Category Archives: Quantum Computing

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

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

Ever since Star Wars Episode VI: Return of the Jedi, when Boba Fett busts his jet suit on Jabba the Hutts sail barge during the Battle of the Great Pit of Carkoon, well, this writer was hooked. Jet packs have since been depicted in media and sci-fi, most notably in the dystopian scenario of Spielbergs 2002 Minority Report (an adaptation of a 1956 science fiction novella by Philip K. Dick). The Guardian offers this thorough history of jet packs.

Technological fact now mirrors science fiction, as the British Royal Navy has recently been testing jet suit technology to board ships. A new video (above) was recently released by the UK-based Gravity Industries, which manufactures the jet suit technology.

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OODA is one of the few independent research sources with experience in due diligence on quantum computing and quantum security companies and capabilities. Our practitioners lens on insights ensures our research is grounded in reality. See: Quantum Computing Sensemaking.

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Jet Suit Testing by the British Royal Navy and Gravity Industries - OODA Loop

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?

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Turns Out Schrdinger, the Father of Quantum Physics, Was a Pedophile - Futurism

For more than a century, IBM has been rooted in the fundamental promise of technology: We believe that when we apply science to real-world problems, we can make progress - for both business and society. And as those problems have changed over time, so have we. IBM has repeatedly reinvented itself to overcome whatever obstacles stand in the way of innovation and value for our clients.

IBM scientists and engineers have been at the heart of our relentless reinvention. They have always been guided by a core principle, to deliver innovation that matters, for our company and the world.

Our commitment to research as part of our business model means we will continue to create the technologies that our clients and the world rely upon. For example, we have led US companies for decades in the number of patents received annually. Today, it was announced IBM has achieved this milestone for IBM's total of more than 8,500 patents led the IFI Claims Patent Service 2021 rankings.29 years in a row.

We are proud of this accomplishment and our leadership. However, the number of patents we receive has never told the full story of the innovation we drive. Our priority has always been leading the frontiers of computing and its relationship to business, science, professions, and society.

I believe that today, more than ever, we need innovation to meet the demands of many of the major challenges of our time - from models to create sustainable growth, to addressing future pandemics and climate change, to enabling energy and food security. To address them, we need faster discovery, open collaboration, efficient problem solving, and the ability to push science and business into new frontiers.

This future will be powered by a blend of high-performance computing, AI, and quantum computing, all integrated through the hybrid cloud. The confluence of these technologies represents a step change in computing, and the outcomes will surpass anything we've seen before. Together, these advancements can exponentially alter the speed and scale at which we can uncover solutions to complex problems. We've come to call this accelerated discovery.

Our priority has always been leading the frontiers of computing and its relationship to business, science, professions, and society.

But this will not happen in a vacuum. Strong innovation is built on a collaborative ecosystem, a commitment to long-term investment in hard tech challenges and fundamental materials, and the implementation of an open approach.

We have a long history of putting these principles into practice, and it's in this spirit we undertook some of the most daunting hard technology challenges in 2021 - and delivered on them.

To name just a few: we worked with our partners to demonstrate the first 2 nm nanosheet technology for semiconductors, which will support up to 50 billion transistors on a chip the size of a fingernail and offer enormous gains in efficiency. We also collaborated with Samsung on the successful prototype of a chip that defies conventional semiconductor design, and lays the groundwork to achieve energy density and performance levels previously thought unattainable.

And as we lead the quest to reach practical and large-scale quantum computing, we stayed true to the ambitious roadmap we laid out in 2020 and In addition to unveiling Eagle, our 127-qubit quantum processor, and previewing the design for IBM Quantum System Two, our next-generation system that will house future quantum processors, we also introduced, Quantum Serverless, a new programming model for leveraging quantum and classical resources. Read more.delivered Eagle, our first 127-qubit processor, which will be critical to growing the nascent quantum industry IBM is pioneering.

To continue to realize a future marked by fundamental technology progress and the exploration of new scientific boundaries, we are deepening our commitment to this approach.

Building open communities for innovation

As part of our strategy, we are doubling down on our already robust and long-standing commitment to open communities. Innovation can emerge from anywhere, from a tech giant or a disruptive startup. In software, the growth of open source has redefined where innovation can come from, and how it is monetized. IBM has a long history in open source, and that continues today. Our pioneering work in serverless computing, which is quickly becoming the leading platform for the hybrid cloud industry because of the significant growth of Red Hat, is just one example of this.

We will also expand our focus to grow communities of innovation. The most successful technologies and innovations are often found when complementary institutions work together. To take one example among many, our collaboration with the The Cleveland Clinic + IBM Discovery Accelerator is a collaboration set to advance pathogen research, and foster the next-gen tech workforce for healthcare. Read more.Cleveland Clinicwill bring together IBM's technology and expertise in hybrid cloud, AI, and quantum computing to help Cleveland Clinic discover solutions to pressing issues around public health.

