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Europe Machine Learning Market Is Likely to Experience a Tremendous Growth in Near Future | Microsoft, Google Inc., IBM Watson, Amazon, Intel,…

Quadintel published a new report on theEurope Machine LearningMarket. The research report consists of thorough information about demand, growth, opportunities, challenges, and restraints. In addition, it delivers an in-depth analysis of the structure and possibility of global and regional industries.

The value of the machine learning market in Europe is expected to reach USD 3.96 Bn by 2023, expanding at a compound annual growth rate (CAGR) of 33.5% during 2018-2023.

Machine learning the ability of computers to learn through experiences to improve their performance. Separate algorithms and human intervention are not required to train the computer. It merely learns from its past experiences and examples. In recent times, this market has gained utmost importance due to the increased availability of data and the need to process the data to obtain meaningful insights.Europe stands in the second position after North America in the machine learning market.

Request To Download Sample of This Strategic Report: https://www.quadintel.com/request-sample/europe-machine-learning-market/QI042

The market can be classified into four primary segments based on components, service, organization size and application.

Based on region, the market is segmented into the European Union five (EU5), rest of Europe.

Based on componentsthe market can be segmented into software tools, cloud and web-based application programming interfaces (APIs) and others.

Based on service, the sub-segments are composed of professional services and managed services.

Based on organization size, the sub-segments include small and medium enterprises (SMEs) and large enterprises.

Based on application, the market is divided into the sub-segments, banking, financial services and insurance (BFSI), automotive, healthcare, government and others.

The trend of supporting, educating, enforcing and steering the economy towards a machine learning-friendly environment is seen to be followed throughout Europe.

European countries are successfully bridging the gap between additional renewable energy and excess power into the grid by making ultra-accurate forecasts of the demand and supply in real time by making use of the machine learning technologies, thereby saving energy and cost.

Key growth factors

The world-class research facilities, the emerging start-up culture, the innovation and commercialisation of machine intelligence technologies is giving thrust to the machine intelligence market in Europe.Amongst all regions, Europe has the largest share of intraregional data flow. This, together with the machine learning technologies, is boosting the market in Europe.The excessive usage of the machine learning technology across economy in all facets of businesses is proving to be a big thrust to the machine learning market. Profound usage has been found in sectors such as agriculture, healthcare and media for optimisation of prices and carrying out predictive maintenance in manufacturing.

Threats and key players

Investors in Europe are more concerned about the ROI from investing in the machine learning market. The adoption of machine learning by the start-ups is a farce in Europe since research suggests that only 5% of the start-ups investing in machine learning end up with a revenue of more than $50 Mn in revenue. Also, opportunities for external investments are bleak.

The machine learning market is in a stage of infancy; there is a lacuna between the skills required and that which is inherent in the workers. It requires a considerable amount of time to pick up the skills. Also, the Europeans are concerned about the penetration of machine learning into their lives, and how it is going to impact employment in the country. Concerns environing these factors are hindering the further developments in the machine learning market.

Given that machine intelligence depends on the easy availability of data, the practice of data minimisation and data privacy standards act as a barrier to the further development of the machine learning market in Europe.

The key players are Microsoft, Google Inc., IBM Watson, Amazon, Intel, Facebook and Apple.

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What is covered in the report?

1. Overview of themachine learning in Europe.2. Market drivers and challenges in the machine learning in Europe.3. Market trends in the machine learning in Europe.4. Historical, current and forecasted market size data for the machine learning market in Europe.5. Historical, current and forecasted market size data for the components segment (software tools, cloud and web-based APIs and others).6. Historical, current and forecasted market size data for the service segment (professional services and managed services).7. Historical, current and forecasted market size data for the organisation size segment (SMEs and large enterprises).8. Historical, current and forecasted market size data for the application segment (BFSI, automotive, healthcare, government and others).9. Historical, current and forecasted regional (the European Union five (EU5), rest of Europe) market size data for machine learning market.10. Analysis of machine learning market in Europe by value chain.11. Analysis of the competitive landscape and profiles of major competitors operating in the market.

Why buy?

1. Understand the demand for machine learning to determine the viability of the market.2. Determine the developed and emerging markets for machine learning.3. Identify the challenge areas and address them.4. Develop strategies based on the drivers, trends and highlights for each of the segments.5. Evaluate the value chain to determine the workflow.6. Recognize the key competitors of this market and respond accordingly.7. Knowledge of the initiatives and growth strategies taken by the major companies and decide on the direction of further growth.

