At its Quantum Summit 2023, IBM took the stage with an interesting spirit: one of almost awe at having things go their way. But the quantum of today the one thats changing IBMs roadmap so deeply on the back of breakthrough upon breakthrough was hard enough to consolidate. As IBM sees it, the future of quantum computing will hardly be more permissive. IBM announced cutting-edge devices at the event, including the 133-qubit Heron Quantum Processing Unit (QPU), which is the company's first utility-scale quantum processor, and the self-contained Quantum System Two, a quantum-specific supercomputing architecture. And further improvements to the cutting-edge devices are ultimately required.

Each breakthrough that afterward becomes obsolete is another accelerating bump against what we might call quantum's "plateau of understanding." Weve already crested this plateau with semiconductors, so much so that the latest CPUs and GPUs are reaching practical, fundamental design limits where quantum effects start ruining our math. Conquering the plateau means that utility and understanding are now enough for research and development to be somewhat self-sustainable at least for a Moores-law-esque while.

IBMs Quantum Summit serves as a bookend of sorts for the companys cultural and operational execution, and its 2023 edition showcased an energized company that feels like it's opening up the doors towards a "quantum-centric supercomputing era." That vision is built on the company's new Quantum Processing Unit, Heron, which showcases scalable quantum utility at a 133-qubit count and already offers things beyond what any feasible classical system could ever do. Breakthroughs and a revised understanding of its own roadmap have led IBM to present its quantum vision in two different roadmaps, prioritizing scalability in tandem with useful, minimum-quality rather than monolithic, hard-to-validate, high-complexity products.

IBM's announced new plateau for quantum computing packs in two particular breakthroughs that occurred in 2023. One breakthrough relates to a groundbreaking noise-reduction algorithm (Zero Noise Extrapolation, or ZNE) which we covered back in July basically a system through which you can compensate for noise. For instance, if you know a pitcher tends to throw more to the left, you can compensate for that up to a point. There will always be a moment where you correct too much or cede ground towards other disruptions (such as the opponent exploring the overexposed right side of the court). This is where the concept of qubit quality comes into account the more quality your qubits, the more predictable both their results and their disruptions and the better you know their operational constraints then all the more useful work you can extract from it.

The other breakthrough relates to an algorithmic improvement of epic proportions and was first pushed to Arxiv on August 15th, 2023. Titled High-threshold and low-overhead fault-tolerant quantum memory, the paper showcases algorithmic ways to reduce qubit needs for certain quantum calculations by a factor of ten. When what used to cost 1,000 qubits and a complex logic gate architecture sees a tenfold cost reduction, its likely youd prefer to end up with 133-qubit-sized chips chips that crush problems previously meant for 1,000 qubit machines.

Enter IBMs Heron Quantum Processing Unit (QPU) and the era of useful, quantum-centric supercomputing.

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The two-part breakthroughs of error correction (through the ZNE technique) and algorithmic performance (alongside qubit gate architecture improvements) allow IBM to now consider reaching 1 billion operationally useful quantum gates by 2033. It just so happens that its an amazing coincidence (one born of research effort and human ingenuity) that we only need to keep 133 qubits relatively happy within their own environment for us to extract useful quantum computing from them computing that we wouldnt classically be able to get anywhere else.

The Development and Innovation roadmap showcase how IBM is thinking about its superconducting qubits: as weve learned to do with semiconductors already, mapping out the hardware-level improvements alongside the scalability-level ones. Because as weve seen through our supercomputing efforts, theres no such thing as a truly monolithic approach: every piece of supercomputing is (necessarily) efficiently distributed across thousands of individual accelerators. Your CPU performs better by knitting and orchestrating several different cores, registers, and execution units. Even Cerebras Wafer Scale Engine scales further outside its wafer-level computing unit. No accelerator so far no unit of computation - has proven powerful enough that we dont need to unlock more of its power by increasing its area or computing density. Our brains and learning ability seem to provide us with the only known exception.

IBMs modular approach and its focus on introducing more robust intra-QPU and inter-QPU communication for this years Heron shows its aware of the rope it's walking between quality and scalability. The thousands of hardware and scientist hours behind developing the tunable couplers that are one of the signature Heron design elements that allow parallel execution across different QPUs is another. Pushing one lever harder means other systems have to be able to keep up; IBM also plans on steadily improving its internal and external coupling technology (already developed with scalability in mind for Heron) throughout further iterations, such as Flamingos planned four versions which still only end scaling up to 156 qubits per QPU.