These sorts of collaborations will help technology to solve truly profound problems, and we hope to do so in partnership with other institutions adopting our technology, including Fraunhofer-Geselleschaft, Germany's largest research institution, the Hartree Centre, a major AI and high-performance computing research facility in the UK, and Japan's University of Tokyo and Keio University. Worldwide, we will continue to forge partnerships with the broader scientific community as we look to accelerate the pace of discovery.

Pushing discovery beyond patent filings

Moving forward, we're strengthening our companywide approach to focus our innovation efforts around the areas that matter most for our business and for society at large. This will include hybrid cloud, AI, quantum computing, systems and semiconductors, and security.

We believe these areas will have the most impact on our clients, industries, and the world. We also believe they're the ones with the greatest potential for ecosystem collaboration.

While IBM will remain an intellectual property powerhouse with one of the strongest US patent portfolios, as part of our heightened focus moving forward, we'll also take a more selective approach to patenting. We are proud of our decades-long history of topping the US patents chart, but in this new era, our position as the recipient of the most patents in any given year will not be a priority. Instead, our focus will be to prioritize growing these key technology areas of our company.

The problems the world is facing today require us to work faster than ever before. We see it as our duty to catalyze scientific progress by taking the cutting-edge technologies we're working on, scaling them, and deploying them with partners across every industry.

Innovation is the heart and soul of IBM and serves as the engine to make our clients and the world work better. We made enormous strides in the last year, and we plan to achieve even more in 2022.

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International Business Machines : Building on Our History of Innovation for the Future of IBM - marketscreener.com

Let's look at example that shows how quantum computers can succeed where classical computers fail:

A supercomputer might be great at difficult tasks like sorting through a big database of protein sequences. But it will struggle to see the subtle patterns in that data that determine how those proteins behave.

Proteins are long strings of amino acids that become useful biological machines when they fold into complex shapes. Figuring out how proteins will fold is a problem with important implications for biology and medicine.

A classical supercomputer might try to fold a protein with brute force, leveraging its many processors to check every possible way of bending the chemical chain before arriving at an answer. But as the protein sequences get longer and more complex, the supercomputer stalls. A chain of 100 amino acids could theoretically fold in any one of many trillions of ways. No computer has the working memory to handle all the possible combinations of individual folds.

Quantum algorithms take a new approach to these sorts of complex problems -- creating multidimensional spaces where the patterns linking individual data points emerge. In the case of a protein folding problem, that pattern might be the combination of folds requiring the least energy to produce. That combination of folds is the solution to the problem.

Classical computers can not create these computational spaces, so they can not find these patterns. In the case of proteins, there are already early quantum algorithms that can find folding patterns in entirely new, more efficient ways, without the laborious checking procedures of classical computers. As quantum hardware scales and these algorithms advance, they could tackle protein folding problems too complex for any supercomputer.

How complexity stumps supercomputers

Proteins are long strings of amino acids that become useful biological machines when they fold into complex shapes. Figuring out how proteins will fold is a problem with important implications for biology and medicine.

A classical supercomputer might try to fold a protein with brute force, leveraging its many processors to check every possible way of bending the chemical chain before arriving at an answer. But as the protein sequences get longer and more complex, the supercomputer stalls. A chain of 100 amino acids could theoretically fold in any one of many trillions of ways. No computer has the working memory to handle all the possible combinations of individual folds.

Quantum computers are built for complexityQuantum algorithms take a new approach to these sorts of complex problems -- creating multidimensional spaces where the patterns linking individual data points emerge. Classical computers can not create these computational spaces, so they can not find these patterns. In the case of proteins, there are already early quantum algorithms that can find folding patterns in entirely new, more efficient ways, without the laborious checking procedures of classical computers. As quantum hardware scales and these algorithms advance, they could tackle protein folding problems too complex for any supercomputer.

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What is Quantum Computing? | IBM

Twenty-seven years before Steve Jobs unveiled a computer you could put in your pocket, physicist Paul Benioff published a paper showing it was theoretically possible to build a much more powerful system you could hide in a thimble a quantum computer.

Named for the subatomic physics it aimed to harness, the concept Benioff described in 1980 still fuels research today, including efforts to build the next big thing in computing: a system that could make a PC look in some ways quaint as an abacus.

Richard Feynman a Nobel Prize winner whose wit-laced lectures brought physics to a broad audience helped establish the field, sketching out how such systems could simulate quirky quantum phenomena more efficiently than traditional computers. So,

Quantum computing is a sophisticated approach to making parallel calculations, using the physics that governs subatomic particles to replace the more simplistic transistors in todays computers.

