Mediaboss Marketing

Quantum computers promise to be game-changers in fields where there are enormously complex calculations to be carried out. Hoping to use quantum computing to address one of humanitys biggest problems climate change investigators from Microsoft Research and ETH Zurich have developed a quantum algorithm they say is able to simulate catalytic processes extremely quickly. In doing so, they claim that it could be used to find an efficient method for carrying out carbon fixation, cutting down on carbon dioxide in the atmosphere by turning it into useful compounds.

At present, synthetic catalytic processes are discovered using laborious trial-and-error lab experiments. Computer simulations are much faster, but modern computers have a difficult job calculating the properties of very complex molecules. By contrast, Microsofts quantum catalytic simulation algorithm reportedly beats existing state-of-the-art algorithms by 10 times; boding well for the transformational possibilities of using quantum computing as a cornerstone of future chemistry.

Our unique approach pushes the boundaries to deliver the promise of quantum computing and to create unprecedented possibilities for our world, Matthias Troyer, distinguished scientist at Microsoft Research, told Digital Trends. Quantum computing is redefining what is possible with technology, creating unprecedented possibilities to solve humanitys most complex challenges. Microsoft is committed to turning the impossible into reality in a responsible way that brings the best solutions to humanity and our planet.

Troyer explained that the advancements in algorithms gained from this research will serve as a springboard for future work. Microsoft is hoping that it will be able to work alongside the chemistry community to find new ways for quantum computers to help develop new chemical processes, molecules, and, eventually someday, materials. The research is available to read via Microsofts blog.

This isnt the first promising quantum algorithm Digital Trends has covered this month. Recently we wrote about a quantum algorithm that could help revolutionize disease diagnosis. However, like all quantum algorithms, it is going to rely on quantum computers advancing sufficiently in order for researchers to be able to gain the most benefit from it. The hardware this will require is another topic Microsoft discusses in the research paper on this work.

See original here:
Microsofts plan to scrub carbon out of the atmosphere? Quantum computers - Yahoo! Voices

Many videos describing quantum computers try to distill and oversimplify everything. Thoughty's takes its time and gives more historical and theoretical context than most.

Because it does take a while to get into the subject, here's a shorter explainer by MIT:

Today's computers use bitsa stream of electrical or optical pulses representing1s or0s. Everything from your tweets and e-mails to your iTunes songs and YouTube videos are essentially long strings of these binary digits.

Quantum computers, on the other hand, usequbits, whichare typically subatomic particles such as electrons or photons. Generating and managing qubits is a scientific and engineering challenge. Some companies, such as IBM, Google, and Rigetti Computing, use superconducting circuits cooled to temperatures colder than deep space. Others, like IonQ, trap individual atoms in electromagnetic fields on a silicon chip in ultra-high-vacuum chambers. In both cases, the goal is to isolate the qubits in a controlled quantum state.

The processing power possible through these controlled qubits will make today's fastest computers look positively archaic.

Image: YouTube / Thoughty2

Intelligence is a surprisingly difficult thing to define. Kurzgesagt jumps into the debate with an interesting overview of where intelligence begins. Is a slime mold intelligent? Are plants intelligent?

Wildfires are a natural part of many ecosystems, though more and more are human-caused. Wendover Productions takes a look at how firefighters work to minimize the spread of wildfires in grueling and dangerous conditions.

Because of its ubiquity, the landscape is littered with proposed etymologies of the term OK. This nice explainer clarifies the murky origins of one of the most widely spoken words in the world.

If you ever dropped a quarter into a Space Invaders game, youve likely fantasized about having your own arcade cabinet in your house. Of course, you likely thought better of it for several reasons, including the idea that a giant cabinet dedicated to just one game isnt very practical. Polycade understands the urge though very, []

Most of us have a love-hate relationship with banks. Okay, its actually probably more like a tolerate-hate relationship. We understand their role in holding and securing our money so we dont have to stuff it in a mattress somewhere. But we dont trust the bank not to gouge us on fees whenever they can. And []

If youve ever worked on a video project or engineered a podcast and thought youd make your own sound effects howd that go for ya? We assume it was a bigger undertaking than youd probably bargained for. From using stalks of celery to replicate breaking tree limbs to frying bacon to reproduce the sound of []

Continue reading here:
This simple explainer tackles the complexity of quantum computing - Boing Boing

This stunning image captured last year by physicists at the University of Glasgow in Scotland is the first-ever photo of quantum entanglement - a phenomenon so strange, physicist Albert Einstein famously described it as 'spooky action at a distance'.