Considering how you're solving scalability problems and the qubit quality x density x ease of testing equation, the ticks - the density increases that don't sacrifice quality and are feasible from a testing and productization standpoint - may be harder to unlock. But if one side of development is scalability, the other relates to the quality of whatever youre actually scaling in this case, IBMs superconducting qubits themselves. Heron itself saw a substantial rearrangement of its internal qubit architecture to improve gate design, accessibility, and quantum processing volumes not unlike an Intel tock. The planned iterative improvements to Flamingo's design seem to confirm this.

Theres a sweet spot for the quantum computing algorithms of today: it seems that algorithms that fit roughly around a 60-gate depth are complex enough to allow for useful quantum computing. Perhaps thinking about Intels NetBurst architecture with its Pentium 4 CPUs is appropriate here: too deep an instruction pipeline is counterproductive, after a point. Branch mispredictions are terrible across computing, be it classical or quantum. And quantum computing as we still currently have it in our Noisy Intermediate-Scale Quantum (NISQ)-era is more vulnerable to a more varied disturbance field than semiconductors (there are world overclocking records where we chill our processors to sub-zero temperatures and pump them with above-standard volts, after all). But perhaps that comparable quantum vulnerability is understandable, given how were essentially manipulating the essential units of existence atoms and even subatomic particles into becoming useful to us.

Useful quantum computing doesnt simply correlate with an increasing number of available in-package qubits (announcements of 1,000-qubit products based on neutral atom technology, for instance). But useful quantum computing is always stretched thin throughout its limits, and if it isnt bumping against one fundamental limit (qubit count), its bumping against another (instability at higher qubit counts); or contending with issues of entanglement coherence and longevity; entanglement distance and capability; correctness of the results; and still other elements. Some of these scalability issues can be visualized within the same framework of efficient data transit between different distributed computing units, such as cores in a given CPU architecture, which can themselves be solved in a number of ways, such as hardware-based information processing and routing techniques (AMDs Infinity Fabric comes to mind, as does Nvidia's NVLink).

This feature of quantum computing already being useful at the 133-qubit scale is also part of the reason why IBM keeps prioritizing quantum computing-related challenges around useful algorithms occupying a 100 by 100 grid. That quantum is already useful beyond classical, even in gate grids that are comparably small to what we can achieve with transistors, and points to the scale of the transition of how different these two computational worlds are.

Then there are also the matters of error mitigation and error correction, of extracting ground-truth-level answers to the questions we want our quantum computer to solve. There are also limitations in our way of utilizing quantum interference in order to collapse a quantum computation at just the right moment that we know we will obtain from it the result we want or at least something close enough to correct that we can then offset any noise (non-useful computational results, or the difference of values ranging between the correct answer and the not-yet-culled wrong ones) through a clever, groundbreaking algorithm.

The above are just some of the elements currently limiting how useful qubits can truly be and how those qubits can be manipulated into useful, algorithm-running computation units. This is usually referred to as a qubits quality, and we can see how it both does and doesnt relate to the sheer number of qubits available. But since many useful computations can already be achieved with 133-qubit-wide Quantum Processing Units (theres a reason IBM settled on a mere 6-qubit increase from Eagle towards Heron, and only scales up to 156 units with Flamingo), the company is setting out to keep this optimal qubit width for a number of years of continuous redesigns. IBM will focus on making correct results easier to extract from Heron-sized QPUs by increasing the coherence, stability, and accuracy of these 133 qubits while surmounting the arguably harder challenge of distributed, highly-parallel quantum computing. Its a onetwo punch again, and one that comes from the bump in speed at climbing ever-higher stretches of the quantum computing plateau.

But there is an admission that its a barrier that IBM still wants to punch through its much better to pair 200 units of a 156-qubit QPU (that of Flamingo) than of a 127-qubit one such as Eagle, so long as efficiency and accuracy remain high. Oliver Dial says that Condor, "the 1,000-qubit product", is locally running up to a point. It was meant to be the thousand-qubit processor, and was a part of the roadmap for this years Quantum Summit as much as the actual focus, Heron - but its ultimately not really a direction the company thinks is currently feasible.

