Quantum Machines (QM), a leading provider of advanced quantum control solutions, today announced its intention to work with NVIDIA at its newly established NVIDIA Accelerated Quantum Research Center (NVAQC), unveiled at the GTC global AI conference. The Boston-based center aims to advance quantum computing research with accelerated computing, including integrating quantum processors with AI- supercomputing to overcome significant challenges in the quantum computing space. As quantum computing rapidly evolves, the integration of quantum processors with powerful AI supercomputers becomes increasingly essential. These accelerated quantum supercomputers are pivotal for advancing quantum error correction, device control, and algorithm development.

Quantum Machines joins other quantum computing pioneers, including Quantinuum and QuEra, along with academic partners from Harvard and MIT, in working with NVIDIA at the NVAQC to develop pioneering research. Quantum Machines will work with NVIDIA to integrate its NVIDIA GB200 Grace Blackwell Superchips with QM's advanced quantum control technologies, including the OPX1000. This integration will facilitate rapid, high-bandwidth communication between quantum processors and classical supercomputers. QM and NVIDIA thereby lay the essential foundations for quantum error correction and robust quantum algorithm execution. By reducing latency and enhancing processing efficiency, QM and NVIDIA solutions will significantly accelerate practical applications of quantum computing.

Qualcomm today announced the acquisition of MovianAI Artificial Intelligence (AI) Application and Research JSC (MovianAI), the former generative AI division of VinAI Application and Research JSC (VinAI) and a part of the Vingroup ecosystem. As a leading AI research company, VinAI is renowned for its expertise in generative AI, machine learning, computer vision, and natural language processing. Combining VinAI's advanced generative AI research and development (R&D) capabilities with Qualcomm's decades of extensive R&D will expand its ability to drive extraordinary inventions.

For more than 20 years, Qualcomm has been working closely with the Vietnamese technology ecosystem to create and deliver innovative solutions. Qualcomm's innovations in the areas of 5G, AI, IoT and automotive have helped to fuel the extraordinary growth and success of Vietnam's information and communication technology (ICT) industry and assisted the entry of Vietnamese companies into the global marketplace.

Quantum Machines (QM), the leading provider of advanced quantum control solutions, has recently announced the NVIDIA DGX Quantum Early Customer Program, with a cohort of six leading research groups and quantum computer builders. NVIDIA DGX Quantum, a reference architecture jointly developed by NVIDIA and QM, is the first tightly integrated quantum-classical computing solution, designed to unlock new frontiers in quantum computing research and development. As quantum computers scale, their reliance on classical resources for essential operations, such as quantum error correction (QEC) and parameter drift compensation, grows exponentially. NVIDIA DGX Quantum provides access to the classical acceleration needed to support this progress, advancing the path toward practical quantum supercomputers.

NVIDIA DGX Quantum leverages OPX1000, the best-in-class, modular high-density hybrid control platform, seamlessly interfacing with NVIDIA GH200 Grace Hopper Superchips. This solution brings accelerated computing into the heart of the quantum computing stack for the first time, achieving an ultra-low round-trip latency of less than 4 µs between quantum control and AI supercomputers - faster than any other approach. The NVIDIA DGX Quantum Early Customer Program is now underway, with selected leading academic institutions, national labs, and commercial quantum computer builders participating. These include the Engineering Quantum Systems group (equs.mit.edu) led by MIT Professor William D. Oliver, the Israeli Quantum Computing Center (IQCC), quantum hardware developer Diraq, the Quantum Circuit group (led by Ecole Normale Supérieure de Lyon Professor Benjamin Huard), and more.

A recent study by TechInsights is reshaping the narrative around the cost of semiconductor manufacturing in the United States. According to the survey, processing a 300 mm wafer at TSMC's Fab 21 in Phoenix, Arizona, is only about 10% more expensive than similar operations in Taiwan. This insight challenges earlier assumptions based on TSMC founder Morris Chang's comments, which suggested that high fab-building expenses in Arizona made US chip production financially impractical. G. Dan Hutcheson of TechInsights highlighted that the observed cost difference largely reflects the expenses associated with establishing a brand-new facility. "It costs TSMC less than 10% more to process a 300 mm wafer in Arizona than the same wafer made in Taiwan," he explained. The initial higher costs stem from constructing a fab in an unfamiliar market with a new, sometimes unskilled workforce—a scenario not typical for mature manufacturing sites.