It might not look like much, but just stop and think about it for a second: this fuzzy grey image was the first time we'd seen the particle interaction that underpins the strange science of quantum mechanics and forms the basis of quantum computing.

Quantum entanglement occurs when two particles become inextricably linked, and whatever happens to one immediately affects the other, regardless of how far apart they are. Hence the 'spooky action at a distance' description.

This particular photo shows entanglement between two photons - two light particles. They're interacting and - for a brief moment - sharing physical states.

Paul-Antoine Moreau, first author of the paper wherein the image was unveiled back in July 2019, told the BBC the image was "an elegant demonstration of a fundamental property of nature".

To capture the incredible photo, Moreau and a team of physicists created a system that blasted out streams of entangled photons at what they described as 'non-conventional objects'.

The experiment actually involved capturing four images of the photons under four different phase transitions. You can see the full image below:

(Moreau et al., Science Advances, 2019)

What you're looking at here is actually a composite of multiple images of the photons as they go through a series of four phase transitions.

The physicists split the entangled photons up and ran one beam through a liquid crystal material known as -barium borate, triggering four phase transitions.

At the same time they captured photos of the entangled pair going through the same phase transitions, even though it hadn't passed through the liquid crystal.

You can see the setup below: The entangled beam of photons comes from the bottom left, one half of the entangled pair splits to the left and passes through the four phase filters. The others that go straight ahead didn't go through the filters, but underwent the same phase changes.

(Moreau et al., Science Advances, 2019)

The camera was able to capture images of these at the same time, showing that they'd both shifted the same way despite being split. In other words, they were entangled.

While Einstein made quantum entanglement famous, the late physicist John Stewart Bell helped define quantum entanglement and established a test known as 'Bell inequality'. Basically, if you can break Bell inequality, you can confirm true quantum entanglement.

"Here, we report an experiment demonstrating the violation of a Bell inequality within observed images," the team wrote in Science Advances.

"This result both opens the way to new quantum imaging schemes ... and suggests promise for quantum information schemes based on spatial variables."

The research was published in Science Advances.

A version of this article was first published in July 2019.

See the rest here:
Looking Back on The First-Ever Photo of Quantum Entanglement - ScienceAlert

In a chapter of the Modern CTO podcast, Ripples CTO, David Schwartz, expressed concerns about the development of quantum computers. Ripples CTO believes this technology is a threat to the security of Bitcoin, XRP, and cryptocurrencies. This is primarily because the consensus algorithms behind cryptocurrencies rely on conventional cryptography, as Schwartz stated:

From the point of view of someone who is building systems based on conventional cryptography, quantum computing is a risk. We are not solving problems that need powerful computing like payments and liquidity the work that the computers do is not that incredibly complicated, but because it relies on conventional cryptography, very fast computers present a risk to the security model that we use inside the ledger.

Algorithms like SHA-2 and ECDSA (elliptic curve cryptography) are sort of esoteric things deep in the plumbing but if they were to fail, the whole system would collapse. The systems ability to say who owns Bitcoin or who owns XRP or whether or not a particular transaction is authorized would be compromised().

Ripples CTO said that Ripple is trying to prepare for the emergence of quantum computers. Therefore, they are determining when the algorithms mentioned will no longer be reliable. Ripples CTO estimates that in the next 8-10 years, quantum computers will begin to pose a threat, as Schwartz further stated:

I think we have at least eight years. I have very high confidence that its at least a decade before quantum computing presents a threat, but you never know when there could be a breakthrough. Im a cautious and concerned observer, I would say.

The other fear would be if some bad actor, some foreign government, secretly had quantum computing way ahead of whats known to the public. Depending on your threat model, you could also say what if the NSA has quantum computing. Are you worried about the NSA breaking your payment system?

Despite the above, Ripples CTO made an optimistic conclusion and stated that even if there is a malicious actor with this technology, he will not use it against the average person. Therefore, Schwartz believes that most users have nothing to worry about:

While some people might really be concerned it depends on your threat model, if youre just an average person or an average company, youre probably not going to be a victim of this lets say hypothetically some bad actor had quantum computing that was powerful enough to break things, theyre probably not going to go after you unless you are a target of that type of actor.