IBM did manage to yield all 1,000 Josephson Junctions within their experimental Condor chip the thousand-qubit halo product that will never see the light of day as a product. Its running within the labs, and IBM can show that Condor yielded computationally useful qubits. One issue is that at that qubit depth, testing such a device becomes immensely expensive and time-consuming. At a basic level, its harder and more costly to guarantee the quality of a thousand qubits and their increasingly complex possibility field of interactions and interconnections than to assure the same requirements in a 133-qubit Heron. Even IBM only means to test around a quarter of the in-lab Condor QPUs area, confirming that the qubit connections are working.

But Heron? Heron is made for quick verification that its working to spec that its providing accurate results, or at least computationally useful results that can then be corrected through ZNE and other techniques. That means you can get useful work out of it already, while also being a much better time-to-market product in virtually all areas that matter. Heron is what IBM considers the basic unit of quantum computation - good enough and stable enough to outpace classical systems in specific workloads. But that is quantum computing, and that is its niche.

Heron is IBMs entrance into the mass-access era of Quantum Processing Units. Next years Flamingo builds further into the inter-QPU coupling architecture so that further parallelization can be achieved. The idea is to scale at a base, post-classical utility level and maintain that as a minimum quality baseline. Only at that point will IBM maybe scale density and unlock the appropriate jump in computing capability - when that can be similarly achieved in a similarly productive way, and scalability is almost perfect for maintaining quantum usefulness.

Theres simply never been the need to churn out hundreds of QPUs yet the utility wasnt there. The Canaries, Falcons, and Eagles of IBMs past roadmap were never meant to usher in an age of scaled manufacturing. They were prototypes, scientific instruments, explorations; proofs of concept on the road towards useful quantum computing. We didnt know where usefulness would start to appear. But now, we do because weve reached it.

Heron is the design IBM feels best answers that newly-created need for a quantum computing chip that actually is at the forefront of human computing capability one that can offer what no classical computing system can (in some specific areas). One that can slice through specific-but-deeper layers of our Universe. Thats what IBM means when it calls this new stage the quantum-centric supercomputing one.

Classical systems will never cease to be necessary: both of themselves and the way they structure our current reality, systems, and society. They also function as a layer that allows quantum computing itself to happen, be it by carrying and storing its intermediate results or knitting the final informational state mapping out the correct answer Quantum computing provides one quality step at a time. The quantum-centric bit merely refers to how quantum computing will be the core contributor to developments in fields such as materials science, more advanced physics, chemistry, superconduction, and basically every domain where our classical systems were already presenting a duller and duller edge with which to improve upon our understanding of their limits.

However, through IBMs approach and its choice of transmon superconducting qubits, a certain difficulty lies in commercializing local installations. Quantum System Two, as the company is naming its new almost wholesale quantum computing system, has been shown working with different QPU installations (both Heron and Eagle). When asked about whether scaling Quantum System Two and similar self-contained products would be a bottleneck towards technological adoption, IBMs CTO Oliver Dial said that it was definitely a difficult problem to solve, but that he was confident in their ability to reduce costs and complexity further in time, considering how successful IBM had already proven in that regard. For now, its easier for IBMs quantum usefulness to be unlocked at a distance through the cloud and its quantum computing framework, Quiskit than it is to achieve it by running local installations.

Quiskit is the preferred medium through which users can actually deploy IBM's quantum computing products in research efforts just like you could rent X Nvidia A100s of processing power through Amazon Web Services or even a simple Xbox Series X console through Microsofts xCloud service. On the day of IBM's Quantum Summit, that freedom also meant access to the useful quantum circuits within IBM-deployed Heron QPUs. And it's much easier to scale access at home, serving them through the cloud, than delivering a box of supercooled transmon qubits ready to be plugged and played with.

Thats one devil of IBMs superconducting qubits approach not many players have the will, funding, or expertise to put a supercooled chamber into local operation and build the required infrastructure around it. These are complex mechanisms housing kilometers of wiring - another focus of IBMs development and tinkering culminating in last years flexible ribbon solution, which drastically simplified connections to and from QPUs.