A significant portion of the wafer production cost is driven by equipment, which accounts for well over two-thirds of the total expenses. Leading equipment providers like ASML, Applied Materials, and Lam Research charge similar prices globally, effectively neutralizing geographic disparities. Although US labor costs are higher than in Taiwan, the heavy automation in modern fabs means that labor represents less than 2% of the overall cost. Additional logistics for Fab 21, including the return of wafers to Taiwan for dicing, testing, and packaging, add complexity but only minimally affect the overall expense. With plans to expand domestic packaging capabilities, TSMC's approach is proving to be strategically sound. This fresh perspective suggests that the apparent high cost of US fab construction has been exaggerated. TSMC's $100B investment in American semiconductor manufacturing reflects a calculated decision informed by detailed cost analysis—demonstrating that location-based differences become less significant when the equipment dominates expenses.

We're stepping up our multiplatform gaming offering with exciting news dropping at this year's Game Developers Conference (GDC). We're bringing users more games, more ways to play your games across devices, and improved gameplay. You can read all about the updates for users from The Keyword. At GDC, we'll be diving into all of the latest games coming to Play, plus new developer tools that'll help improve gameplay across the Android ecosystem.

We're sharing a closer look at what's new from Android. We're making Vulkan the official graphics API on Android, enabling you to build immersive visuals, and we're enhancing the Android Dynamic Performance Framework (ADPF) to help you deliver longer, more stable gameplays. Check out our video, or keep reading below.

NVIDIA today announced it is building a Boston-based research center to provide cutting-edge technologies to advance quantum computing. The NVIDIA Accelerated Quantum Research Center, or NVAQC, will integrate leading quantum hardware with AI supercomputers, enabling what is known as accelerated quantum supercomputing. The NVAQC will help solve quantum computing's most challenging problems, ranging from qubit noise to transforming experimental quantum processors into practical devices.

Leading quantum computing innovators, including Quantinuum, Quantum Machines and QuEra Computing, will tap into the NVAQC to drive advancements through collaborations with researchers from leading universities, such as the Harvard Quantum Initiative in Science and Engineering (HQI) and the Engineering Quantum Systems (EQuS) group at the Massachusetts Institute of Technology (MIT).

Large language models (LLMs) love large quantities of memory—so much so, in fact, that AI enthusiasts are turning to multi-GPU setups to make even more VRAM available for their AI apps. But since many current LLMs are extremely large, even this approach has its limits. At times, the GPU will decide to make use of CPU processing power for this data, and when it does, the performance of your CPU cache and DRAM comes into play. All this means that when it comes to the performance of AI applications, it's not just the GPU that matters, but the entire pathway that connects the GPU to the CPU to the I/O die to the DRAM modules. It stands to reason, then, that there are opportunities to boost AI performance by optimizing these elements.

That's exactly what we've found as we've spent time in our R&D labs with the latest AMD Ryzen CPUs. AMD just launched two new Ryzen CPUs with AMD 3D V-Cache Technology, the AMD Ryzen 9 9950X3D and Ryzen 9 9900X3D, pushing the series into new performance territory. After testing a wide range of optimizations in a variety of workloads, we uncovered a range of settings that offer tangible benefits for AI enthusiasts. Now, we're ready to share these optimizations with you through a new BIOS feature: AI Cache Boost. Available through an ASUS AMD 800 Series motherboard and our most recent firmware update, AI Cache Boost can accelerate performance up to 12.75% when you're working with massive LLMs.

Microsoft launched its Majorana 1 chip—the world's first quantum processor powered by a Topological Core architecture—last month. The company's debuting of its Majorana design was celebrated as a significant milestone—in 2023, an ambitious roadmap was published by Microsoft's research department. At the time, a tall Majorana particle-based task was set: the building of a proprietary quantum supercomputer within a decade. Returning to the present day; outside parties have criticized Microsoft's February announcements. The Register published an investigative piece earlier today, based on quotes from key players specializing in the field of Quantum studies. Many propose a theoretical existence of Majorana particles, while Microsoft R&D employees have claimed detection and utilization. The Register referred back to recent history: "(Microsoft) made big claims about Majorana particles before, but it didn't end well: in 2021 Redmond's researchers retracted a 2018 paper in which they claimed to have detected the particles."

