News from the AI & ML world
DeeperML - #quantumcomputing
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@www.microsoft.com
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References:
John Werner
, www.microsoft.com
Microsoft is actively enhancing AI security and providing guidance to organizations navigating the integration of artificial intelligence. Deputy CISO Yonatan Zunger has shared valuable tips on safely and efficiently implementing AI, emphasizing the importance of a collaborative approach to establishing identity standards for agent access across various systems. Microsoft is also focused on building sophisticated AI agents that can augment and amplify organizational capabilities across various sectors.
Recent developments highlight Microsoft's commitment to advancing AI in healthcare. The Azure AI Foundry platform is powering key healthcare advancements in collaboration with Stanford, showcasing the practical application of agentic AI in analyzing complex data and improving patient outcomes. This partnership demonstrates the potential of AI to transform healthcare by enabling more efficient and accurate analysis, leading to better diagnoses and treatment plans. Microsoft is also focused on the future of AI agents and the need for evolving identity standards. As AI agents become more autonomous and capable of independent problem-solving, the need for secure and standardized access to data and systems becomes critical. The company's work in developing agents for developer and operations workflows, such as the Conditional Access Optimizer Agent, demonstrates its proactive approach to addressing these challenges and ensuring the responsible development and deployment of AI technologies. Recommended read:
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@blogs.nvidia.com
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Recent advancements in quantum computing include the launch of new supercomputers and the development of open-source frameworks. NVIDIA and AIST have collaborated to launch ABCI-Q, a supercomputing system designed for hybrid quantum-AI research. This system, powered by NVIDIA H100 GPUs and utilizing NVIDIA’s Quantum-2 InfiniBand platform, is hosted at the Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT). ABCI-Q supports hybrid workloads by integrating GPU-based simulation with physical quantum processors from Fujitsu, QuEra, and OptQC, aiming to advance quantum error correction and algorithm development. It serves as a testbed for quantum-GPU workflows across various hardware modalities.
Quantum Machines has introduced QUAlibrate, an open-source calibration framework designed to significantly reduce the time required for quantum computer calibration. Calibration, a major hurdle in quantum system performance and scalability, can now be reduced from hours to minutes. QUAlibrate enables the creation, execution, and sharing of modular calibration protocols, allowing researchers to calibrate multi-qubit superconducting systems rapidly. At the Israeli Quantum Computing Center, full multi-qubit calibration was achieved in just 140 seconds using QUAlibrate. The framework is built on the QUA programming language and uses the Quantum Abstract Machine (QUAM) to model quantum hardware, featuring a graph-based calibration approach. These advancements are supported by strategic collaborations and investments in quantum technologies. SilQ Connect, a startup focusing on distributed quantum computing, has secured pre-seed funding to advance modular quantum interconnects. This funding from QV Studio, Quantacet, and Quantonation will support the development of microwave-optical quantum interconnects for scalable quantum systems. Additionally, Taiwan's National Center for High-Performance Computing is deploying a new NVIDIA-powered AI supercomputer to support research in climate science, quantum research, and the development of large language models. This initiative aims to foster cross-domain collaboration and global AI leadership. Recommended read:
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@blogs.nvidia.com
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NVIDIA is significantly expanding its presence in the AI ecosystem through strategic partnerships and the introduction of innovative technologies. At Computex 2025, CEO Jensen Huang unveiled NVLink Fusion, a groundbreaking program that opens NVIDIA's high-speed NVLink interconnect technology to non-NVIDIA CPUs and accelerators. This move is poised to solidify NVIDIA's role as a central component in AI infrastructure, even in systems utilizing silicon from other vendors, including MediaTek, Marvell, Fujitsu, and Qualcomm. This initiative represents a major shift from NVIDIA's previously exclusive use of NVLink and is intended to enable the creation of semi-custom AI infrastructures tailored to specific needs.
