Monthly Archives: January 2020

On Oct. 23, 2019, Google published a paper in the journal Nature entitled Quantum supremacy using a programmable superconducting processor. The tech giant announced its achievement of a much vaunted goal: quantum supremacy.

This perhaps ill-chosen term (coined by physicist John Preskill) is meant to convey the huge speedup that processors based on quantum-mechanical systems are predicted to exhibit, relative to even the fastest classical computers.

Googles benchmark was achieved on a new type of quantum processor, code-named Sycamore, consisting of 54 independently addressable superconducting junction devices (of which only 53 were working for the demonstration).

Each of these devices allows the storage of one bit of quantum information. In contrast to the bits in a classical computer, which can only store one of two states (0 or 1 in the digital language of binary code), a quantum bit qbit can store information in a coherent superposition state which can be considered to contain fractional amounts of both 0 and 1.

Sycamore uses technology developed by the superconductivity research group of physicist John Martinis at the University of California, Santa Barbara. The entire Sycamore system must be kept cold at cryogenic temperatures using special helium dilution refrigeration technology. Because of the immense challenge involved in keeping such a large system near the absolute zero of temperature, it is a technological tour de force.

The Google researchers demonstrated that the performance of their quantum processor in sampling the output of a pseudo-random quantum circuit was vastly better than a classical computer chip like the kind in our laptops could achieve. Just how vastly became a point of contention, and the story was not without intrigue.

An inadvertent leak of the Google groups paper on the NASA Technical Reports Server (NTRS) occurred a month prior to publication, during the blackout period when Nature prohibits discussion by the authors regarding as-yet-unpublished papers. The lapse was momentary, but long enough that The Financial Times, The Verge and other outlets picked up the story.

A well-known quantum computing blog by computer scientist Scott Aaronson contained some oblique references to the leak. The reason for this obliqueness became clear when the paper was finally published online and Aaronson could at last reveal himself to be one of the reviewers.

The story had a further controversial twist when the Google groups claims were immediately countered by IBMs quantum computing group. IBM shared a preprint posted on the ArXiv (an online repository for academic papers that have yet to go through peer review) and a blog post dated Oct. 21, 2019 (note the date!).

While the Google group had claimed that a classical (super)computer would require 10,000 years to simulate the same 53-qbit random quantum circuit sampling task that their Sycamore processor could do in 200 seconds, the IBM researchers showed a method that could reduce the classical computation time to a mere matter of days.

However, the IBM classical computation would have to be carried out on the worlds fastest supercomputer the IBM-developed Summit OLCF-4 at Oak Ridge National Labs in Tennessee with clever use of secondary storage to achieve this benchmark.

While of great interest to researchers like myself working on hardware technologies related to quantum information, and important in terms of establishing academic bragging rights, the IBM-versus-Google aspect of the story is probably less relevant to the general public interested in all things quantum.

For the average citizen, the mere fact that a 53-qbit device could beat the worlds fastest supercomputer (containing more than 10,000 multi-core processors) is undoubtedly impressive. Now we must try to imagine what may come next.

The reality of quantum computing today is that very impressive strides have been made on the hardware front. A wide array of credible quantum computing hardware platforms now exist, including ion traps, superconducting device arrays similar to those in Googles Sycamore system and isolated electrons trapped in NV-centres in diamond.

These and other systems are all now in play, each with benefits and drawbacks. So far researchers and engineers have been making steady technological progress in developing these different hardware platforms for quantum computing.

What has lagged quite a bit behind are custom-designed algorithms (computer programs) designed to run on quantum computers and able to take full advantage of possible quantum speed-ups. While several notable quantum algorithms exist Shors algorithm for factorization, for example, which has applications in cryptography, and Grovers algorithm, which might prove useful in database search applications the total set of quantum algorithms remains rather small.