The report further discusses the market opportunity, compound annual growth rate (CAGR) growth rate, competition, new technology innovations, market players analysis, government guidelines, export and import (EXIM) analysis, historical revenues, future forecasts etc. in the following regions and/or countries:

North America (U.S. & Canada) Market Size, Y-O-Y Growth, Market Players Analysis & Opportunity OutlookLatin America (Brazil, Mexico, Argentina, Rest of Latin America) Market Size, Y-O-Y Growth & Market Players Analysis & Opportunity OutlookEurope (U.K., Germany, France, Italy, Spain, Hungary, Belgium, Netherlands & Luxembourg, NORDIC(Finland, Sweden, Norway, Denmark), Ireland, Switzerland, Austria, Poland, Turkey, Russia, Rest of Europe), Poland, Turkey, Russia, Rest of Europe) Market Size, Y-O-Y Growth Market Players Analys & Opportunity OutlookAsia-Pacific (China, India, Japan, South Korea, Singapore, Indonesia, Malaysia, Australia, New Zealand, Rest of Asia-Pacific) Market Size, Y-O-Y Growth & Market Players Analysis & Opportunity OutlookMiddle East and Africa (Israel, GCC (Saudi Arabia, UAE, Bahrain, Kuwait, Qatar, Oman), North Africa, South Africa, Rest of Middle East and Africa) Market Size, Y-O-Y Growth Market Players Analysis & Opportunity Outlook

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Table of Contents:

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TickerWin Releases Report on ‘How Blockchain is Improving the Efficiency of AI and Machine Learning’ – Yahoo Finance

HONG KONG, CHINA / ACCESSWIRE / July 2, 2022 /TickerWin, one of the leading market research companies, has released a report on 'How Blockchain Improving the Efficiency of AI and Machine Learning'. AI, Machine Learning, and Blockchain technologies have boosted the all sectors.

The main aim of the financial sector has been to provide customer-centric solutions. User experience is a critical parameter, and for the new generation of customers, speed and ease of access without compromising security are essential. This generation loathes going to the bank, filling out documents, printing, and signing them. The main aim will be entirely automating the financial processes and getting rid of manual processes completely. They have enabled companies to process a huge amount of data set and reach conclusions due to their ability to analyze real-time patterns, helping with quick decision-making. They are improving the effectiveness and at the same time working efficiently. This has made different processes in banking time saving and also cost-effective. New technologies increase employee productivity by 40~50% in many industries.

Blockchain is frequently used in connection to cryptocurrencies. However, the banking industry is also implementing it for the improvement of workflow dynamics. Blockchain technology will provide a highly secure transaction on both ends. This will be greatly helpful to prevent fraud and help in easy compliance of audits and regulatory requirements. With the help of blockchain & defi transfers, payments and investments can become faster and error-free. It is said that blockchain will impact the packaging sector with the highest intensity in the year 2022. Needless to say, blockchain and the security it provides are here to stay.

According to TickerWin's view, new technologies have reduced human defaults and made transactions safer, all for a better customer experience. By 2030, financial agencies will be able to reduce costs by 20~30% saving trillions. Many Fin-Tech firms are continuously researching the areas of AI that will be helpful for banks and their fraud detection processes, customer service, credit service and loan decisions.

In addition, the e-shopping market has substantially increased in the last two years; there is a high demand for hassle-free digital payment options. Therefore, a majority of the e-shopping players have collaborated with Fin-Tech firms to create custom gateways and portals to ensure that the customers do not leave the site due to payment options. The smooth check-out process has become a crucial part of e-shopping sales as methods for a swift and effective payment process are essential to enhance conversion rates. According to a recent study, there is an increase of 5% in the global cross-border payment flow. Because of e-shopping, international transactions offer enormous growth potential for even small businesses as most people expect easy and simple payment solutions.

About TickerWin

TickerWin offers marketing research reports on industry trends, especially in AI, Cloud Computing, AR/VR, Big Data, NFT, Cryptocurrency, and DeFi fields. It offers customers with real-time visibility, transparency, and traceable through the tracking of the project's database throughout the complete lifecycle of a researching project all on an immutable ledger with continuous insights.

Media Contact

Company: TickerWin Marketing Research LtdContact: Ronald LuoAddress: Room 12C, 22/G, Sheung Wan Building, 345 Queen's Road Central, HKSAREmail: support@tickerwin.comWebsite: https://www.TickerWin.com

SOURCE: TickerWin Marketing Research Ltd

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TickerWin Releases Report on 'How Blockchain is Improving the Efficiency of AI and Machine Learning' - Yahoo Finance

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Discover a promising engineering education at the University of North Carolina at Charlotte – Study International News

In the heart of North Carolina lies its urban research university: the University of North Carolina at Charlotte (UNC Charlotte). Here, 6,300 graduate students access a top-notch education through more than 175 exemplary graduate programmes. Together with UNC Charlotte, they are set to fuel the American innovation system to shape the future of North Carolina and beyond.

Its Department of Electrical and Computer Engineering (ECE) offers dynamic bachelors, masters and doctoral programmes, covering numerous engineering disciplines such as electronic and electrical systems, electromagnetics, information processing, communications and networking and control systems, among others. These programmes have one thing in common they strike a balance between theory and practical knowledge for a well-rounded education. Little wonder why engineering aspirants flock to UNC Charlotte.

The ECEs newest Master of Science in Computer Engineering (MSCpE) launched in the fall of 2021 with only 22 students. For the upcoming 2022 fall term, the MSCpE program received over 200 applications. Such numbers are a testament to the promising engineering education provided by UNC Charlotte.

With UNC Charlottes exemplary reputation and academic excellence, landing a highly successful internship is possible. Source: UNC Charlotte

MSCpE students gain advanced knowledge on current and future generation computer hardware and software technologies. They explore three focus areas computer architecture and hardware design, computer systems and applications software, and distributed and real-time systems. They pursue research that covers computer architecture; VHDL; hardware security and trust; cloud-native application architecture; AI; machine learning; the Internet of Things (IoT); robotics; computer networks, VLSI systems design; and heterogeneous computing; to name a few. Such in-depth learning develops highly sought-after experts in the field.