This strategy ensures that while customers may incorporate rival chips, the underlying AI ecosystem remains firmly rooted in NVIDIA's technologies, including its GPUs, interconnects, and software stack. NVIDIA is also teaming up with Foxconn to construct an AI supercomputer in Taiwan, further demonstrating its commitment to advancing AI capabilities in the region. The collaboration will see Foxconn subsidiary, Big Innovation Company, delivering the infrastructure for 10,000 NVIDIA Blackwell GPUs. This substantial investment aims to empower Taiwanese organizations by providing the necessary AI cloud computing resources to facilitate the adoption of AI technologies across both private and public sectors. In addition to hardware advancements, NVIDIA is also investing in quantum computing research. Taiwan's National Center for High-Performance Computing (NCHC) is deploying a new NVIDIA-powered AI supercomputer designed to support climate science, quantum research, and the development of large language models. Built by ASUS, this supercomputer will feature NVIDIA HGX H200 systems with over 1,700 GPUs, along with other advanced NVIDIA technologies. This initiative aligns with NVIDIA's broader strategy to drive breakthroughs in sovereign AI, quantum computing, and advanced scientific computation, positioning Taiwan as a key hub for AI development and technological autonomy. Recommended read:
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Joe DeLaere@NVIDIA Technical Blog
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NVIDIA has announced the opening of its NVLink technology to rival companies, a move revealed by CEO Jensen Huang at Computex 2025. The new program, called NVLink Fusion, allows companies making custom CPUs and accelerators to license the NVLink port designs. This opens the door for non-NVIDIA chips to integrate with NVIDIA's AI infrastructure, fostering a more flexible AI hardware ecosystem. MediaTek, Marvell, Fujitsu, and Qualcomm are among the early partners signing on to integrate their chips with NVIDIA's GPUs via NVLink Fusion.
NVIDIA's decision to extend NVLink support is a strategic play to remain central to the AI landscape. By enabling companies to combine their custom silicon with NVIDIA's technology, NVIDIA ensures it remains essential to their AI strategies and potentially captures additional revenue streams. NVLink Fusion allows for semi-custom AI infrastructure where other processors are involved, but the underlying connective tissue belongs to NVIDIA. The high-speed interconnect offers significantly higher bandwidth compared to PCIe 5.0, offering advantages for CPU-to-GPU communications. This expansion doesn't mean NVIDIA is entirely opening the interconnect standard. Connecting an Intel CPU to an AMD GPU directly using NVLink Fusion remains impossible. NVIDIA is essentially allowing semi-custom accelerator designs to take advantage of the high-speed interconnect even if the accelerator isn't designed by NVIDIA. As part of the announcement, NVIDIA also unveiled its next-generation Grace Blackwell systems and a new AI platform called DGX Cloud Lepton, further solidifying its position in the AI compute market. Recommended read:
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Siôn Geschwindt@The Next Web
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References:
The Next Web
, medium.com
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Quantum computing is rapidly advancing, presenting both opportunities and challenges. Researchers at Toshiba Europe have achieved a significant milestone by transmitting quantum-encrypted messages over a record distance of 254km using standard fiber optic cables. This breakthrough, facilitated by quantum key distribution (QKD) cryptography, marks the first instance of coherent quantum communication via existing telecom infrastructure. QKD leverages the principles of quantum mechanics to securely share encryption keys, making eavesdropping virtually impossible, as any attempt to intercept the message would immediately alert both parties involved.