Quantum computing is a uniquely complex problem, and democratized access to hundreds or thousands of mass-produced Herons in IBMs refrigerator-laden fields will ultimately only require, well a stable internet connection. Logistics are what they are, and IBMs Quantum Summit also took the necessary steps to address some needs within its Quiskit runtime platform by introducing its official 1.0 version. Food for thought is realizing that the era of useful quantum computing seems to coincide with the beginning of the era of Quantum Computing as a service as well. That was fast.

The era of useful, mass-producible, mass-access quantum computing is what IBM is promising. But now, theres the matter of scale. And theres the matter of how cost-effective it is to install a Quantum System Two or Five or Ten compared to another qubit approach be it topological approaches to quantum computing, or oxygen-vacancy-based, ion-traps, or others that are an entire architecture away from IBMs approach, such as fluxonium qubits. Its likely that a number of qubit technologies will still make it into the mass-production stage and even then, we can rest assured that everywhere in the road of human ingenuity lie failed experiments, like Intels recently-decapitated Itanium or AMDs out-of-time approach to x86 computing in Bulldozer.

It's hard to see where the future of quantum takes us, and its hard to say whether it looks exactly like IBMs roadmap the same roadmap whose running changes we also discussed here. Yet all roadmaps are a permanently-drying painting, both for IBM itself and the technology space at large. Breakthroughs seem to be happening daily on each side of the fence, and its a fact of science that the most potential exists the earlier the questions we ask. The promising qubit technologies of today will have to answer to actual interrogations on performance, usefulness, ease and cost of manipulation, quality, and scalability in ways that now need to be at least as good as what IBM is proposing with its transmon-based superconducting qubits, and its Herons, and scalable Flamingos, and its (still unproven, but hinted at) ability to eventually mass produce useful numbers of useful Quantum Processing Units such as Heron. All of that even as we remain in this noisy, intermediate-scale quantum (NISQ) era.

Its no wonder that Oliver Dial looked and talked so energetically during our interview: IBM has already achieved quantum usefulness and has started to answer the two most important questions quality and scalability, Development, and Innovation. And it did so through the collaboration of an incredible team of scientists to deliver results years before expected, Dial happily conceded. In 2023, IBM unlocked useful quantum computing within a 127-qubit Quantum Processing Unit, Eagle, and walked the process of perfecting it towards the revamped Heron chip. Thats an incredible feat in and of itself, and is what allows us to even discuss issues of scalability at this point. Its the reason why a roadmap has to shift to accommodate it and in this quantum computing world, its a great follow-up question to have.

Perhaps the best question now is: how many things can we improve with a useful Heron QPU? How many locked doors have sprung ajar?

See more here:
IBM demonstrates useful Quantum computing within 133-qubit Heron, announces entry into Quantum-centric ... - Tom's Hardware

Insider Brief

PRESS RELEASE A consortium of joint research partners announced the successful development of Japans third superconducting quantum computer installed at Osaka University.

The partnership includes the Center for Quantum Information and Quantum Biology at Osaka University, RIKEN, the Advanced Semiconductor Research Center at the National Institute of Advanced Industrial Science and Technology (AIST), the Superconducting ICT Laboratory at the National Institute of Information and Communications Technology (NICT), Amazon Web Services, e-trees.Japan, Inc., Fujitsu Limited, NTT Corporation (NTT), QuEL, Inc., QunaSys Inc., and Systems Engineering Consultants Co.,LTD. (SEC).

Starting December 22, 2023, the partners will provide users in Japan access to the newly developed computer via the cloud, enabling researchers to execute quantum algorithms, improve and verify the operation of software, and explore use cases remotely.

The newly developed superconducting quantum computer uses a 64 qubit chip provided by RIKEN, which leverages the same design as the chip in RIKENs first superconducting quantum computer, which was unveiled to users in Japan as a cloud service for non-commercial use on March 27, 2023.

For the new quantum computer, the research team sourced more domestically manufactured components (excluding the refrigerator). The research team confirmed that the new quantum computer, including its components, provides sufficient performance and will utilize the computer as a test bed for components made in Japan.

Moving forward, the research group will operate the new computer while improving its software and other systems for usage including the processing of heavy workloads on the cloud. The research team anticipates that the computer will drive further progress in the fields of machine learning and the development of practical quantum algorithms, enable the exploration of new use cases in material development and drug discovery, and contribute to the solution of optimization problems to mitigate environmental impact.