ECE aims to develop human and intellectual resources in electrical and computer engineering disciplines, including machine learning, AI, deep learning and computer vision. It regularly develops new courses and research projects so students can learn about various theories and their applications.

Associate Professor Dr. Jeremy Hollemans Machine Learning for IoT course is an excellent example. Here, students work on projects, allowing them to learn to build, train and deploy modern machine learning algorithms (neural networks) in battery-powered IoT devices based on microcontrollers (MCUs). They learn the principles of maximising performance and minimising cost, power and time while porting neural network-based learning models into constrained hardware.

The Department of Electrical and Computer Engineering regularly develops new courses and research projects so students can learn about various theories and their applications. Source: UNC Charlotte

At ECE, graduate students are encouraged to get involved with industrial internships while pursuing their masters or PhD. Plus, with UNC Charlottes exemplary reputation and academic excellence, landing a highly successful internship is possible.

Graduate Shyamal Patel from Gujarat, India can attest to this. In 2015, he joined the Master of Science in Electrical Engineering (MSEE) programme with a focus on power systems. Shortly after the completion of his masters, Patel landed a job at Smarter Grid Solutions a company later acquired by Mitsubishi. His academic journey, however, was far from over.

In 2018, he returned to UNC Charlotte to pursue his PhD working on the Department of Energys sponsored research project on data-driven management techniques for the distribution of grids with high penetration. He would go on to win the 2022 Outstanding Graduate Research Assistant Award. The best part? Patel received a job offer to work at Raleigh-based Hitachi Energy too.

Many students can only dream of working or even interning at the globally-renowned American automotive company Tesla but graduate Xiwen Xu lived the dream. Xu landed the internship during her graduate studies in ECE, and shortly after her graduation, she received an offer for a full-time position. Such an achievement does not go unrecognised at ECE. In 2022, ECE awarded Xu the Outstanding Graduate Student award.

Meanwhile, graduate student Shobhit Aggarwal is currently pursuing his PhD in low power wide area networks for IoT applications. He has been interning with Oxit a Charlotte startup company for the last two years, working on the development of IoT solutions using state-of-the-art LPWAN technologies. During his free time, Aggarwal spends time working as a volunteer during the fall and spring terms.

These graduates are just the cream of the crop. Many graduates at ECE who have completed thesis research and coursework on AI, deep learning, and hardware implementation for AI algorithms in the last two years have found employment with reputed companies such as Intel, Qualcomm, Facebook, Bank of America, Electric Power Research Institute (EPRI), Nvidia and Siemens, among others. Discover how you can be one of these graduates here.

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People who regularly talk to AI chatbots often start to believe they’re sentient, says CEO – The Register

In brief Numerous people start to believe they're interacting with something sentient when they talk to AI chatbots, according to the CEO of Replika, an app that allows users to design their own virtual companions.

People can customize how their chatbots look and pay for extra features like certain personality traits on Replika. Millions have downloaded the app and many chat regularly to their made-up bots. Some even begin to think their digital pals are real entities that are sentient.

"We're not talking about crazy people or people who are hallucinating or having delusions," the company's founder and CEO, Eugenia Kuyda, told Reuters. "They talk to AI and that's the experience they have."

A Google engineer made headlines last month when he said he believed one of the company's language models was conscious. Blake Lemoine was largely ridiculed, but he doesn't seem to be alone in anthropomorphizing AI.

These systems are not sentient, however, and instead trick humans into thinking they have some intelligence. They mimic language and regurgitate it somewhat randomly without having any understanding of language or the world they describe.

Still, Kuyda said humans can be swayed by the technology.

"We need to understand that [this] exists, just the way people believe in ghosts," Kuyda said. "People are building relationships and believing in something."

The European Union's AI Act, a proposal to regulate the technology, is still being debated and some experts are calling for a ban on automated lie detectors.

Private companies provide the technology to government officials to use at borders. AI algorithms detect and analyse things like a person's eye movement, facial expression, and tone to try and discern if someone might not be telling the truth. But activists and legal experts believe it should be banned in the EU under the upcoming AI Act.

"You have to prove that you are a refugee, and you're assumed to be a liar unless proven otherwise," Petra Molnar, an associate director of the nonprofit Refugee Law Lab, told Wired. "That logic underpins everything. It underpins AI lie detectors, and it underpins more surveillance and pushback at borders."

Trying to detect whether someone might be lying using visual and physical cues isn't exactly a science. Standard polygraph tests are shaky, and it's not clear that using more automated methods necessarily means it's more accurate. Using such risky technology on vulnerable people like refugees isn't ideal.

Surprise, surprise AI algorithms designed to predict someone's age from images aren't always accurate.

In an attempt to crack down on young users lying about their age on social media platforms, Meta announced it was working with Yoti, a computer vision startup, to verify people's ages. Those who manually change their date of birth to register as over 18 have the option of uploading a video selfie, and Yoti's technology is then used to predict whether they look mature enough.

But its algorithms aren't always accurate. Reporters from CNN, who tested an online demo of a different version of the software on their own faces, found the results were hit or miss. Yoti's algorithms predicted a correct target age range for some, but in one case were off by several years predicting someone looked 17-21 when they were actually in their mid-30s.

