In a major stride toward building a shared national research infrastructure, the U.S. National Science Foundation has launched the National Artificial Intelligence Research Resource pilot program with significant support from NVIDIA. The initiative aims to broaden access to the tools needed to power responsible AI discovery and innovation. It was announced Wednesday in partnership with 10 other federal agencies as well as private-sector, nonprofit and philanthropic organizations. "The breadth of partners that have come together for this pilot underscores the urgency of developing a National AI Research Resource for the future of AI in America," said NSF Director Sethuraman Panchanathan. "By investing in AI research through the NAIRR pilot, the United States unleashes discovery and impact and bolsters its global competitiveness."

NVIDIA's commitment of $30 million in technology contributions over two years is a key factor in enlarging the scale of the pilot, fueling the potential for broader achievements and accelerating the momentum toward full-scale implementation. "The NAIRR is a vision of a national research infrastructure that will provide access to computing, data, models and software to empower researchers and communities," said Katie Antypas, director of the Office of Advanced Cyberinfrastructure at the NSF. "Our primary goals for the NAIRR pilot are to support fundamental AI research and domain-specific research applying AI, reach broader communities, particularly those currently unable to participate in the AI innovation ecosystem, and refine the design for the future full NAIRR," Antypas added.

Researchers from Tsinghua University in Beijing have developed FlexRAM, the first fully flexible resistive RAM memory built using liquid metal. The innovative approach suspends droplets of gallium-based liquid metal in a soft biopolymer material. Applying voltage pulses oxidizes or reduces the metal, mimicking neuron polarization. This allows the reversible switching between high and low resistance states corresponding to bit 1s and 0s for data storage. Even when powered off, data persists in the inert liquid for 43,200 seconds (or 12 hours). The current FlexRAM prototype consists of 8 independent 1-bit memory units, storing a total of 1 byte. It has demonstrated over 3,500 write cycles, though further endurance improvements are needed for practical use. Commercial RAM is rated for millions of read/write cycles. The millimeter-scale metal droplets could eventually reach nanometer sizes, dramatically increasing memory density.

FlexRAM represents a breakthrough in circuits and electronics that can freely bend and flex. The researchers envision applications from soft robotics, medical implants, and flexible wearable devices. Compatibility with stretchable substrates unlocks enormous potential for emerging technologies. While still in the early conceptual stages, FlexRAM proves that computing and memory innovations that were once thought impossible or fanciful can become real through relentless scientific creativity. It joins a wave of pioneering flexible electronics research attaining more flexibility than rigid silicon allows. There are still challenges to solve before FlexRAM and liquid electronics can transform computing. But by proving a fluid-state memory device possible, the technology flows toward a radically different future for electronics and computation. Below, you can see the liquid metal droplet that is the FlexRAM breakthrough.

Quantum coherence at room temperature has been achieved, thanks to the efforts of Associate Professor Nobuhiro Yanai and his research team at Kyushu University's Faculty of Engineering. Additional credit goes to Associate Professor Kiyoshi Miyata (also of Kyushu University) and Professor Yasuhiro Kobori of Kobe University, all in Japan. Their scientific experiments have led to an ideal set of conditions where it is "crucial to generate quantum spin coherence in the quintet sublevels by microwave manipulation at room temperature." A quantum system requires operation in a stable state over a certain period of time, free of environmental interference.

Kobori-san has disclosed multi-department research results in a very elaborate document: "This is the first room-temperature quantum coherence of entangled quintets." The certain period of time mentioned above was only measures in nanoseconds, so more experimental work and further refinement will be carried out to prolong harmonious conditions. Head honco, Professor Yanai outlined some goals: "It will be possible to generate quintet multiexciton state qubits more efficiently in the future by searching for guest molecules that can induce more such suppressed motions and by developing suitable MOF structures...This can open doors to room-temperature molecular quantum computing based on multiple quantum gate control and quantum sensing of various target compounds."