As pointed out by Microsoft researcher Chetan Nayak; their latest paper was actually authored last March 2024, but only made public in recent weeks. Further details of progress are expected next week, at the American Physical Society (APS) 2025 Joint March Meeting. The Register has compiled quotes from vocal critics; starting with Henry Legg—a lecturer in theoretical physics at the University of St Andrews, Scotland. The noted scholar believes—as divulged in a scientific online comment—that Microsoft's claimed Quantum breakthrough: "is not reliable and must be revisited." Similarly, collaborators from Germany's Forschungszentrum Jülich institute and the University of Pittsburgh, USA released a joint video statement. (Respectively) Experimental physicist Vincent Mourik and by Professor Sergey Frolov outlined: "distractions caused by unreliable scientific claims from Microsoft Quantum."

ASML Holding N.V. (ASML) and imec, a leading research and innovation hub in nanoelectronics and digital technologies, today announce that they have signed a new strategic partnership agreement, focusing on research and sustainability. The agreement has a duration of five years and aims to deliver valuable solutions in two areas by bringing together ASML's and imec's respective knowledge and expertise. First, to develop solutions that advance the semiconductor industry and second, to develop initiatives focused on sustainable innovation.

The collaboration incorporates ASML's whole product portfolio, with a focus on developing high-end nodes, using ASML systems including 0.55 NA EUV, 0.33 NA EUV, DUV immersion, YieldStar optical metrology and HMI single- and multi-beam technologies. These tools will be installed in imec's state-of-the-art pilot line and incorporated in the EU- and Flemish-funded NanoIC pilot line, providing the most advanced infrastructure for sub-2 nm R&D to the international semiconductor ecosystem. Focus areas for R&D will also include silicon photonics, memory and advanced packaging, offering full stack innovation for future semiconductor-based AI applications in diverse markets.

Hello Director! We're happy to announce that all owners of will be receiving a free content update. The update is hitting PC players (Steam and Epic Games Store, GOG to follow later) today, including several improvements to support newer hardware. In the near future we will release this same update for PlayStation 5 and Xbox Series X|S platforms. We have a small team working on these updates so we want to space them out to give us time to fix potential issues that might come up. We appreciate your patience! Keep an eye on our social channels for the exact date and time, as well as update notes.

Control Ultimate Edition contains the main game and all previously released Expansions ("The Foundation" and "AWE") in one great value package. A corruptive presence has invaded the Federal Bureau of Control…Only you have the power to stop it. The world is now your weapon in an epic fight to annihilate an ominous enemy through deep and unpredictable environments. Containment has failed, humanity is at stake. Will you regain control?

When the US imposed sanctions on Chinese semiconductor makers, China began the push for sovereign chipmaking tools. According to a study conducted by the Emerging Technology Observatory (ETO), Chinese institutions have dramatically outpaced their US counterparts in next-generation chipmaking research. Between 2018 and 2023, nearly 475,000 scholarly articles on chip design and fabrication were published worldwide. Chinese research groups contributed 34% of the output—compared to just 15% from the United States and 18% from Europe. The study further emphasizes the quality of China's contributions. Focusing on the top 10% of the most-cited articles, Chinese researchers were responsible for 50% of this high-impact work, while American and European research accounted for only 22% and 17%, respectively.

This trend shows China's lead isn't about numbers only, and suggests that its work is resonating strongly within the global academic community. Key research areas include neuromorphic, optoelectric computing, and, of course, lithography tools. China is operating mainly outside the scope of US export restrictions that have, since 2022, shrunk access to advanced chipmaking equipment—precisely, tools necessary for fabricating chips below the 14 nm process node. Although US sanctions were intended to limit China's access to cutting-edge manufacturing technology, the massive body of Chinese research suggests that these measures might eventually prove less effective, with Chinese institutions continuing to push forward with influential, high-citation studies. However, Chinese theoretical work is yet to be proven in the field, as only a single company currently manufactures 7 nm and 5 nm nodes—SMIC. Chinese semiconductor makers still need more advanced lithography solutions to reach high-volume manufacturing on more advanced nodes like 3 nm and 2 nm to create more powerful domestic chips for AI and HPC.