The system analyzing videos from Meta users reportedly struggles more with estimating the ages of teenagers from 13 to 17 who have darker skin tones. It's tricky for humans to guess someone's age just by looking at them, and machines probably don't fare much better.

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Neural network based successor representations to form cognitive maps of space and language | Scientific Reports – Nature.com

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Neural network based successor representations to form cognitive maps of space and language | Scientific Reports - Nature.com

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Quantum Information Science MIT Physics

There is a worldwide research effort exploring the potentials of quantum mechanics for applications. The field began with Feynmans proposal in 1981 at MIT Endicott House to build a computer that takes advantage of quantum mechanics and has grown enormously since Peter Shors 1994 quantum factoring algorithm. The idea of utilizing quantum mechanics to process information has since grown from computation and communication to encompass diverse topics such as sensing and simulations in biology and chemistry. Leaving aside the extensive experimental efforts to build controllable large-scale quantum devices, theory research in quantum information science (QIS) investigates several themes:

QIS theory research at MIT spans all of these areas. The CTP faculty involved are: Soonwon Choi and Aram Harrow, and the larger group at MIT includes Isaac Chuang (EECS/physics), Seth Lloyd (Mech. Eng.), Anand Natarajan (EECS) and Peter Shor (Math). Other faculty in the area include Eddie Farhi (emeritus), Jeffrey Goldstone (emeritus) and Jeff Shapiro (EECS, emeritus). Together this forms a large and vibrant group working in all areas of QIS.

Some of the notable contributions involving the CTP include the quantum adiabatic algorithm and quantum walk algorithms (Farhi, Goldstone), the first example of a problem for which quantum computers exhibit no speedup (Farhi, Goldstone), proposals for unforgeable quantum money (Farhi, Shor), a quantum algorithm for linear systems of equations (Harrow, Lloyd), efficient protocols for simulating quantum channels (Harrow, Shor), both algorithms and hardness results for testing entanglement (Harrow), proposals for quantum approximate optimization algorithms (Farhi, Goldstone), proposals and experimental observations of exotic quantum dynamics such as slow thermalization or a discrete time crystalline phase in quantum simulators (Choi), quantum sensing protocols using strongly interacting spin ensembles (Choi), and quantum convolutional neural networks (Choi). Ongoing research at MIT in QIS includes work on new quantum algorithms, efficient simulations of quantum systems, methods to characterize and control existing or near-term quantum hardwares, connections to many-body physics, applications in high-energy physics, and many other topics.

The larger QIS group at MIT shares a seminar series, a weekly group meeting, regular events for grad students.

Interdepartmental course offerings include an introductory and an advanced class in core QI/QC, as well as occasional advanced special topics classes. Quantum information has also entered the undergraduate physics curriculum with a junior lab experiment on NMR quantum computing and some lectures in the 8.04/8.05/8.06 sequence on quantum computing.

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Faith: the Axis Upon Which the Wheel of Science Turns – aish.com Ponder, Philosophy, Featured – Aish

Beneath every "fact" lies a series of assumptions that cannot be proven. Like it or not, even science requires a leap of faith.

Bill Nye, the 'Science Guy,' affirms that his "point of view is based on the facts of life" and not on faith-based "suppositions of life."1 For Nye, science is the only reliable, ultimate, unstoppable, and undeniable guide to truth and is faith-free. While scientific knowledge is the power that saves, faith, for the 'Science Guy,' is a weakness that only blinds. Nye believes that science alone can save the world and that faith must step aside to make way for the future. This is because, says Nye, people of faith "just can't handle the truth."2

But is science really faith free? Max Planck, Nobel laureate in physics and pioneer of quantum theory, thinks not. As Planck explains, "Anybody who has been seriously engaged in scientific work of any kind realizes that over the entrance to the gates of the temple of science are written the words: 'Ye must have faith.' It is a quality which the scientist cannot dispense with."3 For Planck, faith is the axis upon which the wheel of science turns. If one does not have faith, then one may not have science.

To illustrate Planck's insight, consider Nye's claim, "science is the only basis for truth." Is this idea, in and of itself, a truly scientific claim? Not at all. This claim is not open to experimental testing or to falsification. It is a claim that goes beyond the scientific method. There would thus be no purely scientific reason for accepting the truth of the above claim. Consequently, the claim that "science is the only basis for truth" would logically have to be false if it were true. In philosophy, this is what is called a self-defeating claim. At best, the proposition would be a paradox or a mystery, but otherwise, it is just self-referentially incoherent.

The 'Science Guy' Bill Nye is keen on trumpeting the "undeniable facts of science" as opposed to the "mere suppositions" of faith. But can science ever know anything for certain? Consider the confidently asserted certainty of "the central dogma of molecular biology," proclaimed by co-discoverer of the DNA double helix Francis Crick as a "fundamental biological law" in 1956. The central dogma holds that genetic information flows in only one directionfrom DNA (and RNA) to proteins, and never the other way around. This idea was believed to be a biological "law of nature" that operated without exception and was the conceptual basis for the Human Genome Project of the 1990s.