Much of the early interest (and funding) in quantum computing was spurred by the possibility of quantum-enabled advances in cryptography and code-breaking. A huge number of online interactions ranging from confidential communications to financial transactions require secure and encrypted messages, and modern cryptography relies on the difficulty of factoring large numbers to achieve this encryption.

Quantum computing could be very disruptive in this space, as Shors algorithm could make code-breaking much faster, while quantum-based encryption methods would allow detection of any eavesdroppers.

The interest various agencies have in unbreakable codes for secure military and financial communications has been a major driver of research in quantum computing. It is worth noting that all these code-making and code-breaking applications of quantum computing ignore to some extent the fact that no system is perfectly secure; there will always be a backdoor, because there will always be a non-quantum human element that can be compromised.

More appealing for the non-espionage and non-hacker communities in other words, the rest of us are the possible applications of quantum computation to solve very difficult problems that are effectively unsolvable using classical computers.

Ironically, many of these problems emerge when we try to use classical computers to solve quantum-mechanical problems, such as quantum chemistry problems that could be relevant for drug design and various challenges in condensed matter physics including a number related to high-temperature superconductivity.

So where are we in the wonderful and wild world of quantum computation?

In recent years, we have had many convincing demonstrations that qbits can be created, stored, manipulated and read using a number of futuristic-sounding quantum hardware platforms. But the algorithms lag. So while the prospect of quantum computing is fascinating, it will likely be a long time before we have quantum equivalents of the silicon chips that power our versatile modern computing devices.

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Google claims to have invented a quantum computer, but IBM begs to differ - The Conversation CA

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We are at an inflection point

Ever since Professor Alan Turing proposed the principle of the modern computer in 1936, computing has come a long way. While advancements to date have been promising, the future is even brighter, all thanks to quantum computing, which performs calculations based on the behaviour of particles at the sub-atomic level, writes Kalyan Kumar, CVP and CTO IT Services,HCL Technologies.

Quantum computing promises to unleash unimaginable computing power thats not only capable of addressing current computational limits, but unearthing new solutions to unsolved scientific and social mysteries. Whats more, thanks to increasing advancement since the 1980s, quantum computing can now drive some incredible social and business transformations.

Quantum computing holds immense promise in defining a positive, inclusive and human centric future, which is what theWEF Future Council on Quantum Computingenvisages. The most anticipated uses of quantum computing are driven by its potential to simulate quantum structures and behaviours across chemicals and materials. This promise is being seen guardedly by current scientists who claim quantum computing is still far from making a meaningful impact.

This said, quantum computing is expected to open amazing and much-needed possibilities in medical research. Drug development time, which usually takes more than 10 to 12 years with billions of dollars of investment, is expected to reduce considerably, alongside the potential to explore unique chemical compositions that may just be beyond the limits of current classical computing. Quantum computing can also help with more accurate weather forecasting, and provide accurate information that can help save tremendous amounts of agriculture production from damage.

Quantum computing promises a better and improved future, and while humans are poised to benefit greatly from this revolution, businesses too can expect unapparelled value.

When it comes to quantum computing, it can be said that much of the world is at the they dont know what they dont know stage. Proof points are appearing, and it is seemingly becoming clear that quantum computing solves problems that cannot be addressed by todays computers. Within transportation, for example, quantum computing is being used to develop battery and self-driving technologies, while Volkswagen has also been using quantum computing to match patterns and predict traffic conditions in advance, ensuring a smoother movement of traffic. In supply chains, logistics and trading are receiving a significant boost from the greater computing power and high-resolution modelling quantum computing provides, adding a huge amount of intelligence using new approaches to machine learning.

The possibilities for businesses are immense and go way beyond these examples mentioned above, in domains such as healthcare, financial services and IT. Yet a new approach is required. The companies that succeed in quantum computing will be those that create value chains to exploit the new insights, and form a management system to match the high-resolution view of the business that will emerge.