According to the report from a journal called Fundamental Research, researchers from the Institute of Computing Technology at the Chinese Academy of Sciences have developed a 256-core multi-chiplet processor called Zhejiang Big Chip, with plans to scale up to 1,600 cores by utilizing an entire wafer. As transistor density gains slow, alternatives like multi-chiplet architectures become crucial for continued performance growth. The Zhejiang chip combines 16 chiplets, each holding 16 RISC-V cores, interconnected via network-on-chip. This design can theoretically expand to 100 chiplets and 1,600 cores on an advanced 2.5D packaging interposer. While multi-chiplet is common today, using the whole wafer for one system would match Cerebras' breakthrough approach. Built on 22 nm process technology, the researchers cite exascale supercomputing as an ideal application for massively parallel multi-chiplet architectures.

Careful software optimization is required to balance workloads across the system hierarchy. Integrating near-memory processing and 3D stacking could further optimize efficiency. The paper explores lithography and packaging limits, proposing hierarchical chiplet systems as a flexible path to future computing scale. While yield and cooling challenges need further work, the 256-core foundation demonstrates the potential of modular designs as an alternative to monolithic integration. China's focus mirrors multiple initiatives from American giants like AMD and Intel for data center CPUs. But national semiconductor ambitions add urgency to prove domestically designed solutions can rival foreign innovation. Although performance details are unclear, the rapid progress shows promise in mastering modular chip integration. Combined with improving domestic nodes like the 7 nm one from SMIC, China could easily create a viable Exascale system in-house.

Dell Technologies, Intel and the University of Cambridge announce the deployment of the co-designed Dawn Phase 1 supercomputer. Leading technical teams built the U.K.'s fastest AI supercomputer that harnesses the power of both artificial intelligence (AI) and high performance computing (HPC) to solve some of the world's most pressing challenges. This sets a clear way forward for future U.K. technology leadership and inward investment into the U.K. technology sector. Dawn kickstarts the recently launched U.K. AI Research Resource (AIRR), which will explore the viability of associated systems and architectures. Dawn brings the U.K. closer to reaching the compute threshold of a quintillion (1018) floating point operations per second - one exaflop, better known as exascale. For perspective: Every person on earth would have to make calculations 24 hours a day for more than four years to equal a second's worth of processing power in an exascale system.

"Dawn considerably strengthens the scientific and AI compute capability available in the U.K., and it's on the ground, operational today at the Cambridge Open Zettascale Lab. Dell PowerEdge XE9640 servers offer a no-compromises platform to host the Intel Data Center GPU Max Series accelerator, which opens up the ecosystem to choice through oneAPI. I'm very excited to see the sorts of early science this machine can deliver and continue to strengthen the Open Zettascale Lab partnership between Dell Technologies, Intel and the University of Cambridge, and further broaden that to the U.K. scientific and AI community," said Adam Roe, EMEA HPC technical director at Intel.

A research paper released this week describes ways generative AI can assist one of the most complex engineering efforts: designing semiconductors. The work demonstrates how companies in highly specialized fields can train large language models (LLMs) on their internal data to build assistants that increase productivity.

Few pursuits are as challenging as semiconductor design. Under a microscope, a state-of-the-art chip like an NVIDIA H100 Tensor Core GPU (above) looks like a well-planned metropolis, built with tens of billions of transistors, connected on streets 10,000x thinner than a human hair. Multiple engineering teams coordinate for as long as two years to construct one of these digital mega cities. Some groups define the chip's overall architecture, some craft and place a variety of ultra-small circuits, and others test their work. Each job requires specialized methods, software programs and computer languages.

A new forecast from International Data Corporation (IDC) shows that enterprises will invest nearly $16 billion worldwide on GenAI solutions in 2023. This spending, which includes GenAI software as well as related infrastructure hardware and IT/business services, is expected to reach $143 billion in 2027 with a compound annual growth rate (CAGR) of 73.3% over the 2023-2027 forecast period. This is more than twice the rate of growth in overall AI spending and almost 13 times greater than the CAGR for worldwide IT spending over the same period.