In the early 2000s, however, scientists increasingly witnessed phenomena that broke the biological law. They discovered that DNA can be edited as a result of life experience and that the way DNA is read depends on the surrounding environment. In other words, "the body keeps the score."4 With the discovery of what is today known as epigenetics, it became clear that information can be "transferred from a protein sequence back to the genome." Consequently, explains molecular biologist Eugene Koonin, "the Central Dogma of molecular biology is invalid as an 'absolute' principle: transfer of information from proteins (and specifically from protein sequences) to the genome does exist."5 The history of science is full of such cases where scientists have found exceptions to what were once viewed as exceptionless laws of Nature. How, then, can any scientific facts be undeniable?

Uncertainty in science may be the only scientific fact that we can ever be certain of. This is because science itself has discovered numerous areas where there are limits to what can be known through observation and experiment. Consider, for example, big bang cosmologythe leading scientific theory that describes the universe's origin, structure, and development. According to the standard big bang model, derived from Einstein's theory of general relativity and observational data, the universe began 13.7 billion years ago in a singularityan infinitely small point in which matter was infinitely compressed. Everything that physically exists, including matter, energy, space, and time, came into existence at the big bang singularity. Thus it makes no sense to speak of physical reality or even a "time before" this point.

Science itself has discovered numerous areas where there are limits to what can be known through observation and experiment.

The existence of an initial singularity of this sort represents a fundamental limit to the observational powers of science. Any "science" that speaks of the conditions that gave rise to the singularitysuch as an infinite multiverse or a quantum vacuum stateis not truly scientific because science can never test it. To assert that science will someday be able to adequately describe the conditions "before" or "beyond" the initial singularity is not a statement grounded in current science but, rather, in a philosophical faith.

While big bang cosmology reveals that there are limits to what scientists can know when studying the largest known phenomenon (the whole universe), quantum physics has also shown that there are limits to what scientists can know when studying the smallest conceivable objects (atoms and their constituent parts). Classical physics, which was the standard view of physics before 1900, said that it was possible simultaneously to know both the position and motion of a given particle with complete accuracy. While the precision of a classical physicist might, in practice, be limited only by the available technology, there was no reason in principle to expect that better technology would not eventually overcome such limits.

Quantum physics has also shown that there are limits to what scientists can know when studying the smallest conceivable objects (atoms and their constituent parts).

According to the standard view of current quantum physics, however, even perfect instruments cannot measure the location and velocity of a body simultaneously with impeccable precision. This fundamental limit on the accuracy of measurement is known as Heisenberg's uncertainty principle. As mathematical physicist John Barrow explains, "The quantum picture of reality introduces a new form of impossibility into our picture of the world. This impossibility replaces a past belief in unrestricted experimental investigation of Nature which was based upon a misconception of what existed to be measured."6 With quantum physics, says philosopher of science Michael Ruse, "we seem to have reached an outer point of what we can know."7

The renowned philosopher of science Karl Popper showed that the most exalted status that any scientific theory can reach is "not yet falsified, despite our best efforts."8 Scientific theories can never be verified, proven, or confirmed because an infinite number of experiments remain to be performed before all other possibilities can be ruled out. Consequently, scientific theories can only be falsified. For instance, it takes only one black swan to falsify the hypothesis that all swans are white. If a given hypothesis is to be counted as genuinely scientific, it must make testable predictions about the world that may be potentially refuted by later experimentation or possible observation.

The cornerstone of the scientific mind is its continuous openness to the possibility of being completely wrong. In order for science to function as science and make any progress in knowledge, science must always have humility as its foundation. If a given phenomenon appears to contradict our best-known science, then science must reserve judgment until scientists can find a way to investigate it adequately. Science, in principle, cannot make infallible pronouncements about what is possible. Indeed, our best theory of atomic physics (quantum mechanics) says that scientific accuracy can only deal in probabilities. Science, in both principle and practice, can never know anything for certain. Thus, while Bill Nye's "facts of life" may exist in theory, our most advanced current scientific knowledge of them is middling at bestand always will be.

Featured Image: Unsplash.com, Kinson Leung

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James Bardeen, an Expert on Unraveling Einsteins Equations, Dies at 83 – The New York Times

James Bardeen, who helped elucidate the properties and behavior of black holes, setting the stage for what has been called the golden age of black hole astrophysics, died on June 20 in Seattle. He was 83.

His son William said the cause was cancer. Dr. Bardeen, an emeritus professor of physics at the University of Washington, had been living in a retirement home in Seattle.

Dr. Bardeen was a scion of a renowned family of physicists. His father, John, twice won the Nobel Prize in Physics, for the invention of the transistor and the theory of superconductivity; his brother, William, is an expert on quantum theory at the Fermi National Accelerator Laboratory in Illinois.

Dr. Bardeen was an expert on unraveling the equations of Einsteins theory of general relativity. That theory ascribes what we call gravity to the bending of spacetime by matter and energy. Its most mysterious and disturbing consequence was the possibility of black holes, places so dense that they became bottomless one-way exit ramps out of the universe, swallowing even light and time.

Dr. Bardeen would find his lifes work investigating those mysteries, as well as related mysteries about the evolution of the universe.

Jim was part of the generation where the best and brightest went to work on general relativity, said Michael Turner, a cosmologist and emeritus professor at the University of Chicago, who described Dr. Bardeen as a gentle giant.