This advance addresses growing concerns among European IT professionals, with 67% fearing that quantum computing could compromise current encryption standards. Unlike classical computers, which would take an impractical amount of time to break modern encryption, quantum computers can exploit phenomena like superposition and entanglement to potentially crack even the most secure classical encryptions within minutes. This has prompted global governments and organizations to accelerate the development of robust cryptographic algorithms capable of withstanding quantum attacks. Efforts are underway to build quantum-secure communication infrastructure. Heriot-Watt University recently inaugurated a £2.5 million Optical Ground Station (HOGS) to promote satellite-based quantum-secure communication. In July 2024, Toshiba Europe, GÉANT, PSNC, and Anglia Ruskin University demonstrated cryogenics-free QKD over a 254 km fiber link, using standard telecom racks and room temperature detectors. Initiatives such as Europe’s EuroQCI and ESA’s Eagle-1 satellite further underscore the commitment to developing and deploying quantum-resistant technologies, mitigating the silent threat that quantum computing poses to cybersecurity. Recommended read:
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@www.aiwire.net
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References:
AIwire
, www.aiwire.net
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The Quantum Economic Development Consortium (QED-C) has released a report detailing the potential synergies between Quantum Computing (QC) and Artificial Intelligence (AI). The report, based on a workshop, highlights how these two technologies can work together to solve problems currently beyond the reach of classical computing. AI could be used to accelerate circuit design, application development, and error correction in QC. Conversely, QC offers the potential to enhance AI models by efficiently solving complex optimization and probabilistic tasks, which are infeasible for classical systems.
A hybrid approach, integrating the strengths of classical AI methods with QC algorithms, is expected to substantially reduce algorithmic complexity and improve the efficiency of computational processes and resource allocation. The report identifies key areas where this integration can yield significant benefits, including chemistry, materials science, logistics, energy, and environmental modeling. The applications could range from predicting high-impact weather events to improving the modeling of chemical reactions for pharmaceutical advancements. The report also acknowledges the necessity of cross-industry collaboration, expanded academic research, and increased federal support to advance QC + AI development. Celia Merzbacher, Executive Director of QED-C, emphasized the importance of collaboration between industry, academia, and governments to maximize the potential of these technologies. A House Science Committee hearing is scheduled to assess the progress of the National Quantum Initiative, underscoring the growing importance of quantum technologies in the U.S. Recommended read:
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@news.microsoft.com
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References:
news.microsoft.com
, The Microsoft Cloud Blog
Microsoft is aggressively expanding its AI capabilities across various sectors, introducing new AI agents designed to enhance productivity and security. Recently unveiled AI agents for Microsoft 365 Copilot, such as Researcher and Analyst, are designed to help users with complex research tasks and data analysis. Researcher can build detailed strategies, identify opportunities, and create comprehensive reports by integrating data from internal and external sources. Analyst can forecast demand and visualize customer purchasing patterns, functioning like a virtual data scientist.
Microsoft is also focused on defending against AI-enhanced cyber threats and enhancing cybersecurity measures. New AI agents within Microsoft Security Copilot and Microsoft Purview are designed to automate tasks related to phishing, data security, and identity management. For instance, a phishing triage agent can handle routine phishing alerts, allowing human cybersecurity teams to focus on more complex threats. These advancements come at a time when AI is lowering the barrier for cybercrime, with threat actors using AI tools to create convincing social engineering lures and fraudulent websites. In addition to AI advancements, Microsoft is also making strides in quantum computing, moving it from a futuristic concept to practical applications. Quantum computing is currently being used to optimize finance, discover new drugs, secure networks, and build better batteries. Furthering its AI capabilities, Microsoft has launched "Computer Use" for Copilot Studio as an early research preview, which allows AI agents to interact directly with websites and desktop applications, enabling automation even when there is no API available. Microsoft also recently introduced "Draft with Copilot" for Copilot Studio, which will help users write or rewrite prompts using Copilot to produce better outcomes, with Copilot also able to generate sample test data. Recommended read:
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@sciencedaily.com
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Recent advancements in quantum computing research have yielded promising results. Researchers at the University of the Witwatersrand in Johannesburg, along with collaborators from Huzhou University in China, have discovered a method to shield quantum information from environmental disruptions, potentially leading to more reliable quantum technologies. This breakthrough involves manipulating quantum wave functions to preserve quantum information, which could enhance medical imaging, improve AI diagnostics, and strengthen data security by providing ultra-secure communication.