While there are some initial stage quantum devices already available, these are still far from what the world has been envisaging. Top multinational technology companies have been investing considerably in this field, but they still have some way to go. There has recently been talk of prototype quantum computers performing computations that would have previously taken 10,000 years in just 200 seconds. Though of course impressive, this is just one of the many steps needed to achieve the highest success in quantum computing.

It is vital to understand how and when we are going to adopt quantum computing, so we know the right time to act. The aforementioned prototype should be a wakeup call to early adopters who are seeking to find ways to create a durable competitive advantage. We even recently saw a business announcing its plans to make a prototype quantum computer available on its cloud, something we will all be able to buy or access some time from now. If organisations truly understand the value and applications of quantum computing, they will be able to create new products and services that nobody else has. However, productising and embedding quantum computing into products may take a little more time.

One important question arises from all this: are we witnessing the beginning of the end for classical computing? When looking at the facts, it seems not. With the advent of complete and practical quantum computers, were seeing a hybrid computing model emerging where digital binary computers will co-process and co-exist with quantum Qbit computers. The processing and resource sharing needs are expected to be optimised using real time analysis, where quantum takes over exponential computational tasks. To say the least, quantum computing is not about replacing digital computing, but about coexistence enabling composed computing that handles different tasks at the same time similar to humans having left and right brains for analytical and artistic dominance.

If one things for sure, its that we are at an inflection point, witnessing what could arguably be one of the most disruptive changes in human existence. Having a systematic and planned approach to adoption of quantum computing will not only take some of its mystery away, but reveal its true strategic value, helping us to know when and how to become part of this once in a lifetime revolution.

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What Is Quantum Computing, And How Can It Unlock Value For Businesses? - Computer Business Review

Among the healthcare technologies venture firms be looking at most closely at in 2020, various artificial intelligence and machine learning applications are atop this list, of course. But so are more nuts-and-bolts tools like administrative process automation and patient engagement platforms, VCs say.

Other, more leading-edge technologies genomics-focused data and analytics, and even quantum computing are among the areas attracting investor interest this year.

"We expect 2020 to mark the first year where health IT venture firms will start to look at quantum computing technology for upcoming solutions," Dr. Anis Uzzaman, CEO and general partner of Pegasus Tech Ventures, told Healthcare IT News.

"With the breakthrough supremacy announcement from Google validating the technology and the subsequent launch of the service Amazon Braket in 2019, there is sure to be a new wave of entrepreneurial activity starting in 2020."

He said quantum computing technology holds a lot of promise for the healthcare industry with potential breakthroughs possible throughout the health IT stack from operations and administration to security.

Among the promising companies, Uzzaman pointed to Palo Alto-based QC Ware, a startup pioneering a software solution that enables companies to use a variety of quantum hardware platforms such as Rigetti and IBM to solve a variety of enterprise problems, including those specifically related to healthcare.

He also predicted artificial intelligence would continue to be at the forefront for health IT venture firms in 2020 as it becomes more clear which startups may be winners in their initial target sectors.

"There has been consistent growth of investment activity over the past few years into healthcare startups using artificial intelligence to target a range of areas from imaging to diagnostics," he said.

However, Uzzaman also noted regulation and long enterprise sales cycles have largely slowed the ability for these companies to significantly scale their revenues.

"Therefore, we anticipate 2020 will be the year where it will become clearer to health IT venture firms who will be winners in applying artificial intelligence to imaging, pathology, genomics, operations, diagnostics, transcription, and more," he said. "We will also continue to see moderate growth in the overall investment amount in machine learning and AI companies, but will see a notable decrease in the number of companies receiving an investment.

Uzzaman explained there were already some signs in late 2019 that there could be late in a short-term innovation cycle for artificial intelligence with many companies, particularly those applying machine learning and AI to robotics, shutting down.

"However, we anticipate many companies will reach greater scale with their solutions and separate themselves from the competition, which will translate into more mega funding rounds," he said.

