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In the healthcare industry, quantum computing could enable a variety of disruptive use cases for providers and health plans by accelerating diagnoses, personalizing medicine, and optimizing pricing. Quantum-enhanced machine learning algorithms are particularly relevant to the sector.

Quantum Computing in Healthcare Market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. It also provides market information in terms of development and its capacities.

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Prominent players in the global Quantum Computing in Healthcare market are consistently pouring funds into the research and development of next-generation healthcare IT solutions. These players are keen on expanding their foothold in cloud-based Quantum Computing in Healthcare solutions.

Some of the top key players of this market are D-Wave Solutions, IBM, Google, Microsoft, Rigetti Computing, Intel, Anyon Systems Inc., Cambridge Quantum Computing Limited, Origin Quantum Computing Technology.

Various factors are responsible for the markets growth trajectory, which are studied at length in the report. In addition, the report lists down the restraints that are posing threat to the global Quantum Computing in Healthcare market. This report is a consolidation of primary and secondary research, which provides market size, share, dynamics, and forecast for various segments and sub-segments considering the macro and micro environmental factors. It also gauges the bargaining power of suppliers and buyers, threat from new entrants and product substitute, and the degree of competition prevailing in the market.

Global Quantum Computing in Healthcare Market Segmentation:

Market Segmentation: By Type

Diagnostic AssistancePrecision MedicineOthers

Market Segmentation: By Application

HospitalResearch InstituteOther

Global Quantum Computing in Healthcare Market research report offers:

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The key regional markets methodically examined in the research report are North America, Europe, Japan, China, India, and Southeast Asia. North America is expected to represent a substantial share in the market during the forecast period. The growth of the region is primarily driven by the healthcare IT market in the U.S., which is one of the most prominent and mature markets worldwide. The stringent regulatory norms and Quantum Computing in Healthcare incentivizing policies in the region are prompting hospitals and clinics in the region to implement Quantum Computing in Healthcare solutions.

The cost analysis of the Global Quantum Computing in Healthcare Market has been performed while keeping in view manufacturing expenses, labor cost, and raw materials and their market concentration rate, suppliers, and price trend. Other factors such as Supply chain, downstream buyers, and sourcing strategy have been assessed to provide a complete and in-depth view of the market. Buyers of the report will also be exposed to a study on market positioning with factors such as target client, brand strategy, and price strategy taken into consideration.

Key questions answered in the report include:

Table of Contents

Global Quantum Computing in Healthcare Market Research Report 2022 2028

Chapter 1 Quantum Computing in Healthcare Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Quantum Computing in Healthcare Market Forecast

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Quantum Computing in Healthcare Market to Witness Robust Expansion by 2029 | D-Wave Solutions, IBM, Google - Digital Journal

A recent investigation that resurfaced damning evidence that famed physicist Erwin Schrdinger was a pedophile is continuing to make waves in the academic community.

Schrdinger, widely cited as the father of quantum physics and perhaps best remembered for his 1935 thought experiment Schrdingers Cat, was widely revealed to be a pedophile by The Irish Times after the newspaper published a report detailing his record as a sexual predator and serial abuser.

Its a stomach-churning revelation about a researcher whose work revolutionized the study of the natural world and even led directly to todays international research frenzy into quantum computing and which shows, once again, that even the powerful and brilliant can be monsters.

The Irish Times identified young girls who Schrdinger became infatuated with, including a 14-year-old girl whom the physicist groomed after he became her math tutor.

Schrdinger, who died in 1961, later admitted to impregnating the girl when she was 17 and he was in his mid-forties. Horrifyingly, she then had a botched abortion that left her permanently sterile, according to the newspaper.

Perhaps most diabolically, the physicist kept a record of his abuse in his diaries, even justifying his actions by claiming he had a right to the girls due to his genius.

Walter Moore, author of the biography Schrdinger, Life and Thought published in 1989, said that the physicists attitudes towards women was essentially that of a male supremacist. Disgustingly, the biography seemed to downplay and even romanticize his abusive habits, and describes him as having a Lolita complex.

Schrdinger also attempted a relationship with a different 12-year-old girl, disgustingly writing in his journal that she was among the unrequited loves of his life. However, he decided not to pursue her after a family member voiced their concerns that the physicist was a, you know, unrepentant abusive predator.

In response, a petition has been launched to change the title of a lecture hall at Dublins Trinity University thats named after him.

We can acknowledge the great mark Schrdinger has left on science through our study, and this petition does not wish to diminish the impact his lectures or ideas had on physics, the petition says. However, it seems in bad taste that a modern college such as Trinity would honor this man with an entire building.

Thats true, of course. You can recognize the contributions someone has had in their field while also acknowledging that they were an absolute scumbag.

Buthonoring them by naming a lecture hall or a giant space telescope is completely unnecessary.

READ MORE: How Erwin Schrdinger insulted his Lolita complex in Ireland [The Irish Times]

More on horrible men: James Webb Hated Gay People. Why Are We Naming a Telescope After Him?