GlobalFoundries (GF) and the Massachusetts Institute of Technology (MIT) today announced a new master research agreement to jointly pursue advancements and innovations for enhancing the performance and efficiency of critical semiconductor technologies. The collaboration will be led by MIT's Microsystems Technology Laboratories (MTL) and GF's research and development team, GF Labs.

With an initial research focus on AI and other applications, the first projects are expected to leverage GF's differentiated silicon photonics technology, which monolithically integrates RF SOI, CMOS and optical features on a single chip to realize power efficiencies for datacenters, and GF's 22FDX platform, which delivers ultra-low power consumption for intelligent devices at the edge.

IBM today debuted the next generation of its Granite large language model (LLM) family, Granite 3.2, in a continued effort to deliver small, efficient, practical enterprise AI for real-world impact. All Granite 3.2 models are available under the permissive Apache 2.0 license on Hugging Face. Select models are available today on IBM watsonx.ai, Ollama, Replicate, and LM Studio, and expected soon in RHEL AI 1.5 - bringing advanced capabilities to businesses and the open-source community.

In nearly every corner of our lives, the buzz about AI is impossible to ignore. It's destined to revolutionize how we work, learn, and play. For those of us immersed in the world of gaming—whether as players or creators—the question isn't just how AI will change the game, but how it will ignite new possibilities.

At Xbox, we're all about using AI to make things better (and more fun!) for players and game creators. We want to bring more games to more people around the world and always stay true to the creative vision and artistry of game developers. We believe generative AI can boost this creativity and open up new possibilities. We're excited to announce a generative AI breakthrough, published today in the journal Nature and announced by Microsoft Research, that shows this potential to open up new possibilities—including the opportunity to make older games accessible to future generations of players across new devices and in new ways.

Shrinking components was (and still is) the main way to boost the speed of all electronic devices; however, as devices get tinier, making them becomes trickier. A group of scientists from SANKEN (The Institute of Scientific and Industrial Research), at Osaka University has discovered another method to enhance performance: putting a special metal layer known as a metamaterial on top of a silicon base to make electrons move faster. This approach shows promise, but the tricky part is managing the metamaterial's structure so it can adapt to real-world needs.

To address this, the team looked into vanadium dioxide (VO₂). When heated, VO₂ changes from non-conductive to metallic, allowing it to carry electric charge like small adjustable electrodes. The researchers used this effect to create 'living' microelectrodes, which made silicon photodetectors better at spotting terahertz light. "We made a terahertz photodetector with VO₂ as a metamaterial. Using a precise method, we created a high-quality VO₂ layer on silicon. By controlling the temperature, we adjusted the size of the metallic regions—much larger than previously possible—which affected how the silicon detected terahertz light," says lead author Ai I. Osaka.

Scientists have made a big step forward in data storage technology, they've managed to improve the manufacturing process for 3D NAND flash memory. This type of storage technology stacks memory cells on top of each other to obtain higher data density. A team of experts from Lam Research, the University of Colorado Boulder, and Princeton Plasma Physics Lab came up with a better way to etch (the process of carving holes into alternating layers of silicon oxide and silicon nitride) by using hydrogen fluoride plasma. This new method cuts vertical channels through silicon-based materials twice as fast as before achieving 640 nanometers in just one minute.

The team found out that mixing in certain chemicals like phosphorus trifluoride helps the etching process. They also learned that some byproducts can slow down etching, but adding water can help fix this problem. "The salt can decompose at a lower temperature when water is present, which can accelerate etching", said Yuri Barsukov, a former PPPL researcher now working at Lam Research. This breakthrough is important as the need for data storage received a huge boost with the rise of AI programs, that need tons of storage.