Ezra Mehlman, managing partner with Health Enterprise Partners, explained that at the beginning of each year, the firm conducts a market mapping exercise to determine which healthcare IT categories are rising to the top of the prioritization queue of its network of hospital and health plan limited partners.

"In the past year, we have seen budgets meaningfully open for automation solutions in administrative processing, genomics-focused data and analytics offerings, aging-in-place technologies and, in particular, patient engagement platforms rooted in proven clinical use cases," he said. "We are actively looking at all of these spaces."

He pointed out that in 2018, more than $2 billion was invested into artificial intelligence and machine learning healthcare IT companies, which represented a quarter of the total dollars invested into digital health companies that year.

"We view this as a recognition of two things: the meteoric aspirations that the market has assigned to AI and machine learning's potential, and a general sense that the underlying healthcare data infrastructure has reached the point of maturity, where it is possible to realize ROI from AI/machine learning initiatives," he said.

However, he said Health Enterprise Partners is still waiting for the "breakout" to occur in adoption.

"We believe we have now reached the point where category leaders will emerge in each major healthcare AI subsector and the usage will become more widespread we have made one such investment in the clinical AI space in the last year," Mehlman said.

Heading into 2020, Mehlman said companies that cannot deliver high-six-figure, year-one ROI in the form of increased revenue or reduced cost will struggle, and companies that cannot crisply answer the question, "Who is the buyer and what is the budget?" will be challenged.

"If one applies these tests to some of the areas that have attracted the most healthcare VC investment--social determinants of health, blockchain and digital therapeutics to name a few the number of viable companies sharply drops off," he said.

Mehlman noted that while these sound like simple principles, the current environment of rapidly consolidating, budget-constrained hospitals, vertically integrating health plans, and big tech companies making inroads into healthcare has raised the bar on what is required for a healthcare startup to gain meaningful market traction.

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Healthcare venture investment in 2020: Quantum computing gets a closer look - Healthcare IT News

Delta Air Lines is embarking on a multi-year collaborative effort with IBM including joining theIBM Q Networkto explore the potential capabilities of quantum computing to transform experiences for customers and employees.

"Partnering with innovative companies like IBM is one way Delta stays on the leading edge of tech to better serve our customers and our people, while drawing the blueprints for application across our industry," saidRahul Samant, Delta's CIO. "We've done this most recently with biometrics in our international terminals and we're excited to explore how quantum computing can be applied to address challenges across the day of travel."

TheIBM Q Network is a global community of Fortune 500 companies, startups, academic institutions and research labs working to advance quantum computing and explore practical applications.

Additionally, through theIBM Q Hub at NC State University, Delta will have access to the IBM Q Network's fleet of universal hardware quantum computersfor commercial use cases and fundamental research, including the recently-announced 53-qubit quantum computer, which, the company says, has the most qubits of a universal quantum computer available for external access in the industry, to date.

"We are very excited by the addition of Delta to our list of collaborators working with us on building practical quantum computing applications," said director of IBM ResearchDario Gil. "IBM's focus, since we put the very first quantum computer on the cloud in 2016, has been to move quantum computing beyond isolated lab experiments conducted by a handful of organizations, into the hands of tens of thousands of users. We believe a clear advantage will be awarded to early adopters in the era of quantum computing and with partners like Delta, we're already making significant progress on that mission."

For more information about the IBM Q Network, go to http://www.ibm.com/quantum-computing/network/overview

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Delta Partners with IBM to Explore Quantum Computing - Database Trends and Applications

The world of quantum is the world of the very, very small. At sizes near those of atoms and smaller, the rules of physics start morphing into something unrecognizableat least to us in the regular world. While quantum physics seems bizarre, it offers huge opportunities.

Quantum physics may hold the key to vast technological improvements in computing, sensing, and communication. Quantum computing may be able to solve problems in minutes that would take lifetimes on todays computers. Quantum sensors could act as extremely high-powered antennas for the military. Quantum communication systems could be nearly unhackable. But we dont have the knowledge or capacity to take advantage of these benefitsyet.