UK startup Phasecraft has announced a new algorithm, THRIFT, that improves the ability of quantum computers to model new materials and chemicals by a factor of 10. By optimizing quantum simulation, THRIFT enables scientists to model new materials and chemicals faster and more accurately, even on today’s slower machines. Furthermore, Oxford researchers have demonstrated a 25-nanosecond controlled-Z gate with 99.8% fidelity, combining high speed and accuracy in a simplified superconducting circuit. This achievement advances fault-tolerant quantum computing by improving raw gate performance without relying heavily on error correction or added hardware. Recommended read:
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Stephen Ornes@Quanta Magazine
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References:
Quanta Magazine
, medium.com
A novel quantum algorithm has demonstrated a speedup over classical computers for a significant class of optimization problems, according to a recent report. This breakthrough could represent a major advancement in harnessing the potential of quantum computers, which have long promised faster solutions to complex computational challenges. The new algorithm, known as decoded quantum interferometry (DQI), outperforms all known classical algorithms in finding good solutions to a wide range of optimization problems, which involve searching for the best possible solution from a vast number of choices.
Classical researchers have been struggling to keep up with this quantum advancement. Reports of quantum algorithms often spark excitement, partly because they can offer new perspectives on difficult problems. The DQI algorithm is considered a "breakthrough in quantum algorithms" by Gil Kalai, a mathematician at Reichman University. While quantum computers have generated considerable buzz, it has been challenging to identify specific problems where they can significantly outperform classical machines. This new algorithm demonstrates the potential for quantum computers to excel in optimization tasks, a development that could have broad implications across various fields. Recommended read:
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staff@insidehpc.com
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Nvidia CEO Jensen Huang has publicly walked back previous comments made in January, where he expressed skepticism regarding the timeline for quantum computers becoming practically useful. Huang apologized for his earlier statements, which caused a drop in stock prices for quantum computing companies. During the recent Nvidia GTC 2025 conference in San Jose, Huang admitted his misjudgment and highlighted ongoing advancements in the field, attributing his initial doubts to his background in traditional computer systems development. He expressed surprise that his comments had such a significant impact on the market, joking about the public listing of quantum computing firms.
SEEQC and Nvidia announced a significant breakthrough at the conference, demonstrating a fully digital quantum-classical interface protocol between a Quantum Processing Unit (QPU) and a Graphics Processing Unit (GPU). This interface is designed to facilitate ultra-low latency and bandwidth-efficient quantum error correction. Furthermore, Nvidia is enhancing its support for quantum research with the CUDA-Q platform, designed to streamline the development of hybrid, accelerated quantum supercomputers. CUDA-Q performance can now be pushed further than ever with v0.10 support for the NVIDIA GB200 NVL72. Recommended read:
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@Scientific American
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D-Wave, a quantum computing firm, has asserted that its quantum computers have achieved quantum supremacy by solving a problem of scientific relevance faster than classical computers. Specifically, D-Wave Quantum Inc. claims that its annealing quantum computer outperformed the Frontier supercomputer in simulating complex magnetic materials, a feat published in the journal Science. The company stated that its system completed simulations in minutes that would take Frontier nearly a million years and consume more than the world's annual electricity consumption. The results, according to D-Wave executives, validate the practical advantage of quantum annealing and represent a significant milestone in quantum computational supremacy and materials discovery.
However, the company's claims have been met with scrutiny. Some researchers argue that classical algorithms can still rival or exceed quantum methods in certain cases. For instance, researchers at the Flatiron Institute and EPFL have suggested that classical algorithms, including belief propagation and time-dependent variational Monte Carlo methods, can match or even surpass D-Wave's results in specific scenarios. D-Wave's CEO, Alan Baratz, has responded to these criticisms, arguing that the competing studies tested only a subset of the problems addressed in D-Wave's work and that their simulations covered a broader range of lattice geometries and conditions. Recommended read:
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Cierra Choucair@thequantuminsider.com
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NVIDIA is establishing the Accelerated Quantum Research Center (NVAQC) in Boston to integrate quantum hardware with AI supercomputers. The aim of the NVAQC is to enable accelerated quantum supercomputing, addressing quantum computing challenges such as qubit noise and error correction. Commercial and academic partners will work with NVIDIA, with collaborations involving industry leaders like Quantinuum, Quantum Machines, and QuEra, as well as researchers from Harvard's HQI and MIT's EQuS.
