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Category: supercomputing – Page 41

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2022 has been a dynamic year for quantum computing. With commercial breakthroughs such as the UK Ministry of Defence (MoD) investing in its first quantum computer, the launch of the world’s first quantum computer capable of advantage over the cloud and the Nobel Prize in Physics awarded for ground-breaking experiments with entangled photons, the industry is making progress.

At the same time, 2022 saw the tremendous accomplishment of the exaflop barrier broken with the Frontier supercomputer. At a cost of roughly $600 million and requiring more than 20 megawatts of power, we are approaching the limits of what classical computing approaches can do on their own. Often for practical business reasons, many companies are not able to fully exploit the increasing amount of data available to them. This hampers digital transformation across areas most reliant on high-performance computing (HPC): healthcare, defense, energy and finance.

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Not going to happen unless some “doomsdayers” decide to take man back to analog. Perish the thought!

Which brings us to Big Blue – not Big Brother – and its move to take artificial intelligence into the cloud minus all the hardware.

Yes, IBM (and let’s not leave out Red Hat, IBM’s core cloud player) has found another way to tout its cloud computing business by creating what it calls an artificial intelligence-focused supercomputer that exists in the cloud.

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Researchers in the US developed a new energy-based benchmark for quantum advantage and used it to demonstrate noisy intermediate-scale quantum (NISQ) computers that use several orders of magnitude less energy than the world’s most powerful supercomputer. Quantum computing is a branch of computer science that focuses on the development of technologies based on quantum theory principles.

Quantum computing solves problems that are too complex for classical computing by utilizing the unique properties of quantum physics. The question of whether a quantum computer can perform calculations beyond the reach of even the most powerful conventional supercomputer is becoming increasingly relevant as quantum computers become larger and more reliable. This ability, dubbed “quantum supremacy,” marks the transition of quantum computers from scientific curiosity to useful devices. Scientists predict that Quantum computing is better than supercomputers as it performs tasks a million times faster. Quantum computers can handle complex calculations easily because they are built based on quantum principles that go beyond classical physics.

Quantum computers and supercomputers are extremely powerful machines used for complex calculations, problem solving, and data analysis. While both have the potential to revolutionize computing technology, they have significant speed and capability differences. In 2019, Google’s quantum computer performed a calculation that would take the world’s most powerful computer 10,000 years to complete. It is the seed for the world’s first fully functional quantum computer, which will be capable of producing better medicines, developing smarter artificial intelligence, and solving cosmic mysteries. Theoretical physicist John Preskill proposed a formulation of quantum supremacy, or the superiority of quantum computers, in 2012. He dubbed it the moment when quantum computers can perform tasks that ordinary computers cannot. To quickly crunch large amounts of data and achieve a single result, supercomputers employ a traditional computing approach with multiple processors.

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Researchers from the University of Sussex and Universal Quantum have demonstrated for the first time that quantum bits (qubits) can directly transfer between quantum computer microchips and demonstrated this with record-breaking speed and accuracy. This breakthrough resolves a major challenge in building quantum computers large and powerful enough to tackle complex problems that are of critical importance to society.

Today, quantum computers operate on the 100-qubit scale. Experts anticipate millions of qubits are required to solve important problems that are out of reach of today’s most powerful supercomputers. There is a global quantum race to develop quantum computers that can help in many important societal challenges from to making fertilizer production more energy efficient and solving important problems in nearly every industry, ranging from aeronautics to the financial sector.

In the research paper, published today in Nature Communications, the scientists demonstrate how they have used a new and powerful technique, which they dub “UQ Connect,” to use electric field links to enable qubits to move from one quantum computing microchip module to another with unprecedented speed and precision. This allows chips to slot together like a jigsaw puzzle to make a more powerful quantum .

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This is still the beginning of what AI can possibly do.

IBM’s Watson supercomputer is working wonders in an area where OpenAI’s ChatGPT does not have much to offer, the stock market. An exchange-traded fund (ETF) is using the power of artificial intelligence (AI) to balance its portfolio and has done pretty well for itself this year, ETF.

PhonlamaiPhoto/iStock.