The Department of Energy (DOE) recently announced that it will establish Quantum Information Science Centers to help lay the foundation for these technologies. As Congress put forth in the National Quantum Initiative Act, the DOEs Office of Science will make awards for at least two and up to five centers.

These centers will draw on both quantum physics and information theory to give us a soup-to-nuts understanding of quantum systems. Teams of researchers from universities, DOE national laboratories, and private companies will run them. Their expertise in quantum theory, technology development, and engineering will help each center undertake major, cross-cutting challenges. The centers work will range from discovery research up to developing prototypes. Theyll also address a number of different technical areas. Each center must tackle at least two of these subjects: quantum communication, quantum computing and emulation, quantum devices and sensors, materials and chemistry for quantum systems, and quantum foundries for synthesis, fabrication, and integration.

The impacts wont stop at the centers themselves. Each center will have a plan in place to transfer technologies to industry or other research partners. Theyll also work to leverage DOEs existing facilities and collaborate with non-DOE projects.

As the nations largest supporter of basic research in the physical sciences, the Office of Science is thrilled to head this initiative. Although quantum physics depends on the behavior of very small things, the Quantum Information Science Centers will be a very big deal.

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. For more information, please visit https://www.energy.gov/science.

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New Centers Lead the Way towards a Quantum Future - Energy.gov

ASC20 set up Quantum Computing tasks for the first time. Teams are going to use the QuEST (Quantum Exact Simulation Toolkit) running on supercomputers to simulate 30 qubits in two cases: quantum random circuits (random.c), and quantum fast Fourier transform circuits (GHZ_QFT.c). Quantum computing is a disruptive technology, considered to be the next generation high performance computing. However the R&D of quantum computers is lagging behind due to the unique properties of quantum. It adds extra difficulties for scientists to use real quantum computers to solve some of the most pressing problems such as particle physics modeling, cryptography, genetic engineering, and quantum machine learning. From this perspective, the quantum computing task presented in the ASC20 challenge, hopefully, will inspire new algorithms and architectures in this field.

The other task revealed is Language Exam Challenge. Teams will take on the challenge to train AI models on an English Cloze Test dataset, vying to achieve the highest test scores. The dataset covers multiple levels of English language tests in China, including the college entrance examination, College English Test Band 4 and Band 6, and others. Teaching the machines to understand human language is one of the most elusive and long-standing challenges in the field of AI. The ASC20 AI task signifies such a challenge, by using human-oriented problems to evaluate the performance of neural networks.

Wang Endong, ASC Challenge initiator, member of the Chinese Academy of Engineering and Chief Scientist at Inspur Group, said that through these tasks, students from all over the world get to access and learn the most cutting-edge computing technologies. ASC strives to foster supercomputing & AI talents of global vision, inspiring technical innovation.

Dr. Lu Chun, Vice President of SUSTech host of the ASC20 Finals, commented that supercomputers are important infrastructure for scientific innovation and economic development. SUSTech makes focused efforts on developing supercomputing and hosting ASC20, hoping to drive the training of supercomputing talent, international exchange and cooperation, as well as inter discipline development at SUSTech.

Furthermore, during January 15-16, 2020, the ASC20 organizing committee held a competition training camp in Beijing to help student teams prepare for the ongoing competition. HPC and AI experts from the State Key Laboratory of High-end Server and Storage Technology, Inspur, Intel, NVIDIA, Mellanox, Peng Cheng Laboratory and the Institute of Acoustics of the Chinese Academy of Sciences gathered to provide on-site coaching and guidance. Previous ASC winning teams also shared their successful experiences.

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ASC20 Finals to be Held in Shenzhen, Tasks Include Quantum Computing Simulation and AI Language Exam January 21, 2020 - Quantaneo, the Quantum...