Google Security Research team has just published its latest research on a fundamental flaw in the microcode patch verification system that affects AMD processors from "Zen 1" through "Zen 4" generations. The vulnerability stems from an inadequate hash function implementation in the CPU's signature validation process for microcode updates, enabling attackers with local administrator privileges (ring 0 from outside a VM) to inject malicious microcode patches, potentially compromising AMD SEV-SNP-protected confidential computing workloads and Dynamic Root of Trust Measurement systems. Google disclosed this high-severity issue to AMD on September 25, 2024, leading to AMD's release of an embargoed fix to customers on December 17, 2024, with public disclosure following on February 3, 2025; however, due to the complexity of supply chain dependencies and remediation requirements, comprehensive technical details are being withheld until March 5, 2025, allowing organizations time to implement necessary security measures and re-establish trust in their confidential compute environments.

AMD has released comprehensive mitigation measures through AGESA firmware updates across its entire EPYC server processor lineup, from the first-generation Naples to the latest Genoa-X and Bergamo architectures. The security patch, designated as CVE-2024-56161 with a high severity rating of 7.2, introduces critical microcode updates: Naples B2 processors require uCode version 0x08001278, Rome B0 systems need 0x0830107D, while Milan and Milan-X variants mandate versions 0x0A0011DB and 0x0A001244 respectively. For the latest Genoa-based systems, including Genoa-X and Bergamo/Siena variants, the required microcode versions are 0x0A101154, 0x0A10124F, and 0x0AA00219. These updates implement robust protections across all SEV security features - including SEV, SEV-ES, and SEV-SNP - while introducing new restrictions on microcode hot-loading capabilities to prevent future exploitation attempts.

Today, OpenAI has announced a new ChatGPT feature called "Deep Research," which is capable of performing complex, multi-step research processes entirely on its own. Using so-called agents, which are autonomous bots working on top of the AI model, this feature searches the web and curates all needed information. This agentic behavior was trained on real-world browser usage, accompanied by Python code execution. Deep search, like OpenAI's o1 and o3 models, uses reinforcement learning, which steps back to "think" and creates a chain of thought before delivering users an answer to their question. Depending on the topic, deep research can take 5 to 30 minutes to search the web, crawl through data, and compile it in a reader-friendly manner.

Regarding benchmarks of its performance, OpenAI put out a lot of interesting comparisons and evaluations. Compared to all previous models, deep research gives these models additional context to help AI with more information. Thus, in evaluation benchmarks like Humanity's Last exam, deep research scored 26.6%, whereas o1 and o3-mini scored 9.1 and 13%, respectively. Other evaluations showed a modest improvement, while concrete comparisons were made in UX, business, and medical research. Turning the deep research feature on delivered more information every time, and you can see it for yourself here.

New technology from Chalmers University of Technology and the University of Gothenburg, Sweden, is helping the EU establish its own competitive computer manufacturing industry. Researchers have developed components critical for optimising on-chip memory, a key factor in enhancing the performance of next-generation computers.

The research leader, Professor Per Stenström, along with colleagues, has discovered new ways to make cache memory work smarter. A cache is a local memory that temporarily stores frequently accessed data, improving a computer's speed and performance. "Our solution enables computers to retrieve data significantly faster than before, as the cache can manage far more processing elements (PEs) than most existing systems. This makes it possible to meet the demands of tomorrow's powerful computers," says Per Stenström, Professor at the Department of Computer Science and Engineering at Chalmers University of Technology and the University of Gothenburg.

Jon Peddie Research (JPR) reports that shipments of integrated and standalone GPUs exceeded 251 million units in 2024, marking a 6% year-over-year rise. This growth continues to outpace the shipment figures for client CPUs, given that most desktop and laptop processors include built-in graphics, and that leading suppliers such as AMD and NVIDIA also provide tens of millions of discrete GPUs annually. Thanks to some earlier per-quarter data, we find that in the desktop segment, JPR shows that manufacturers shipped about 18.2 million discrete graphics cards in the first half of 2024—a 46% increase compared to the same period in 2023. However, shipments slowed in the third quarter, falling to 8.1 million units, down from 8.9 million units in Q3 2023.

Analysts partly attribute this dip to inventory adjustments at AMD, along with the end of product cycles for Ada Lovelace and RDNA 3 GPUs. Typically, the fourth quarter sees a boost in discrete GPU purchases as gamers gear up for new software releases. Yet it is not entirely clear whether that trend held through late 2024. Early indications suggest that total graphics card shipments for the year lightly exceed the totals from 2023, thanks primarily to strong demand in the first half. We still need data from Q4 of 2024 to see the trend in its final months of the year, despite knowing that the year-over-year growth is 6%. Nonetheless, current levels appear unlikely to approach the elevated peaks observed in 2021 or 2022.