"Generative AI is more than a fleeting trend or mere hype. It is a transformative technology with far-reaching implications and business impact," says Ritu Jyoti, group vice president, Worldwide Artificial Intelligence and Automation market research and advisory services at IDC. "With ethical and responsible implementation, GenAI is poised to reshape industries, changing the way we work, play, and interact with the world."

Dell Technologies expands its Dell Generative AI Solutions portfolio, helping businesses transform how they work along every step of their generative AI (GenAI) journeys. "To maximize AI efforts and support workloads across public clouds, on-premises environments and at the edge, companies need a robust data foundation with the right infrastructure, software and services," said Jeff Boudreau, chief AI officer, Dell Technologies. "That's what we are building with our expanded validated designs, professional services, modern data lakehouse and the world's broadest GenAI solutions portfolio."

Customizing GenAI models to maximize proprietary data
The Dell Validated Design for Generative AI with NVIDIA for Model Customization offers pre-trained models that extract intelligence from data without building models from scratch. This solution provides best practices for customizing and fine-tuning GenAI models based on desired outcomes while helping keep information secure and on-premises. With a scalable blueprint for customization, organizations now have multiple ways to tailor GenAI models to accomplish specific tasks with their proprietary data. Its modular and flexible design supports a wide range of computational requirements and use cases, spanning training diffusion, transfer learning and prompt tuning.

Pierre Ferragu, the Global Technology Infrastructure chief at New Street Research, has predicted a very positive 2025 financial outcome for Taiwan Semiconductor Manufacturing Company Limited (TSMC). A global slowdown in consumer purchasing of personal computers and smartphones has affected a number of companies including the likes of NVIDIA and AMD—their financial reports have projected a 10% annual revenue drop for 2023. TSMC has similarly forecast that its full year revenue for 2023 will settle at $68.31 billion, after an approximate 10% fall. Ferragu did not contest these figures—via his team's analysis—TSMC is expected to pull in $68 billion in net sales for this financial year.

The rumor mill has TSMC revising its revenue guidance for a third time this year—but company leadership has denied that this will occur. New Street Research estimates that conditions will improve next year, with an uptick in client orders placed at TSMC's foundries. Ferragu reckons that TSMC could hit an all-time revenue high of $100 billion by 2025. His hunch is based on the upcoming spending habits of VIP foundry patrons encompassing: "a bottom-up perspective, looking at how TSMC's top customers, which we all know very well, will contribute to such growth." The Taiwanese foundry's order books are reported to be filling up for next year, with Apple and NVIDIA seizing the moment to stand firmly at the front of the 3 nm process queue.

The Platform for Digital and Quantum Innovation of Quebec (PINQ²), a non-profit organization (NPO) founded by the Ministry of Economy, Innovation and Energy of Quebec (MEIE - ministère de l'Économie, de l'Innovation et de l'Énergie du Québec) and the Université de Sherbrooke, along with IBM, are proud to announce the historic inauguration of an IBM Quantum System One at IBM Bromont. This event marks a major turning point in the field of information technology and all sectors of innovation in Quebec, making PINQ² the sole administrator to inaugurate and operate an IBM Quantum System One in Canada. To date, this is one of the most advanced quantum computers in IBM's global fleet of quantum computers.

This new quantum computer in Quebec reinforces Quebec's and Canada's position as a force in the rapidly advancing field of quantum computing, opening new prospects for the technological future of the province and the country. Access to this technology is a considerable asset not only for the ecosystem of DistriQ, the quantum innovation zone for Quebec, but also for the Technum Québec innovation zone, the new "Energy Transition Valley" innovation zone and other strategic sectors for Quebec.