The joint research group is comprised of: Dr. Masahiro Kitagawa, (Professor, Graduate School of Engineering Science, Director of the Center for Quantum Information and Quantum Biology at Osaka University), Dr. Makoto Negoro (Associate Professor, Vice Director of the Center for Quantum Information and Quantum Biology at Osaka University), Dr. Yasunobu Nakamura (Director of the RIKEN Center for Quantum Computing (RQC)), Dr. Katsuya Kikuchi (Group Leader of the 3D Integration System Group of the Device Technology Research Institute at AIST), Dr. Hirotaka Terai (Executive Researcher at the Superconductive ICT Device Laboratory at the Kobe Frontier Research Center of the Advanced ICT Research Institute of NICT), Dr. Yoshitaka Haribara (Senior Startup Machine Learning and Quantum Solutions Architect, Amazon Web Services), Dr. Takefumi Miyoshi(Director of e-trees.Japan, Inc., Specially Appointed Associate Professor, Center for Quantum Information and Quantum Biology at Osaka University, CTO of QuEL, Inc.), Dr. Shintaro Sato (Head of Quantum Laboratory, Fujitsu Research, Fujitsu Limited), Dr. Yuuki Tokunaga (Distinguished Researcher at NTT Computer & Data Science Laboratories), Yosuke Ito (CEO of QuEL, Inc.), Keita Kanno (CTO of QunaSys Inc.), and Ryo Uchida (Chief Technologist of Systems Engineering Consultants Co.,LTD. (SEC)).

For more information: Center for Quantum Information and Quantum Biology, Osaka University

This research was supported by grants from:

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Japan's Third Superconducting Quantum Computer Installed at Osaka University - The Quantum Insider

Luton, Dec. 20, 2023 (GLOBE NEWSWIRE) -- Quantum AI is set to bring the power of quantum computing to the public and has already reached a stunning quantum volume (QV) score of 14,082 in a year since its inception.

Quantum AI Ltd. was conceived by Finlay and Qaiser Sajjad during their time as students at MIT. They were inspired by the exclusive use of new-age technology by the elites on Wall Street. Recognising the transformative power of this technology, they were determined to make its potential accessible to all. Thus, the platform was born, and it has evolved and flourished in just a short time.

Quantum AI

Often, everyday traders have limited access to such advanced tools.

We are fueled by the belief that the power of quantum computing should not be confined to the financial giants but should be available to empower amateur traders as well, asserted the founders of the platform. Since its launch in 2022, they have worked to achieve this vision and have become a significant force in the industry.

The platform combines the power of the technology with the strength of artificial intelligence. By using these latest technologies, including machine learning, algorithms that are more than just lines of code have been created. They harness the potential of quantum mechanics and deep learning to analyse live data in unique ways.

Our quantum system leverages quantum superposition and coherence, providing a quantum advantage through sophisticated simulation and annealing techniques, added the founders.

Quantum AI has shown exceptional results in a brief period. It has received overwhelmingly positive reviews from customers, highlighting the enhanced speed and accuracy of trading. The transformative and groundbreaking impact the platform has had on trading is evident in its growth to 330,000 active members. Notably, it has nearly 898 million lines of code and an impressive quantum value score of 14,082. The performance on this benchmark that IBM established is a massive testament to the impact quantum AI has had in a short span of time.

According to the founders, they have bigger plans on the horizon to take the power of the technology to the public. Quantum AI is growing its team of experts and expanding its operations in Australia and Canada. Its goal of democratising the power of technology is well on its way to being realised. With trading being the first thing they cracked to pay the bills the main focus has turned to aviation, haulage and even e-commerce. The power of

To learn more about the platform and understand the transformative power of the technology for traders, one can visit https://quantumai.co/.

About Quantum AI

With the aim of democratising the power and potential of quantum computing, the company was founded by Finlay and Qaiser Sajjad during their time at MIT. Since its establishment, it has grown to over 330,000 active members and 18 full-time employees, alongside winning the trust of its customers.

###

Media Contact

Quantum AIPR Manager: Nadia El-Masri Email: nadia.el.masri@quantumai.coAddress: Quantum AI Ltd, 35 John Street, Luton, United Kingdom, LU1 2JEPhone: +442035970878URL: https://quantumai.co/

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Quantum AI Brings the Power of Quantum Computing to the Public - GlobeNewswire

Dell predicts that generative AI will move from theory to practice, powerful PCs will unlock more AI advancements and zero trust will become central to cybersecurity practices.