Care about supporting clean energy adoption? Find out how much money (and planet!) you could save by switching to solar power at UnderstandSolar.com. By signing up through this link, Futurism.com may receive a small commission.

Continue reading here:
Turns Out Schrdinger, the Father of Quantum Physics, Was a Pedophile - Futurism

In the thick of action, Cisco has revealed the technology trends that are expected to make a significant impact in 2022 and beyond.

Commenting on the trends and predictions, Osama Al-Zoubi, CTO, Cisco Middle East and Africa, said: Technology is always evolving and moving in exciting new directions. In a time of fast-paced digitization, we identified a range of trends and innovations our customers can expect to see over the next years.

Prediction: Ethical, responsible, and explainable AI will become a top priority

The extreme quantity of data being generated has already exceeded human scale but still needs to be processed intelligently and, in some cases, in near real-time. This scenario is where machine learning (ML) and artificial intelligence (AI) will come into their own.

The challenge is that data has ownership, sovereignty, privacy, and compliance issues associated with it. And if the AI being used to produce instant insights has inherent biases built-in, then these insights are inherently flawed.

This leads to the need for ethical, responsible, and explainable AI. The AI needs to be transparent, so everyone using the system understands how the insights have been produced. Transparency must be present in all aspects of the AI lifecycle its design, development, and deployment.

Prediction: Data driving Edge towards whole new application development

Modern enterprises are defined by the business applications they create, connect to and use. In effect, applications, whether they are servicing end-users or are business-to-business focused or even machine-to-machine connections, will become the boundary of the enterprise.

The business interactions that happen across different types of applications will create an ever-expanding deluge of data. Every aspect of every interaction will generate additional data to provide predictive insights. With predictive insights, the data will likely gravitate to a central data store for some use cases. However, other use cases will require pre-processing of some data at the Edge, including machine learning and other capabilities.

Prediction: Future of innovation and business is tied to unlocking the power of data

Beyond enabling contextual business insights to be generated from the data, teams will be able to better automate many complex actions, ultimately getting to automated self-healing. To achieve this future state, applications must be created with an automated, observable, and API (Application Programming Interface)-first mindset with seamless security embedded from development to run-time. Organisations will have the ability to identify, inspect, and manage APIs regardless of provider or source.

Prediction: Always-on, ubiquitous and cheap internet key to future tech and social equality

There is no doubt that the trend for untethered connectivity and communications will continue. The sheer convenience of using devices wirelessly is obvious to everyone, whether nomadic or mobile.

This always-on internet connectivity will further help alleviate social and economic disparity through more equitable access to the modern economy, especially in non-metropolitan areas, helping create jobs for everyone. But this also means that if wireless connectivity is lost or interrupted, activities must not come to a grinding halt.

The future needs ubiquitous, reliable, always-on internet connectivity at low price points. A future that includes seamless internet services requires the heterogeneity of access meaning AI-augmented and seamless connectivity between every cellular and Wi-Fi generation and the upcoming LEO satellite constellations and beyond.

Prediction: Quantum networking will power a faster, more secure future

Quantum computing and security will interconnect very differently than classical communications networks, which stream bits and bytes to provide voice and data information.

Quantum technology is fundamentally based on an unexplained phenomenon in quantum physics the entanglement between particles that enables them to share states. In the case of quantum networking, this phenomenon can be used to share or transmit information. The prospect of joining sets of smaller quantum computers together to make a very large quantum computer is enticing.

Quantum networking could enable a new type of secure connection between digital devices, making them impenetrable to hacks. As this type of fool proof security becomes achievable with quantum networking, it could lead to better fraud protection for transactions. In addition, this higher quality of secure connectivity may also be able to protect voice and data communications from any interference or snooping. All of these possibilities would re-shape the internet we know and use today.

Also read:

Alibaba: Top 10 trends that will shape the tech industry

Cisco simplifies software and services buying program with new Enterprise Agreement

Link:
From ethical AI to quantum networking Cisco predicts the future of technology - ITP.net

A group of scientists at the U.S. Department of Energys Ames Laboratory has developed computational quantum algorithms that are capable of efficient and highly accurate simulations of static and dynamic properties of quantum systems. The algorithms are valuable tools to gain greater insight into the physics and chemistry of complex materials, and they are specifically designed to work on existing and near-future quantum computers.

Scientist Yong-Xin Yao and his research partners at Ames Lab use the power of advanced computers to speed discovery in condensed matter physics, modeling incredibly complex quantum mechanics and how they change over ultra-fast timescales. Current high performance computers can model the properties of very simple, small quantum systems, but larger or more complex systems rapidly expand the number of calculations a computer must perform to arrive at an accurate model, slowing the pace not only of computation, but also discovery.

This is a real challenge given the current early-stage of existing quantum computing capabilities, said Yao, but it is also a very promising opportunity, since these calculations overwhelm classical computer systems, or take far too long to provide timely answers.