Something to look forward to: Some of the biggest problems that need solving in the enterprise world require sifting through vast amounts of data and finding the best possible solution given a number of factors and requirements, some of which are at times unknown. For years, quantum computing has been touted as the most promising jump in computational speed for certain kind of problems, but Toshiba says revisiting classical algorithms helped it develop a new one that can leverage existing silicon-based hardware to get a faster result.

Toshiba's announcement this week claims a new algorithm it's been perfecting for years is capable of analyzing market data much more quickly and efficiently than those used in some of the world's fastest supercomputers.

The algorithm is called the "Simulated Bifurcation Algorithm," and is supposedly good enough to be used in finding accurate approximate solutions for large-scale combinatorial optimization problems. In simpler terms, it can come up with a solution out of many possible ones for a particularly complex problem.

According to its inventor, Hayato Goto, it draws inspiration from the way quantum computers can efficiently comb through many possibilities. Work on SBA started in 2015, and Goto noticed that adding new inputs to a complex system with 100,000 variables makes it easy to solve it in a matter of seconds with a relatively small computational cost.

This essentially means that Toshiba's new algorithm could be used on standard desktop computers. To give you an idea how important this development is, Toshiba demonstrated last year that SBA can get highly accurate solutions for an optimization problem with 2,000 connected variables in 50 microseconds, or 10 times faster than laser-based quantum computers.

SBA is also highly scalable, meaning it can be made to work on clusters of CPUs or FPGAs, all thanks to the contributions of Kosuke Tatsumura, another one of Toshiba's senior researchers that specializes in semiconductors.

Companies like Microsoft, Google, IBM, and many others are racing to be the first with a truly viable quantum commercial system, but so far their approaches have produced limited results that live inside their labs.

Meanwhile, scientists like Goto and Kosuke are going back to the roots by exploring ways to improve on classical algorithms. Toshiba hopes to use SBA to optimize financial operations like currency trading and rapid-fire portfolio adjustments, but this could very well be used to calculate efficient routes for delivery services and molecular precision drug development.

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Toshiba says it created an algorithm that beats quantum computers using standard hardware - TechSpot

Several companies are working to advance the technology, according to a new report.

The market for quantum networking is projected to reach $5.5 billion by 2025, according to a new report from Inside Quantum Technology (IQT).

While all computing systems rely on the ability to store and manipulate information in individual bits, quantum computers "leverage quantum mechanical phenomena to manipulate information" and to do so requires the use of quantum bits, or qubits, according to IBM.

SEE:Quantum computing: An insider's guide (TechRepublic)

Quantum computing is seen as the panacea for solving the problems computers are not equipped to handle now.

"For problems above a certain size and complexity, we don't have enough computational power on earth to tackle them,'' IBM said. This requires a new kind of computing, and this is where quantum comes in.

IQT says that quantum networking revenue comes primarily from quantum key distribution (QK), quantum cloud computing, and quantum sensor networks. Eventually, these strands will merge into a Quantum Internet, the report said.

Cloud access to quantum computers is core to the business models of many leading quantum computer companiessuch as IBM, Microsoft and Rigettias well as several leading academic institutions, according to the report.

Microsoft, for instance, designed a special programming language for quantum computers, called Q#, and released a Quantum Development Kit to help programmers create new applications, according to CBInsights.

One of Google's quantum computing projects involves working with NASA to apply the tech's optimization abilities to space travel.

The Quantum Internet network will have the same "geographical breadth of coverage as today's internet," the IQT report stated.

It will provide a powerful platform for communications among quantum computers and other quantum devices, the report said.

And will enable a quantum version of the Internet of Things. "Finally, quantum networks can be the most secure networks ever built completely invulnerable if constructed properly," the report said.

The report, "Quantum Networks: A Ten-Year Forecast and Opportunity Analysis," forecasts demand for quantum network equipment, software and services in both volume and value terms.