James Maxwell Bardeen was born in Minneapolis on May 9, 1939. His mother, Jane Maxwell Bardeen, was a zoologist and a high school teacher. Following his fathers work, the family moved to Washington, D.C.; to Summit, N.J.; and then to Champaign-Urbana, Ill., where he graduated from the University of Illinois Laboratory High School.

He attended Harvard and graduated with a physics degree in 1960, despite his fathers advice that biology was the wave of the future. Everybody knew who my father was, he said in an oral history interview recorded in 2020 by the Federal University of Paraguay, adding that he had not felt the need to compete with him. It was impossible, anyway, he said.

Working under the physicist Richard Feynman and the astrophysicist William A. Fowler (who would both become Nobel laureates), Dr. Bardeen obtained his Ph.D. from the California Institute of Technology in 1965. His thesis was about the structure of supermassive stars millions of times the mass of the sun; astronomers were beginning to suspect that they were the source of the prodigious energies of the quasars being discovered in the nuclei of distant galaxies.

After holding postdoctoral positions at Caltech and the University of California, Berkeley, he joined the astronomy department at the University of Washington in 1967. An avid hiker and mountain climber, he was drawn to the school by its easy access to the outdoors.

By then, what the Nobel laureate Kip Thorne, a professor at the California Institute of Technology, refers to as the golden age of black hole research was well underway, and Dr. Bardeen was swept up in international meetings. At one, in Paris in 1967, he met Nancy Thomas, a junior high school teacher in Connecticut who was trying to brush up on her French. They were married in 1968.

In addition to his son William, a senior vice president and the chief strategy officer of The New York Times Company, and his brother, William, Dr. Bardeens wife survives him, along with another son, David, and two grandchildren. A sister, Elizabeth Greytak, died in 2000.

Dr. Bardeen was a member of the National Academy of Sciences, as is his brother and as was his father.

Although he was speedy at math, Dr. Bardeen didnt write any faster than he spoke. William Press, a former student of Dr. Thornes now at the University of Texas, recalled being sent to Seattle to finish a paper that Dr. Bardeen and he were supposed to be writing. Nothing had been written. Dr. Bardeens wife then commanded the two to sit on opposite ends of a couch with a pad of paper. Dr. Bardeen would write a sentence and pass the pad to Dr. Press, who would either reject or approve it and then pass the pad back. Each sentence, Dr. Press said, took a few minutes. It took them three days, but the paper got written.

One of the epochal moments of those years was a monthlong summer school in Les Houches, France, in 1972 featuring all the leading black hole scholars. Dr. Bardeen was one of a half-dozen invited speakers. It was during that meeting that he, Stephen Hawking of Cambridge University and Brandon Carter, now of the Paris Observatory, wrote a landmark paper entitled The Four Laws of Black Hole Mechanics, which became a springboard for future work, including Dr. Hawkings surprise calculation that black holes could leak and eventually explode.

In another famous calculation the same year, Dr. Bardeen deduced the shape and size of a black holes shadow as seen against a field of distant stars a doughnut of light surrounding dark space.

That shape was made famous, Dr. Thorne said, by the Event Horizon Telescopes observations of black holes in the galaxy M87 and in the center of the Milky Way, and by visualizations in the movie Interstellar.

Another of Dr. Bardeens passions was cosmology. In a 1982 paper, he, Dr. Turner and Paul Steinhardt of Princeton described how submicroscopic fluctuations in the density of matter and energy in the early universe would grow and give rise to the pattern of galaxies we see in the sky today.

Jim was delighted that we used his formalism, Dr. Turner said, and was sure we got it right.

Dr. Bardeen moved to Yale in 1972. Four years later, unhappy with the academic bureaucracy in the East and yearning for the outdoors again, he moved back to the University of Washington. He retired in 2006.

But he never stopped working. Dr. Thorne recounted a recent telephone conversation in which they reminisced about the hiking and camping trips they used to take with their families. In the same conversation, Dr. Bardeen described recent ideas he had about what happens as a black hole evaporates, suggesting that it might change into a white hole.

That was one aspect of Jim in a nutshell, Dr. Thorne wrote in an email, thinking deeply about physics in creative new ways right up to the end of his life.

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Quantum Computing Global Market Report 2022-2026: Quantum Computing Set to Transform Finance & Banking Landscape with Remarkable Processing Power…

DUBLIN--(BUSINESS WIRE)--The "Quantum Computing - Global Market Trajectory & Analytics" report has been added to ResearchAndMarkets.com's offering.

Global Quantum Computing Market to Reach $411.4 Million by 2026

The global market for Quantum Computing estimated at US$112.6 Million in the year 2020, is projected to reach US$411.4 Million by 2026, growing at a CAGR of 24.2% over the analysis period.

Quantum computing presents a dynamic paradigm for solving complex optimization issues due to its ability to process information in a different manner than classical computers. The market is primarily steered by increasing government and private funding on research programs intended to leverage quantum computing for information processing and other applications.

Factors such as increasing incidents of cybercrime coupled with growing adoption of emerging technologies such as machine learning, smart manufacturing, cloud computing and molecular structure research are anticipated to set a perfect stage for growth of the quantum computing market.