Taiwan's Economic Daily reckons that a freshly formed partnership between TSMC, Broadcom, and NVIDIA will result in the development of cutting-edge silicon photonics. The likes of IBM, Intel and various academic institutes are already deep into their own research and development processes, but the alleged new alliance is said to focus on advancing AI computer hardware. The report cites a significant allocation of—roughly 200—TSMC staffers onto R&D involving the integration of silicon photonic technologies into high performance computing (HPC) solutions. They are very likely hoping that the usage of optical interconnects (on a silicon medium) will result in greater data transfer rates between and within microchips. Other benefits include longer transmission distances and a lower consumption of power.

TSMC vice president Yu Zhenhua has placed emphasis on innovation, in a similar fashion to his boss, within the development process (industry-wide): "If we can provide a good silicon photonics integrated system, we can solve the two key issues of energy efficiency and AI computing power. This will be a new one...Paradigm shift. We may be at the beginning of a new era." The firm is facing unprecedented demand from its clients—it hopes to further expand its advanced chip packaging capacity to address these issues by late 2024. A shift away from the limitations of "conventional electric" data transmissions could bring next generation AI compute GPUs onto the market by 2025.

According to a new research report from the analyst firm Jon Peddie Research (JPR), unit shipments in the add-in board (AIB) market increased in Q2'23 from last quarter, while AMD gained market share. Quarter to quarter, graphics AIB shipments increased modestly, by 2.9%; however, shipments decreased by -36% year to year.

Since Q1 2000, over 2.10 billion graphics cards, worth about $476 billion, have been sold. The market shares for the desktop discrete GPU suppliers shifted in the quarter, as AMD's market share increased from last quarter and Nvidia's share increased from last year. Intel, which entered the AIB market in Q3'22 with the Arc A770 and A750, will start to increase market share in 2024.

Jon Peddie Research reports the growth of the global PC-based graphics processor unit (GPU) market reached 61.6 million units in Q2'23 and PC CPU shipments decreased by -23% year over year. Overall, GPUs will have a compound annual growth rate of 3.70% during 2022-2026 and reach an installed base of 2,998 million units at the end of the forecast period. Over the next five years, the penetration of discrete GPUs (dGPUs) in the PC will grow to reach a level of 32%.

Year to year, total GPU shipments, which include all platforms and all types of GPUs, decreased by -27%, desktop graphics decreased by -36%, and notebooks decreased by -23%.

Jon Peddie Research reports the growth of the global PC client-based CPU units market reached 53.6 million units in Q2'23, up 17%, and iGPU shipments increased by 14% to 49 million units. Year over year, iGPUs declined -29%.

Integrated GPUs will have a compound annual growth rate of 2.5% during 2022-2026 and reach an installed base of 4.8 billion units at the end of the forecast period. Over the next five years, the penetration of iGPUs in the PC will grow to reach a level of 98%.

PCI-SIG today announced the formation of a new workgroup to deliver PCI Express (PCIe) technology over optical connections. The PCI-SIG Optical Workgroup intends to be optical technology-agnostic, supporting a wide range of optical technologies, while potentially developing technology-specific form factors.

"Optical connections will be an important advancement for PCIe architecture as they will allow for higher performance, lower power consumption, extended reach and reduced latency," said Nathan Brookwood, Research Fellow at Insight 64. "Many data-demanding markets and applications such as Cloud and Quantum Computing, Hyperscale Data Centers and High-Performance Computing will benefit from PCIe architecture leveraging optical connections."

TSMC today held an inauguration ceremony for its global Research and Development Center in Hsinchu, Taiwan, celebrating the Company's newest hub for bringing the next generations of semiconductor technology into reality with customers, R&D partners in industry and academia, design ecosystem partners, and senior government leaders.

The R&D Center will serve as the new home for TSMC's R&D Organization, including the researchers who will develop TSMC's leading-edge process technology at the 2-nanometer generation and beyond, as well as scientists and scholars blazing the trail with exploratory research into fields such as novel materials and transistor structures. With R&D employees already relocating to their workplaces in the new building, it will be ready for its full complement of more than 7,000 staff by September 2023.