"The time has come when the rapidly developing quantum technology industry needs to quantify the opportunities coming out of quantum networking," said Lawrence Gasman, president of Inside Quantum Technology, in a statement.

Quantum Key Distribution (QKD) adds unbreakable coding of key distribution to public key encryption, making it virtually invulnerable, according to the report.

QKD is the first significant revenue source to come from the emerging Quantum Internet and will create almost $150 million in revenue in 2020, the report said.

QKD's early success is due to potential usersbig financial and government organizationshave an immediate need for 100% secure encryption, the IQT report stated.

By 2025, IQT projects that revenue from "quantum clouds" are expected to exceed $2 billion.

Although some large research and government organizations are buying quantum computers for on-premise use, the high cost of the machines coupled with the immaturity of the technology means that the majority of quantum users are accessing quantum through clouds, the report explained.

Quantum sensor networks promise enhanced navigation and positioning and more sensitive medical imaging modalities, among other use cases, the report said.

"This is a very diverse area in terms of both the range of applications and the maturity of the technology."

However, by 2025 revenue from quantum sensors is expected to reach about $1.2 billion.

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Quantum networking projected to be $5.5 billion market in 2025 - TechRepublic

UncategorizedByJohn Breaux|January 22, 2020

Some say that we are in the midst of a new technological revolution, with emerging technologies taking shape to transform the world we live in. As we step into a new decade, expect to see a handful of amazing advancements in technology that will dramatically shape our society at large.

Weve been told for years that self-driving cars are the future, but this decade will bring us the greatest advancements in this field as of yet. Companies have been researching and testing autonomous fleets of cars for years now, and some are finally gearing up to deploy them in the real world. Tesla has already released a self-driving feature in its popular electric vehicles, while Google-owned Waymo has completed a trial of autonomous taxi systems in California where it successfully transported more than 6000 people.

This radically powerful form of computing will continue to reach more practical applications throughout the decade. Quantum computers are capable of performing exponentially more powerful calculations when compared to traditional computing, but the size and power required to run them makes them difficult to use in a more practical sense. Further research in quantum, computing will allow greater application for solving real-world problems.

Augmenting our bodies with technology will become more common as wearable devices will allow us to improve everything from hearing to sight. Examples include devices and implants that will be able to enhance sensory capabilities, improve health, and contribute to a heightened quality of life and functional performance.

The advent of 5G will perhaps be one of the most impactful technologies for the many starting this year and proceeding onwards. 5G networks will have the capability of connecting us to the digital world in ways weve never had before, affording us blazing fast speeds of nearly 10 Gb/s. The speed of 5G will allow for seamless control of vast autonomous car fleets, precise robotic surgery, or streaming of 4K video with no buffering.

Drones are already a pivotal piece of technology in areas including transportation, surveillance, and logistics. Swarm robotics will be a new multi-robot system inspired by nature that will have major potential in completing tasks with unparalleled efficiency. Applications could include providing post-disaster relief, geological surveying, and even farming. Swarm robotics will be able to accomplish tasks through cooperative behavior while adapting to situations in ways that would not be possible with a single drone.

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5 Emerging Technologies That Will Shape this Decade - San Diego Entertainer Magazine

Having led a Bitcoin mining firm for over two years, I've come to realize the importance of computing power. Computing power connects the real (chip energy) and virtual (algorithm) dimensions of our world. Under the condition that the ownership of the assets remains unchanged, computing power is an intangible asset that can be used and circulated. It is a commercialized technical service and a consumption investment. This is a remarkable innovation for mankind, and it is an upgrade for the digital economy.

2020 marks the birth year of the computing power infrastructure. Our world is at the beginning of a new economic and technological cycle. We have entered the digital economic civilization. This wave of technology is driven by the combination of AI, 5G, quantum computing, big data and blockchain. People have started realizing that in the age of the digital economy, computing power is the most important and innovative form of productivity.