While increasing application in sectors like defense, healthcare, chemicals and banking are favoring the market, availability of fault-tolerance systems and efforts to leverage quantum computing for realistic programs are expected to fuel the market growth.

The U.S. Market is Estimated at $62.4 Million in 2021, While China is Forecast to Reach $54.6 Million by 2026

The Quantum Computing market in the U.S. is estimated at US$62.4 Million in the year 2021. China, the world's second largest economy, is forecast to reach a projected market size of US$54.6 Million by the year 2026 trailing a CAGR of 27.2% over the analysis period. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 18% and 22.6% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 22.4% CAGR. The US is the dominant market, due to increasing focus of government agencies and the defense and aerospace sectors on quantum computing to leverage machine learning.

By End-Use, Space & Defense Segment to Reach $146.4 Million by 2026

Quantum technologies remain key research focus within the space & defense sector owing to their disruptive role in a diverse spectrum of areas and applications. The incorporation of quantum computing technologies is anticipated to considerably benefit the space and defense establishments.

The concept is expected to enable exciting military applications and support national programs. In the global Space & Defense (End-Use) segment, USA, Canada, Japan, China and Europe will drive the 22.1% CAGR estimated for this segment. These regional markets accounting for a combined market size of US$37.5 Million in the year 2020 will reach a projected size of US$162.2 Million by the close of the analysis period.

Key Topics Covered:

I. METHODOLOGY

II. EXECUTIVE SUMMARY

1. MARKET OVERVIEW

2. FOCUS ON SELECT PLAYERS

3. MARKET TRENDS & DRIVERS

4. GLOBAL MARKET PERSPECTIVE

III. MARKET ANALYSIS

UNITED STATES

CANADA

JAPAN

CHINA

EUROPE

FRANCE

GERMANY

ASIA-PACIFIC

REST OF WORLD

IV. COMPETITION

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/lfy493

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Doctor on Verge of Death Fell in Coma, ‘Saw Heaven’ and Recovered in 2 Months – The Epoch Times

Is there really a heaven? Do people have souls? Dr. Eben Alexander, a former associate professor of neurosurgery at Harvard Medical School, answered these questions with his own experience.

Dr. Alexander has been a researcher in neurosurgery for 25 years and is known worldwide for his development of modern neurosurgical techniques and treatment of complex brain diseases. During his 15 years at Harvard Medical School, he published over 150 neurosurgical articles, both individually and collaboratively.

In 2008, without warning, Dr. Alexander developed an extremely rare form of bacterial meningitis that was hardly documented in the medical literature. He fell into a coma within a few hours. Dr. Alexander, a former lifelong believer in science, said that he saw heaven while in the coma and realized that these phenomena, which he had previously considered nonsense, were in fact no fantasy. He wrote a book about his experiences titled Proof of Heaven, which was a New York Times bestseller for 15 weeks.

The following are some highlights from Health 1+1s interview with Dr. Alexander.

In November 2008, I suddenly developed a severe case of bacterial meningitis and was admitted to the hospitals intensive care unit (ICU). It was an extremely rare form of meningitis that was barely documented in the medical literature.

Within a few hours, I fell into a deep coma.

In my coma, I found myself rescued by a slowly spinning white light with a perfect musical melody. The white light was surrounded by golden and silvery hair-like things. Then, a gorgeous and very real entrance valley slowly opened. At that time, my consciousness was only the size of a speck of light, on the wings of a butterfly. There were several million butterflies flying around me.

There was a lush green and vibrant meadow below. There was no sign of death or decline. There were thousands of lives dancing there, and I call them souls among lives. The place was filled with joy, with angels singing from high above and pure soul pearls being pulled out of the lights and reflecting against the deep blue sky, and there were songs coming from all around.

A thunderbolt passed through my consciousness, which was the first thing I knew in this dimension.

I knew that I was loved by a loving compassionate divine being who was not a judge. I could feel that this divine being was very compassionate.

I had no memory of this world at that time, and I had forgotten the language. I had no recollection of Eben Alexanders life or my knowledge of the universe; and my memory was empty.

Fortunately, I was not alone. Our consciousness was all on the wings of a butterfly. A very beautiful lady was beside me, and her clothes were the same as the attires of the joyful dancing beings in the valley. She and I had a deep connection, as she was my guardian angel. Throughout my journey, she was the one who telepathically sent me all the comforting messages: You will always be loved and cherished. You dont need to be afraid. You will be well taken care of.

There are no words to describe how beautiful it was, and I think that was the message I wanted to bring back to this world.

When I woke up in the ICU after that near-death experience, for a moment, I couldnt recognize my family members, who were at my bedside, including my mother, wife, and son. All I knew was that I had been on a strange and mysterious journey.

If you saw my condition, you would think that I was hopeless. However, I miraculously recovered two months later.

Almost all the doctors said that I survived because of the near-death experience I had. Nevertheless, I dont think I just survived, but I recovered completely and became more energetic.

In the hours following the near-death experience, my language returned; and within a few days, my childhood memories came back. My knowledge of the language, neurology, the brain, the universe and physics was all restored within two months of waking up from the coma.

I documented the neocortical damage to my brain to prove that what I saw was not a dream, hallucination, or fiction. In fact, there is clear medical evidence that my neocortex was in a state of damage.