NVIDIA's GB200 NVL72 systems and the CUDA-Q platform will power research on quantum simulations, hybrid quantum algorithms, and AI-driven quantum applications. The center will support the broader quantum ecosystem, accelerating the transition from experimental to practical quantum computing. Despite the CEO's recent statement that practical quantum systems are likely still 20 years away, this investment shows confidence in the long-term potential of the technology. Recommended read:
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Harry Goldstein@IEEE Spectrum
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The quantum computing field is experiencing a surge in activity, with several significant developments reported recently. VTT Technical Research Centre of Finland and IQM Quantum Computers have unveiled Europe's first 50-qubit superconducting quantum computer, accessible to researchers and companies through the VTT QX quantum computing service. This milestone strengthens Finland's position as a global leader in quantum computing, following a phased development plan that began with a 5-qubit system in 2021.
Chinese researchers have also made headlines with their Zuchongzhi 3.0, a 105-qubit superconducting quantum processor. They claim it completed a computational task in seconds that would take the world’s most powerful supercomputer an estimated 6.4 billion years to replicate. While the task was a benchmark designed to favor quantum processors, it still reinforces the potential for quantum computational advantage. Also, Mitsubishi Electric and partners are collaborating to develop scalable quantum information processing by connecting multiple quantum devices in practical environments, addressing limitations in single quantum computers. Recommended read:
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Siôn Geschwindt@The Next Web
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Dutch quantum hardware company QuantWare B.V. has secured €20 million in a Series A funding round to scale its quantum processors for next-generation computing. The round was co-led by Invest-NL Deep Tech Fund and Innovation Quarter, with participation from EIC Fund and existing investors. QuantWare develops VIO, a technology that allows its customers to build larger single-chip quantum processing units, which are less prone to interference.
QuantWare's VIO technology aims to solve scaling bottlenecks that limit the size of QPUs today, allowing users to scale any qubit design and unlocking the fastest path towards quantum computers with more than 1 million qubits in a single processor. The funding will be used to further develop VIO, expand chip fabrication facilities, and roll out QuantWare’s Contralto-A QPU, designed for quantum error correction. QuantWare's CEO, Matthijs Rijlaarsdam, stated that their mission is to make VIO the scaling standard and power the first million-qubit quantum computers of the hyperscalers of tomorrow. Recommended read:
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Edd Gent@IEEE Spectrum
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References:
IEEE Spectrum
The future of quantum computing is trending towards modularity, as companies and researchers seek to overcome the limitations of squeezing more qubits onto a single chip. Fabrication and connectivity challenges have prompted a shift toward linking multiple quantum devices to create larger, more powerful computers capable of tackling real-world problems. The focus is on developing technologies that enable the interconnection of quantum processors, as single computers face limited processing capacity and potential service disruptions.
One approach to modular quantum computing involves quantum communication networks (QCNs), which leverage quantum mechanics to transmit quantum information. QCNs promise to link quantum computers and quantum sensors, enabling distributed quantum computing and sensing. Distributed quantum computing harnesses the capabilities of individual quantum computers distributed across different locations to collectively perform quantum computations. Mitsubishi Electric and partners have also signed a joint research agreement to develop scalable quantum information processing by connecting multiple quantum devices in practical environments. VTT Technical Research Centre of Finland and IQM Quantum Computers have launched Europe’s first 50-qubit superconducting quantum computer, now open to researchers and companies. QuantWare, a startup from the Netherlands, claims to have created a 3D chip architecture that offers the fastest route to a 1-million qubit quantum computer. PsiQuantum claims to have solved scalability issues that have long plagued photonic approaches. Delft-based Q*Bird and Eurofiber secure €1M grant to advance quantum-secured communication, this initiative is part of the QUEST project. QuantWare raises €20M to scale quantum processors for next-gen computing. Recommended read:
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