IBM has launched a new tool to help enterprises track greenhouse gas (GHG) emissions across cloud services and advance their sustainability performance throughout their hybrid, multicloud journeys. Now generally available, the IBM Cloud Carbon Calculator - an AI-informed dashboard - can help clients access emissions data across a variety of IBM Cloud workloads such as AI, high performance computing (HPC) and financial services.

Across industries, enterprises are embracing modernization by leveraging hybrid cloud and AI to digitally transform with resiliency, performance, security, and compliance at the forefront, all while remaining focused on delivering value and driving more sustainable business practices. According to a recent study by IBM, 42% of CEOs surveyed pinpoint environmental sustainability as their top challenge over the next three years. At the same time, the study reports that CEOs are facing pressure to adopt generative AI while also weighing the data management needs to make AI successful. The increase in data processing required for AI workloads can present new challenges for organizations that are looking to reduce their GHG emissions. With more than 43% of CEOs surveyed already using generative AI to inform strategic decisions, organizations should prepare to balance executing high performance workloads with sustainability.

When PlayStation VR2 released earlier this year, it offered players a chance to experience virtual game worlds bristling with detail and immersive features. PS VR2 was the culmination of several years of development, which included multiple prototypes and testing approaches. To learn more, we asked PS VR2's Product Manager Yasuo Takahashi about the development process of the innovative headset and PlayStation VR2 Sense Controller, and also gained insight into the various prototypes that were created as part of this process.

PlayStation Blog: When did development for the PS VR2 headset start?
Yasuo Takahashi: Research on future VR technology was being conducted even prior to the launch of the original PlayStation VR as part of our R&D efforts. After PS VR's launch in 2016, discussion around what the next generation of VR would look like began in earnest. We went back and reviewed those R&D findings and we started prototyping various technologies at the beginning of 2017. Early that same year, we began detailed conversations on what features should be implemented in the new product, and which specific technologies we should explore further.

A watershed moment on Nov. 22, 2022, was mostly virtual, yet it shook the foundations of nearly every industry on the planet. On that day, OpenAI released ChatGPT, the most advanced artificial intelligence chatbot ever developed. This set off demand for generative AI applications that help businesses become more efficient, from providing consumers with answers to their questions to accelerating the work of researchers as they seek scientific breakthroughs, and much, much more.

Businesses that previously dabbled in AI are now rushing to adopt and deploy the latest applications. Generative AI—the ability of algorithms to create new text, images, sounds, animations, 3D models and even computer code—is moving at warp speed, transforming the way people work and play. By employing large language models (LLMs) to handle queries, the technology can dramatically reduce the time people devote to manual tasks like searching for and compiling information.

Hello everyone! Today I'm happy to announce that we're putting the next update for Age of Wonders 4 into Open Beta! This previews some of the improvements that are part of the Watcher update, due later this summer. This coming update focuses on what we feel are the issues which are most important to you, and we'd love to get your feedback on what we've managed to do so far.

It's important to remember that this is a work in progress patch. This means that it may be unstable or imbalanced, and that the features we've added may not work entirely as we want them to. It also means that we may revert certain changes later if we feel that they aren't achieving what we want them to or if we're inspired to replace them with something better! Instructions, Patch Notes and F.A.Q. are provided below...

NVIDIA RTX is spinning new cycles for designs. Trek Bicycle is using GPUs to bring design concepts to life. The Wisconsin-based company, one of the largest bicycle manufacturers in the world, aims to create bikes with the highest-quality craftsmanship. With its new partner Lidl, an international retailer chain, Trek Bicycle also owns a cycling team, now called Lidl-Trek. The team is competing in the annual Tour de France stage race on Trek Bicycle's flagship lineup, which includes the Emonda, Madone and Speed Concept. Many of the team's accessories and equipment, such as the wheels and road race helmets, were also designed at Trek.