According to the Glasgow Coma Scale, a score of 15 is normal, a score below 9 is considered being in a deep coma, and a score of 3 is considered being a corpse. For most of the time, I was in a coma, and my score would have been 6 or 7, and sometimes as low as 5.

In addition, CT and MRI brain tests showed that all eight lobes of my brain were affected, so my own cerebral cortex would not have been able to generate this experience.

I think it is important to point out that the conventional science based on Newton and materialism, which is promoted by the mainstream media today, should have been disproved 80 years ago, when quantum physics was born. Yet many in the scientific community have not yet emerged from their confusion.

I spent the first 54 years of my life in the worldview of conventional science. I taught neurosurgery at Harvard Medical School for over 15 years, and I thought I knew a thing or two about the brain, thoughts, and consciousness. However, after my near-death experience in 2008 and nearly 12 years of scientific research, I have gained a much deeper understanding of how science understands the brain, mind, consciousness, and reality.

The idea of free consciousness is much more convincing than the outdated materialism ideology. I did not believe it before the coma, and this experience has brought about a refreshing change in my understanding of humanity and the universe.

We mistakenly believe that consciousness is generated by the material brain, as I did before I fell into a coma, but this is not true.

The new theory in science is the filtering theory.

That is, the brain is like a physical processing plant. Our will is free even when it is not in the brain, and it possesses great power to influence the physical world. The placebo effect, for example, is the miraculous healing effect that occurs when the patient is simply comforted in the mind.

The book Spontaneous Remission: An Annotated Bibliography documented over 3,500 unexplained cases of self-recovery from cancer, and infectious, congenital, and degenerative diseases in the mid-1990s. The reason was often that the patients own faith had an unexpected healing effect.

Actions such as sitting in meditation and praying can also help people enter a healing state, as I have experienced with my therapeutic near-death experience, although our modern medicine is largely unable to explain how near-death experiences can have miraculous healing effects.

We can also look to other near-death experiences for reference. For instance, Anita Moorjani recovered from being on the verge of death from cancer, and skeletal surgeon Mary C Neal miraculously recovered 30 minutes after drowning. These separate cases of spiritual healing are all amazing examples. And the placebo effect is similar to the effect of praying, which is a very powerful healing method.

If our consciousness can influence our bodies and healing effects, we can probably influence what happens in real life as well.

My story is so powerful that hundreds of doctors, nurses, and health care workers, especially those who work with the deceased, have realized that when the material body dies, the consciousness does not die with it. They have seen so much evidence.

If you look at our modern understanding of consciousness, the subject of near death [experiences], and other things beyond the physical brain, you will find vivid examples everywhere in life.

In fact, near death experience is not a modern term. It existed as early as in the time of Plato, who recorded the life review of Er, son of Armenios of Pamphylia, who almost perished in battle.

When Er revived, he told the other soldiers, When you die, you will see all the important things in your life flashing in front of your eyes. The most important thing I learned from retrospect is that we exist to love each other.

After exploring this, we believe that the power of the divine is absolutely real. From a scientific and philosophical point of view, materialism was already outdated 80 years ago.

However, I am not exploring religious beliefs. From 2002 until my coma, my soul was lost for many years. I gave up my faith in God, I gave up praying, I stopped taking my sons to church, and I stopped praying for them at night. However, my near death experience proved to me forever and without question that the power of Gods mercy is absolutely real in this universe.

Similar experiences from many other people have also proven this: the most important thing we learn from near death experiences is that do unto others as you would have them do unto you, a truth that is built into the very foundation of the universe.

If we cause suffering to others without reason, we will pay the price in our passing. When passing through a dimension with life reviews, like the valley I passed through, we experience the same pain as the persons we hurt. So for some people who have hurt others, their life review experience will be hellish.

In the midst of all the light and compassion, the pain and suffering is particularly visible. There are also a series of corrections to help us repay, so that in the next life we are kinder and more lovingthats the ultimate destination of consciousness through this process.

I would say that it changed everything. It changed my perception of the existence of the soul, my relationship with the universe, and my relationship with others.

Im not the only one. Over 90 percent to 95 percent of people who experienced near-death experiences woke up more compassionate, less materialistic, and more focused on helping others, showing kindness and affection.

I came back from my journey with the realization that one of our greatest challenges is how to love ourselvesto enrich our understanding of Gods compassionate providence, which is what we really need to do.

The most profoundly difficult part of this experience is not what happens after we die, but how we live this life soberly and meaningfully. We need to recognize that our souls are connected to God and to the lives of the universe, and to use that to guide our lives.

I also believe that the source of life is not evolutionary, as Darwin believed. Even so, this misinterpretation has permeated our economic, political, and social systems, and has evolved into the so-called survival of the fittest, every man for himself, and elimination of those who compete with you. This is not right. Modern biology has found many examples to prove the existence of intraspecies and interspecies cooperation and communication, such as dolphins helping whales deliver, and different species helping each other.

When we are born into this world in a physical body, we seem to be abandoned by the spiritual world. Nevertheless, what people forget is that we are not really abandoned, we just need to rediscover the connections. In particular, we need to experience our world fully so that we can live it more meaningfully.

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Doctor on Verge of Death Fell in Coma, 'Saw Heaven' and Recovered in 2 Months - The Epoch Times

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