The new algorithms tap into the capabilities of existing quantum computer capabilities by adaptively generating and then tailoring the number and variety of educated guesses the computer needs to make in order to accurately describe the lowest-energy state and evolving quantum mechanics of a system. The algorithms are scalable, making them able to model even larger systems accurately with existing current noisy (fragile and prone to error) quantum computers, and their near-future iterations.

Accurately modeling spin and molecular systems is only the first part of the goal, said Yao, In application, we see this being used to solve complex materials science problems. With the capabilities of these two algorithms, we can guide experimentalists in their efforts to control materials properties like magnetism, superconductivity, chemical reactions, and photo-energy conversion.

Our long-term goal is to reach quantum advantage for materials to utilize quantum computing to achieve capabilities that cannot be achieved on any supercomputer today, said Ames Laboratory Scientist Peter Orth.

This topic is further discussed in two papers: (1)Adaptive Variational Quantum Dynamics Simulation, authored by Y.-X. Yao, N. Gomes, F. Zhang, C.-Z. Wang, K.-M. Ho, T. Iadecola, and P. P. Orth; and published in PRX Quantum; (2) Adaptive Variational Quantum Imaginary Time Evolution Approach for Ground State Preparation, authored by N. Gomes, A. Mukherjee, F. Zhang, T. Iadecola, C.-Z. Wang, K.-M. Ho, P. P. Orth, Y.-X. Yao; accepted in Advanced Quantum Technologies.

Ames Laboratory is a U.S. Department of Energy Office of Science National Laboratory operated by Iowa State University. Ames Laboratory creates innovative materials, technologies and energy solutions. We use our expertise, unique capabilities and interdisciplinary collaborations to solve global problems.

Ames Laboratory is supported by the Office of Science of the U.S. Department of Energy. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time.

Read the rest here:
Innovative New Algorithms Advance the Computing Power of Early-Stage Quantum Computers - SciTechDaily

PayPal head of emerging technology research, Hubert Le Van Gong.

PayPal

PayPal is looking to get in on the ground floor of a cutting-edge technology that could change the way the payments giant catches fraud and measures the creditworthiness of its customers.

Whether it's Goldman Sachs looking to speed up how it prices derivatives, or JPMorgan using quantum computing to test an algorithm that predicts options prices, top financial firms are exploring how and where the tech can be deployed.

Quantum computing, unlike traditional computing, uses a branch physics that runs on quantum bits rather than 1s and 0s. Because of this, quantum computing is helpful when executing large, complex calculations, like those in risk analytics or algorithmic trading.

The firm partnered with IBM in October 2020 to figure out how to use quantum computing to improve fraud detection, credit-risk operations, and overall security posture.

Early research shows quantum computing can be better than traditional computers in sweeping through large data sets and discovering patterns in data that can be indicative of fraudulent behavior or identifying credit-worthy individuals, Hubert Le Van Gong, PayPal's head of emerging technology research, told Insider.

Applying quantum computing to existing machine-learning capabilities could mean PayPal would improve its ability to detect fraud and save costs during the modelling process.

But it's a long-term play many of the benefits are theoretical and have yet to be proven.

"I wouldn't say this technology is going to detect fraud in a meaningful way anytime soon," Jay Gambetta, an IBM fellow and vice president of IBM Quantum, told Insider. "It's still very research-based," he added.

And even with "pretty aggressive" timelines in regards to quantum hardware and software, the technology won't be ready to implement until 2023, Gambetta added.

Even at such an early stage, it's a play the payments giant is ready to take on.

"It's not a matter of if, it's more a matter of when this is going to happen," Le Van Gong said. "The companies that are just sitting back and looking at it, waiting for it to become ready are going to miss out."

PayPal sifts through big, constantly changing data sets to detect fraudulent activity and make decisions around credit worthiness. However the data sets are large and can have millions of samples and up to 10,000 different properties like IP address, device type, or location, Le Van Gong said.

To cut down the number of properties and shave off computational costs of modelling, PayPal currently uses a method called "feature selection," Le Van Gong said. The process uses machine learning to pinpoint which properties are most useful in flagging fraudulent behaviors.

But even with feature selection, it's still an extremely complex, expensive, and time-intensive task to do with classic computers, he said.

"The scale at which PayPal operates in terms of machine learning is such that even classical computers, and the best computers you can find today, are going to be limited," Le Van Gong said. Quantum computers hold the promise of scaling beyond traditional computers when it comes to the number of data features and the size of the datasets, he added.

In addition to scale, quantum computers could help PayPal improve its prediction of important features and do so at a reduced cost compared with traditional computers, Le Van Gong said.

PayPal, which has been researching quantum computing for the past few years, is still in the learning stage of how the technology works and can integrate with classical computers.

The initiative is led by Le Van Gong's emerging technology research team, established in 2021, that explores the use of advanced technologies like cryptography and distributed-ledger security.

"It's still early in the process and it's very much humbling work," he added.

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PayPal is experimenting with quantum computing to supercharge how it analyzes fraud and risk. An exec takes us inside the payment giant's playbook for...