Dell Technologies Ireland MD Catherine Doyle has shared predictions on how technological advancements will impact businesses in 2024.

While AI was certainly one of the hottest topics of 2023, Doyle believes generative AI will be the centre of business focus and that 2024 will be all about putting AI into action.

The first step on the AI journey should be to organise and structure data which will help avoid AI sprawl, Doyle said.

Last year, the company made five predictions for 2023 that included advancements in AI, quantum computing and a greater role for technology in employee satisfaction.

Dell believes these advanced technologies will remain a central focus next year, but also believes zero-trust technologies and a growing focus on sustainability in IT will help organisations to innovate, enhance productivity and remain secure.

Breakthrough technologies will help Irish businesses to navigate new challenges that may emerge in the coming months and to innovate at speed, Doyle said.

Here are five predictions Dell has shared on how technology will advance in 2024.

Doyle said that 2023 saw various creative ideas on how generative AI will transform businesses, but claimed that there are very few real-world examples of generative AI in action.

As we enter 2024, [generative] AI projects will start to be business ready with visible productivity gains becoming evident, Doyle said. An increasing number of Irish businesses will adopt AI and scale it across their organisations.

Earlier this year, a State of IT report from Salesforce suggested that 91pc of Irish IT leaders believe generative AI will have a prominent role in their organisations in the near future. However, there also appeared to be feelings of caution, as 53pc of leaders said they were concerned about the ethics of generative AI.

Doyle said a recent report from Dell also suggests many Irish businesses are looking to integrate generative AI.

According to our latest GenAI Pulse survey, nearly half of IT leaders expect to see meaningful results from [generative] AI initiatives within six months to a year, Doyle said. One of the first steps that leaders can take to ensure successful AI adoption in the year ahead is to organise and structure data within their business.

Quantum computing has had some interesting developments this year, with some leaders claiming that the sector is moving at breakneck speed as interest grows among customers, investors and governments.

Doyle said that the growing demand for data will present an opportunity in the near future for quantum computing and generative AI to become closely linked.

With the global explosion of data and AI, there will be an increasing need for organisations in Ireland to put in place the computing power to manage it effectively, Doyle said. Quantum computing will begin to address this and bring about a massive leap in the computing power that is required to unlock AI innovation.

If we were surprised by the [generative] AI advancements of the last year, leaders should expect to see a bigger jump forward when quantum computing becomes intertwined in the near future.

Doyle also predicts that the promise of powerful digital assistants will become a reality next year, as PCs and AI technology become more powerful.

Over the next 12 months the PC experience will shift from searching to prompting, from reading to understanding and from editing to directing, Doyle said. This will result in the emergence of a two-way human-machine partnership in workplaces across Ireland.

Also, as AI becomes a key part of laptops and devices, it will unlock improved privacy and security while also advancing sustainable design.

Zero trust is a modern cybersecurity strategy that is easy to understand based on the term following a belief to never trust and always verify. Doyle believes 2024 will see zero-trust cybersecurity evolve from a concept to a real technology.

Adopting a zero-trust approach helps organisations build a more resilient and responsive security infrastructure while ultimately lessening the impact of cyberattacks, Doyle said. As the benefits of zero-trust technology becomes evident, it is expected that zero trust will become the norm in a wider range of industries in Ireland.

Some experts argue that technology is one of the key ways companies and the wider community can achieve their sustainability goals. Luis Neves, the CEO of Global Enabling Sustainability Initiative, recently told SiliconRepublic.com that digital technologies will play a vital role in tackling the climate crisis and broader sustainability issues.

Doyle predicts that the role played by technology in advancing sustainability will grow in 2024.

With larger companies being required by the EU to disclose their environmental, social and governance (ESG) performance and activity, business and IT leaders in Ireland will increasingly rely on technology to track their climate data and reduce emissions, Doyle said.

Our latest Digital Pulse Survey revealed that almost half of companies are looking at upgrading technology in the coming year to cut rising energy costs and drive sustainable innovation.

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Dell expects quantum computing and generative AI to link in 2024 - SiliconRepublic.com