As soon as its clear that theres a problem, these systems will probably be frozen until they can be fixed or improved. So, most people dont have to worry about it.

Go here to see the original:
Ripple CTO: Quantum computers will be a threat to Bitcoin and XRP - Crypto News Flash

As healthcare businesses transform for a post-COVID-19 era, they are embracing digital technologies as essential for outmaneuvering the uncertainty faced by businesses and as building blocks for driving more innovation. Maturing digital technologies such as social, mobile, analytics and cloud (SMAC); emerging technologies such as distributed ledger, artificial intelligence, extended reality and quantum computing (DARQ);and scientific advancements (e.g., CRISPR, materials science) are helping to make innovative breakthroughs a reality.

These technologies are also proving essential in supporting COVID-19 triage efforts. For example, hospitals in China are using artificial intelligence (AI) to scan lungs, which is reducing the burden on healthcare providers and enabling earlier intervention. Hospitals in the United States are also using AI to intercept individuals with COVID-19 symptoms from visiting patients in the hospital.

Because AI and machine learning (ML) definitions can often be confused, it may be best to start by defining our terms.

AI can be defined as a collection of different technologies that can be brought together to enable machines to act with what appears to be human-like levels of intelligence. AI provides the ability for technology to sense, comprehend, act and learn in a way that mimics human intelligence.

ML can be viewed as a subset of AI that provides software, machines and robots the ability to learn without static program instructions.

ML is currently being used across the health industry to generate personalized product recommendations to consumers, identify the root cause of quality problems and fix them, detect healthcare claims fraud, and discover and recommend treatment options to physicians. ML-enabled processes rely on software, systems, robots or other machines which use ML algorithms.

For the healthcare industry, AI and ML represent a set of inter-related technologiesthat allow machines to perform and help with both administrative and clinical healthcare functions. Unlike legacy technologies that are algorithm-based tools that complement a human, health-focused AI and ML today can truly augment human activity.

The full potential of AI is moving beyond mere automation of simple tasks into a powerful tool enabling collaboration between humans and machines. AI is presenting an opportunity to revolutionize healthcare jobs for the better.

Recent research indicates that in order to maximize the potential of AI and to be digital leaders, healthcare organizations must re-imagine and re-invent their processes and create self-adapting, self-optimizing living processes that use ML algorithms and real-time data to continuously improve.

In fact, theres consensus among healthcare organizations hat ML-enabled processes help achieve previously hidden or unobtainable value, and that these processes are finding solutions to previously unsolved business problems.

Despite these key findings, additional research surprisingly finds that only 39% of healthcare organizations report that they have inclusive design or human-centric design principles in place to support human-machine collaboration. Machines themselves will become agents of process change, unlocking new roles and new ways for humans and machines to work together.

In order to tap into the unique strengths of AI, healthcare businesses will need to rely on their peoples talent and ability to steward, direct, and refine the technology. Advances in natural language processing and computer vision can help machines and people collaborate and understand one another and their surroundings more effectively. It will be vital to prioritize explainability to help organizations ensure that people understand AI.

Powerful AI capabilities are already delivering profound results across other industries such as retail and automotive. Healthcare organizations now have an opportunity to integrate the new skills needed to enable fluid interactions between human and machines and adapt to the workforce models needed to support these new forms of collaboration.

By embracing the growing adoption of AI, healthcare organizations will soon see the potential benefits and value of AI such as organizational and workflow improvements that can unleash improvements in cost, quality and access. Growth in the AI health market is expected to reach $6.6 billion by 2021 thats a compound annual growth rate of 40%. In just the next couple of years,the health AI market will grow more than 10 times.

AI generally, and ML specifically, gives us technology that can finally perform specialized nonroutine tasks as it learns for itself without explicit human programing shifting nonclinical judgment tasks away from healthcare enterprise workers.

What will be key to the success of healthcare organizations leveraging AI and ML across every process, piece of data and worker? When AI and ML are effectively added to the operational picture, we will see healthcare systems where machines will take on simple, repetitive tasks so that humans can collaborate on a larger scale and work at a higher cognitive level. AI and ML can foster a powerful combination of strategy, technology and the future of work that will improve both labor productivity and patient care.

Brian Kalis is a managing director of digital health and innovation for Accenture's health business.

More:
Now More Than Ever We Should Take Advantage of the Transformational Benefits of AI and ML in Healthcare - Managed Healthcare Executive