Computing power is not just technical but also economic innovation. It's a small breakthrough at the fundamental level with impact that will be immeasurable. And people have finally seen the value of the bottom layer through the 10 years of crypto mining evolution.

However, there are two major problems faced by the entire technological landscape: First is insufficient computing power. Second is the dominance of centralized computing power, which creates a monopoly and gives rise to manipulation problems and poor data security.

How does more computing power help?

Artificial Intelligence

Mining Bitcoin has allowed my company to build the foundation of computing infrastructure, so we are planning to eventually expand into AI computing. This experience has further shown me the importance of working toward developing more computing power if tech leaders want to continue creating innovative technologies.

Consider this: For an AI system to recognize someone's voice or identify an animal or a human being, it first needs to process millions of audio, video or image samples. It then learns to differentiate between two different pitches of voices or to differentiate faces based on various facial features. To reach that level of precision, an AI model needs to be fed a tremendous amount of data.

It is only possible to do that if we have powerful computers that can process millions of data points every single second. The more the computing power, the faster we can feed the data to train the AI system, resulting in a shorter span for the AI to reach near-perfection, i.e., human-level intelligence.

The computing power required by AI has been doubling roughly every three and a half months since 2012. The need to build better AI has made it mandatory to keep up with this requirement for more computing power. Tech companies are leaving no stone unturned to rise to this demand.

It is almost as if computing power is now an asset into which investors and organizations are pouring millions of dollars. They are constantly testing and modifying their best chips to produce more productive versions of them. The results of this investment are regularly seen in the form of advanced, more compact chips capable of producing higher computing power while consuming lesser energy.

For new technological breakthroughs, computing power itself has become the new "production material" and "energy." Computing power is the fuel of our technologically advanced society. I've observed it is driving the development in various technological landscapes, such as AI, graphics computing, 5G and cryptocurrency.

Cryptocurrency Mining

Similar to AI, the decentralized digital economy sector also relies on high computing power. Transactions of cryptocurrencies, such as Bitcoin, are validated through a decentralized process called "mining." Mining requires miners across the world to deploy powerful computers to find the solution or the hash to a cryptographic puzzle that proves the legitimacy of each transaction requested on the blockchain.

The bad news, however, is that the reward to mine Bitcoin is halved almost every four years. This means that following May 20, 2020 the next halving date miners who mine Bitcoin would receive half the reward per block compared to what they do now. Two primary factors that compensate for the halving of rewards are an increase in the price of Bitcoin and advanced chips with high computing power.

Miners run not one but multiple high-end graphics processing units to mine Bitcoin, which is an electricity-intensive process. The only way to keep mining profitably is to invest in better chips that produce more computing power with lower electricity consumption. This helps miners process more hashes per second (i.e., the hashrate) to get to the right hash and attain the mining reward.

So far, mining chip producers have delivered the promise of more efficient chips leading to an increase in the mining hashrate from 50 exahashes per second to 90 exahashes per second in the past six months. Per the reports, the efficiency of the latest chips combined with increased Bitcoin prices has helped keep the mining business highly profitable since the previous halving.

High computing power has become an addiction we humans are not getting rid of in the foreseeable future. With our growing fondness for faster computer applications and more humanlike AI, it's likely that we demand faster and more perfect versions of the systems we use today. A viable way to fulfill this would be to produce more computing power.

The two biggest challenges that lie in our way are producing clean electricity at lower costs and developing chips that have a lower electricity-consumption-to-computing-power-production ratio. The core of industrial production competition today lies in the cost of producing electricity. Low energy prices enable us to provide stable services. For example, there is an abundance of hydro-electric power in southwest China, and cooperative data centers are located there so they can harness the hydropower.

If we could make low-cost, clean energy available everywhere, we'd cut the cost of producing computing power. When this energy is used by power-efficient computing chips, the total cost drops even more and high computing power becomes highly affordable.

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The Need For Computing Power In 2020 And Beyond - Forbes