Bicycle design involves complex physics—and a key challenge is balancing aerodynamic efficiency with comfort and ride quality. To address this, the team at Trek is using NVIDIA A100 Tensor Core GPUs to run high-fidelity computational fluid dynamics (CFD) simulations, setting new benchmarks for aerodynamics in a bicycle that's also comfortable to ride and handles smoothly. The designers and engineers are further enhancing their workflows using NVIDIA RTX technology in Dell Precision workstations, including the NVIDIA RTX A5500 GPU, as well as a Dell Precision 7920 running dual RTX A6000 GPUs.

AI and accelerated computing will help climate researchers achieve the miracles they need to achieve breakthroughs in climate research, NVIDIA founder and CEO Jensen Huang said during a keynote Monday at the Berlin Summit for the Earth Virtualization Engines initiative. "Richard Feynman once said that "what I can't create, I don't understand" and that's the reason why climate modeling is so important," Huang told 180 attendees at the Harnack House in Berlin, a storied gathering place for the region's scientific and research community. "And so the work that you do is vitally important to policymakers to researchers to the industry," he added.

To advance this work, the Berlin Summit brings together participants from around the globe to harness AI and high-performance computing for climate prediction. In his talk, Huang outlined three miracles that will have to happen for climate researchers to achieve their goals, and touched on NVIDIA's own efforts to collaborate with climate researchers and policymakers with its Earth-2 efforts. The first miracle required will be to simulate the climate fast enough, and with a high enough resolution - on the order of just a couple of square kilometers.

A group of researchers in China have used a new approach to AI to create a full RISC-V processor from scratch. The team set out to answer the question of whether an AI could design an entire processor on its own without human intervention. While AI design tools do already exist and are used for complex circuit design and validation today, they are generally limited in use and scope. The key improvements shown in this approach over traditional or AI assisted logic design are the automated capabilities, as well as its speed. The traditional assistive tools for designing circuits still require many hours of manual programming and validation to design a functional circuit. Even for such a simple processor as the one created by the AI, the team claims the design would have taken 1000x as long to be done by humans. The AI was trained by observing specific inputs and outputs of existing CPU designs, with the paper summarizing the approach as such:

(...) a new AI approach, which generates large-scale Boolean function with almost 100% validation accuracy (e.g., > 99.99999999999% as Intel) from only external input-output examples rather than formal programs written by the human. This approach generates the Boolean function represented by a graph structure called Binary Speculation Diagram (BSD), with a theoretical accuracy lower bound by using the Monte Carlo based expansion, and the distance of Boolean functions is used to tackle the intractability.

Today, it was announced that Rensselaer Polytechnic Institute will become the first university in the world to house an IBM Quantum System One. The IBM quantum computer, intended to be operational by January of 2024, will serve as the foundation of a new IBM Quantum Computational Center in partnership with Rensselaer Polytechnic Institute (RPI). By partnering, RPI's vision is to greatly enhance the educational experiences and research capabilities of students and researchers at RPI and other institutions, propel the Capital Region into a top location for talent, and accelerate New York's growth as a technology epicenter.

RPI's advance into research of applications for quantum computing will represent a more than $150 million investment once fully realized, aided by philanthropic support from Curtis R. Priem '82, vice chair of RPI's Board of Trustees. The new quantum computer will be part of RPI's new Curtis Priem Quantum Constellation, a faculty endowed center for collaborative research, which will prioritize the hiring of additional faculty leaders who will leverage the quantum computing system.

A new global study by the IBM Institute for Business Value found that nearly half of CEOs surveyed identify productivity as their highest business priority—up from sixth place in 2022. They recognize technology modernization is key to achieving their productivity goals, ranking it as second highest priority. Yet, CEOs can face key barriers as they race to modernize and adopt new technologies like generative AI.

The annual CEO study, CEO decision-making in the age of AI, Act with intention, found three-quarters of CEO respondents believe that competitive advantage will depend on who has the most advanced generative AI. However, executives are also weighing potential risks or barriers of the technology such as bias, ethics and security. More than half (57%) of CEOs surveyed are concerned about data security and 48% worry about bias or data accuracy.