ChatGPT responded that the stock market was too hard to predict and that it did not have access to live stock data. However, ETF Managers Group, in partnership with a fintech firm Equbot has been using AI to pick holdings in the $102 million AI-powered Equity ETF (AIEQ) since 2017. The fund has doubled the returns on the Vanguard Total Stock Market ETF (VTI) this year.

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Physicists have invented a new type of analog quantum computer that can tackle hard physics problems that the most powerful digital supercomputers cannot solve.

New research published in Nature Physics by collaborating scientists from Stanford University in the U.S. and University College Dublin (UCD) in Ireland has shown that a novel type of highly-specialized analog computer, whose circuits feature quantum components, can solve problems from the cutting edge of quantum physics that were previously beyond reach. When scaled up, such devices may be able to shed light on some of the most important unsolved problems in physics.

For example, scientists and engineers have long wanted to gain a better understanding of superconductivity, because existing —such as those used in MRI machines, and long-distance energy-efficient power networks—currently operate only at extremely low temperatures, limiting their wider use. The holy grail of materials science is to find materials that are superconducting at room temperature, which would revolutionize their use in a host of technologies.

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Tech giants from Google to Amazon and Alibaba —not to mention nation-states vying for technological supremacy—are racing to dominate this space. The global quantum-computing industry is projected to grow from $412 million in 2020 to $8.6 billion in 2027, according to an International Data Corp. analysis.

Whereas traditional computers rely on binary “bits”—switches either on or off, denoted as 1s and 0s—to process information, the “qubits” that underpin quantum computing are tiny subatomic particles that can exist in some percentage of both states simultaneously, rather like a coin spinning in midair. This leap from dual to multivariate processing exponentially boosts computing power. Complex problems that currently take the most powerful supercomputer several years could potentially be solved in seconds. Future quantum computers could open hitherto unfathomable frontiers in mathematics and science, helping to solve existential challenges like climate change and food security. A flurry of recent breakthroughs and government investment means we now sit on the cusp of a quantum revolution. “I believe we will do more in the next five years in quantum innovation than we did in the last 30,” says Gambetta.

But any disrupter comes with risks, and quantum has become a national-security migraine. Its problem-solving capacity will soon render all existing cryptography obsolete, jeopardizing communications, financial transactions, and even military defenses. “People describe quantum as a new space race,” says Dan O’Shea, operations manager for Inside Quantum Technology, an industry publication. In October, U.S. President Joe Biden toured IBM’s quantum data center in Poughkeepsie, N.Y., calling quantum “vital to our economy and equally important to our national security.” In this new era of great-power competition, China and the U.S. are particularly hell-bent on conquering the technology lest they lose vital ground. “This technology is going to be the next industrial revolution,” says Tony Uttley, president and COO for Quantinuum, a Colorado-based firm that offers commercial quantum applications. “It’s like the beginning of the internet, or the beginning of classical computing.”

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The expertise of GPT3.5 at the industrial scale.

If you are tired of your requests to access ChatGPT being waitlisted repeatedly, Microsoft has some good news for you. The chatbot is coming soon to Azure Open AI services, where businesses can access the most advanced artificial intelligence (AI) in the world, the company said in a press release.

ChatGPT, the chatbot released on November 30 last year, has caught the imagination of engineers and non-engineers alike. The large language model used by the platform allows the AI to help answer user queries in a conversational style.

NurPhoto/Getty.

Microsoft teamed up with OpenAI in July 2019 to accelerate breakthroughs in the field of AI. On its part, Microsoft used its expertise in computing to build AI supercomputers exclusively for OpenAI and, since November 2021, has been offering the Azure OpenAI service for enterprise customers.

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My first computer had a CPU with 3,510 transistors. We now live in a world where you can get chips with over a trillion transistors.

“This a data centre accelerator that contains 146 billion transistors.”

I checked and the article didn’t include the transistors that made up the L4 cache memory on the chip. The actual total is 1.25 trillion transistors plus another 1.1 trillion capacitors.

This chip is coming out later this year and I expect to see it used in large quantities in supercomputers and in the server market in general.

Quite impressive!

By the way, the record for transistors on a chip is 2.6 trillion with the latest Cerebras chip and that chip is two years old and doesn’t even use any chiplets, so is just one giant chip. (Compared to the MI300 composed of 41 chiplets!)

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