Lam Research Corporation today announced that its innovative dry photoresist (dry resist) technology has been qualified for direct-print 28 nm pitch back end of line (BEOL) logic at 2 nm and below by imec, a leading research and innovation hub in nanoelectronics and digital technologies. An advanced patterning technique introduced by Lam, dry resist enhances the resolution, productivity and yield of extreme ultraviolet (EUV) lithography, a pivotal technology used in the production of next-generation semiconductor devices.

"Lam's dry photoresist technology provides unparalleled low-defectivity, high-resolution patterning," said Vahid Vahedi, chief technology and sustainability officer at Lam Research. "We are excited to offer this technology to imec and its partners as a critical process in the design and manufacturing of leading-edge semiconductor devices."

NVIDIA announced today it is opening its first Vietnam research and development center, signaling its confidence in the country's bright artificial intelligence future. The company is collaborating with the Vietnamese government to establish its new Vietnam Research and Development Center focused on AI. NVIDIA will use the R&D center to focus on software development, capitalizing on the country's strong talent pool of STEM engineers, and to engage industry leaders, startups, government agencies, universities and students to accelerate the adoption of AI.

"We are delighted to open NVIDIA's R&D center to accelerate Vietnam's AI journey," said Jensen Huang, founder and CEO of NVIDIA. "With our expertise in AI development, we will partner with a vibrant ecosystem of researchers, startups and enterprise organizations to build incredible AI right here in Vietnam."

The Biden administration is set to announce new, targeted restrictions on China's semiconductor industry, focusing primarily on emerging chip manufacturing equipment companies rather than broad industry-wide limitations. According to Bloomberg, these new restrictions are supposed to take effect on Monday. The new rules will specifically target two manufacturing facilities owned by Semiconductor Manufacturing International Corp. (SMIC) and will add select companies to the US Entity List, restricting their access to American technology. However, most of Huawei's suppliers can continue their operations, suggesting a more mild strategy. The restrictions will focus on over 100 emerging Chinese semiconductor equipment manufacturers, many of which receive government funding. These companies are developing tools intended to replace those currently supplied by industry leaders such as ASML, Applied Materials, and Tokyo Electron.

The moderated approach comes after significant lobbying efforts from American semiconductor companies, who argued that stricter restrictions could disadvantage them against international competitors. Major firms like Applied Materials, KLA, and Lam Research voiced concerns about losing market share to companies in Japan and the Netherlands, where similar but less stringent export controls are in place. Notably, Japanese companies like SUMCO are already seeing the revenue impacts of Chinese independence. Lastly, the restrictions will have a limited effect on China's memory chip sector. The new measures will not directly affect ChangXin Memory Technologies (CXMT), a significant Chinese DRAM manufacturer capable of producing high-bandwidth memory for AI applications.

Today at its inaugural IBM Quantum Developer Conference, IBM announced quantum hardware and software advancements to execute complex algorithms on IBM quantum computers with record levels of scale, speed, and accuracy.

IBM Quantum Heron, the company's most performant quantum processor to-date and available in IBM's global quantum data centers, can now leverage Qiskit to accurately run certain classes of quantum circuits with up to 5,000 two-qubit gate operations. Users can now use these capabilities to expand explorations in how quantum computers can tackle scientific problems across materials, chemistry, life sciences, high-energy physics, and more.

The CHERI Alliance CIC (Community Interest Company) today announced its official launch and the expansion of its membership, welcoming Chevin Technology (UK), Critical Technologies (USA), the Defence Science and Technology Laboratory (DSTL, UK), Google (USA), Light Momentum Technology Corporation (Taiwan), National Cyber Security Centre (NCSC, a part of GCHQ, UK), Parvat Infotech (India), SRI International (USA), TechWorks (UK), Trusted Computer Center of Excellence (USA), the University of Birmingham (UK), and the University of Glasgow (UK) as founding members.

Founded to unite hardware security leaders and system developers, the CHERI Alliance aims to establish CHERI (Capability Hardware Enhanced RISC Instructions) as the new standard for memory safety and scalable software compartmentalization.