Quantum computers calculate using qubits, computing units that can be on, off or any value between, instead of the bits in traditional computers that are either on or off, one or zero. The qubits ability to live in the in-between state called superposition adds a powerful capability to the computing equation, making quantum computers superior for some kinds of math.

Using qubits, quantum computers could buzz through calculations that would take classical computers a loooong time if they could even finish them.

For example, todays computers use eight bits to represent any number between 0 and 255. Thanks to features like superposition, a quantum computer can use eight qubits to represent every number between 0 and 255, simultaneously.

Its a feature like parallelism in computing: All possibilities are computed at once rather than sequentially, providing tremendous speedups.

So, while a classical computer steps through long division calculations one at a time to factor a humongous number, a quantum computer can get the answer in a single step. Boom!

That means quantum computers could reshape whole fields, like cryptography, that are based on factoring what are today impossibly large numbers.

That could be just the start. Some experts believe quantum computers will bust through limits that now hinder simulations in chemistry, materials science and anything involving worlds built on the nano-sized bricks of quantum mechanics.

Quantum computers could even extend the life of semiconductors by helping engineers create more refined simulations of the quantum effects theyre starting to find in todays smallest transistors.

Indeed, experts say quantum computers ultimately wont replace classical computers, theyll complement them. And some predict quantum computers will be used as accelerators much as GPUs accelerate todays computers.

Dont expect to build your own quantum computer like a DIY PC with parts scavenged from discount bins at the local electronics shop.

The handful of systems operating today typically require refrigeration that creates working environments just north of absolute zero. They need that computing arctic to handle the fragile quantum states that power these systems.

In a sign of how hard constructing a quantum computer can be, one prototype suspends an atom between two lasers to create a qubit. Try that in your home workshop!

Quantum computing takes nano-Herculean muscles to create something called entanglement. Thats when two or more qubits exist in a single quantum state, a condition sometimes measured by electromagnetic waves just a millimeter wide.

Crank up that wave with a hair too much energy and you lose entanglement or superposition, or both. The result is a noisy state called decoherence, the equivalent in quantum computing of the blue screen of death.

A handful of companies such as Alibaba, Google, Honeywell, IBM, IonQ and Xanadu operate early versions of quantum computers today.

Today they provide tens of qubits. But qubits can be noisy, making them sometimes unreliable. To tackle real-world problems reliably, systems need tens or hundreds of thousands of qubits.

Experts believe it could be a couple decades before we get to a high-fidelity era when quantum computers are truly useful.

Predictions of when we reach so-called quantum computing supremacy the time when quantum computers execute tasks classical ones cant is a matter of lively debate in the industry.

The good news is the world of AI and machine learning put a spotlight on accelerators like GPUs, which can perform many of the types of operations quantum computers would calculate with qubits.

So, classical computers are already finding ways to host quantum simulations with GPUs today. For example, NVIDIA ran a leading-edge quantum simulation on Selene, our in-house AI supercomputer.

NVIDIA announced in the GTC keynote the cuQuantum SDK to speed quantum circuit simulations running on GPUs. Early work suggests cuQuantum will be able to deliver orders of magnitude speedups.

The SDK takes an agnostic approach, providing a choice of tools users can pick to best fit their approach. For example, the state vector method provides high-fidelity results, but its memory requirements grow exponentially with the number of qubits.

That creates a practical limit of roughly 50 qubits on todays largest classical supercomputers. Nevertheless weve seen great results (below) using cuQuantum to accelerate quantum circuit simulations that use this method.

Researchers from the Jlich Supercomputing Centre will provide a deep dive on their work with the state vector method in session E31941 at GTC (free with registration).

A newer approach, tensor network simulations, use less memory and more computation to perform similar work.

Using this method, NVIDIA and Caltech accelerated a state-of-the-art quantum circuit simulator with cuQuantum running on NVIDIA A100 Tensor Core GPUs. It generated a sample from a full-circuit simulation of the Google Sycamore circuit in 9.3 minutes on Selene, a task that 18 months ago experts thought would take days using millions of CPU cores.

Using the Cotengra/Quimb packages, NVIDIAs newly announced cuQuantum SDK, and the Selene supercomputer, weve generated a sample of the Sycamore quantum circuit at depth m=20 in record time less than 10 minutes, said Johnnie Gray, a research scientist at Caltech.

This sets the benchmark for quantum circuit simulation performance and will help advance the field of quantum computing by improving our ability to verify the behavior of quantum circuits, said Garnet Chan, a chemistry professor at Caltech whose lab hosted the work.

NVIDIA expects the performance gains and ease of use of cuQuantum will make it a foundational element in every quantum computing framework and simulator at the cutting edge of this research.

Sign up to show early interest in cuQuantum here.

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What Is Quantum Computing? | NVIDIA Blog