, lattice-based cryptography will prevent future quantum computing-based attacks and form a basis for Fully Homomorphic Encryption (FHE) that makes it possible for users to perform calculations on a file without seeing the data or revealing it to hackers. The NSA, NIST, and other governmental agencies are also starting to invest in this developing method.

Moreover, according to aForbes article, quantum computing can transform cybersecurity in four areas: quantum random number generation is fundamental to cryptography; quantum-secure communications, specifically quantum key distribution (QKD); post-quantum cryptography, and quantum machine learning.

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The Promise and Impact of Quantum Computing on Cybersecurity - Analytics Insight

Scientists at the Freie Universitt Berlin have come up with an AI-based solution for calculating the ground state of the Schrdinger equation in quantum chemistry.

The Schrdingers equation is primarily used to predict the chemical and physical properties of a molecule based on the arrangement of its atoms. The equation helps determine where the electrons and nuclei of a molecule are and under a given set of conditions what their energies are.

The equation has the same central importance as Newtons law motion, which can predict an objects position at a particular moment, but in quantum mechanics that is in atoms or subatomic particles.

The article describes how the neural network developed by the scientists at the Freie Universitt Berlin brings more accuracy in solving the Schrdingers equation and what does this mean for the future.

In principle, the Schrdingers equation can be solved to predict the exact location of atoms or subatomic particles in a molecule, but in practice, this is extremely difficult since it involves a lot of approximation.

Central to the equation is a mathematical object, a wave function that specifies electrons behaviour in a molecule. But the high dimensionality of the wave function makes it extremely difficult to find out how electrons affect each other. Thus the most you get from the mathematical representations is a probabilistic account of it and not exact answers.

This limits the accuracy with which we can find properties of a molecule like the configuration, conformation, size, and shape, which can help define the wave function. The process becomes so complex that it becomes impossible to implement the equation beyond a few atoms.

Replacing the mathematical building blocks, the scientists at Freie Universitt Berlin came up with a deep neural network that is capable of learning the complex patterns of how electrons are located around the nuclei.

The scientists developed a Deep Neural Networks (DNN) model, PauliNet, that has several advantages over conventional methods to study quantum systems like the Quantum Monte Carlo or other classical quantum chemistry methods.

The DNN model developed by these scientists is highly flexible and allows for a variational approach that can aid accurate calculation of electronic properties beyond the electronic energies.

Secondly, it also helps the easy calculation of many-body and more-complex correlation with fewer determinants, reducing the need for higher computation power. The model mainly helped solve a major tradeoff issue between accuracy and computational cost, often faced while solving the Schrodinger equation.

The model can also calculate the local energy of heavy nuclei like heavy metals without using pseudo-potentials or approximations.

Lastly, the model developed in the study has anti-symmetry functions and other principles crucial to electronic wave functions integrated into the DNN model, rather than let the model learn. Thus, building fundamental physics in the model has helped it make meaningful and accurate predictions.

In recent years, artificial intelligence has helped solve many scientific problems that otherwise seemed impossible using traditional methods.

AI has become instrumental in anticipating the results of experiments or simulations of quantum systems, especially due to its sciences complex nature. In 2018, reinforcement learning was used to design new quantum experiments in automated laboratories autonomously.

Recent efforts by the University of Warwick and another IBM and DeepMind have also tried to solve the Schrdingers equation. However, PauliNet, with its greater accuracy of solving the equation now, presents us with a potential to use it in many real-life applications.

Understanding molecules composition can help accelerate drug-discovery, which earlier was difficult due to the approximations to understand its properties.

Similarly, it could also help discover several other elements or metamaterials like new catalysts, industrial chemical applications, new pesticides, among others. It can be used in characterising molecules that are synthesised in laboratories.

Several academic and commercial software use Schrdingers equation at the core but are based on applications. The accuracy of this software will improve. Quantum computing in itself is based on quantum phenomena of superposition and is made up of qubits that take advantage of the principle. Quantum computing performance will improve as qubits will be able to be measured faster.

While the current study has come up with a faster, cheaper, and accurate solution, there are many challenges to overcome before it is industry-ready.

However, once it is ready, the world will witness many applications as a result of greater accuracy in solving Schrdingers equation.

Kashyap currently works as a Tech Journalist at Analytics India Magazine (AIM). Reach out at kashyap.raibagi@analyticsindiamag.com

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AI Helps Solve Schrdinger's Equation What Does The Future Hold? - Analytics India Magazine