News from the AI & ML world
DeeperML - #advancement
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@quantumcomputingreport.com
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The quantum computing industry is experiencing a surge in activity, marked by significant acquisitions and technological advancements. IonQ has announced its intent to acquire UK-based Oxford Ionics for $1.075 billion in stock and cash, uniting two leaders in trapped-ion quantum computing. This deal aims to accelerate the development of scalable and reliable quantum systems, targeting 256 high-fidelity qubits by 2026 and over 10,000 physical qubits by 2027. The acquisition combines IonQ's quantum computing stack with Oxford Ionics' semiconductor-compatible ion-trap technology, strengthening IonQ's technical capabilities and expanding its European presence. CEO of IonQ, Niccolo de Masi, highlighted the strategic importance of this acquisition, uniting talent from across the world to become the world’s best quantum computing, quantum communication and quantum networking ecosystem.
Recent advancements also include the activation of Europe’s first room-temperature quantum accelerator by Fraunhofer IAF, featuring Quantum Brilliance’s diamond-based QB-QDK2.0 system. This system utilizes nitrogen-vacancy (NV) centers and operates without cryogenic requirements, seamlessly integrating into existing high-performance computing environments. It's co-located with classical processors and NVIDIA GPUs to support hybrid quantum-classical workloads. Moreover, IBM has announced plans to build the world’s first large-scale, error-corrected quantum computer named Starling, aiming for completion by 2028 and cloud availability by 2029. IBM claims it has cracked the code for quantum error correction, moving from science to engineering. Further bolstering the industry's growth, collaborative projects are demonstrating the potential of quantum computing in various applications. IonQ, in partnership with AstraZeneca, AWS, and NVIDIA, has showcased a quantum-accelerated drug discovery workflow that drastically reduces simulation time for key pharmaceutical reactions. Their hybrid system, integrating IonQ’s Forte quantum processor with NVIDIA CUDA-Q and AWS infrastructure, achieved over a 20-fold improvement in time-to-solution for the Suzuki-Miyaura reaction. Additionally, the Karnataka State Cabinet has approved the second phase of the Quantum Research Park at the Indian Institute of Science (IISc) in Bengaluru, allocating ₹48 crore ($5.595 million USD) to expand the state’s quantum technology infrastructure and foster collaboration between academia, startups, and industry.
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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.
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@www.microsoft.com
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Microsoft Research is delving into the transformative potential of AI as "Tools for Thought," aiming to redefine AI's role in supporting human cognition. At the upcoming CHI 2025 conference, researchers will present four new research papers and co-host a workshop exploring this intersection of AI and human thinking. The research includes a study on how AI is changing the way we think and work along with three prototype systems designed to support different cognitive tasks. The goal is to explore how AI systems can be used as Tools for Thought and reimagine AI’s role in human thinking.
As AI tools become increasingly capable, Microsoft has unveiled new AI agents designed to enhance productivity in various domains. The "Researcher" agent can tackle complex research tasks by analyzing work data, emails, meetings, files, chats, and web information to deliver expertise on demand. Meanwhile, the "Analyst" agent functions as a virtual data scientist, capable of processing raw data from multiple spreadsheets to forecast demand or visualize customer purchasing patterns. The new AI agents unveiled over the past few weeks can help people every day with things like research, cybersecurity and more. Johnson & Johnson has reportedly found that only a small percentage, between 10% and 15%, of AI use cases deliver the vast majority (80%) of the value. After encouraging employees to experiment with AI and tracking the results of nearly 900 use cases over about three years, the company is now focusing resources on the highest-value projects. These high-value applications include a generative AI copilot for sales representatives and an internal chatbot answering employee questions. Other AI tools being developed include one for drug discovery and another for identifying and mitigating supply chain risks.
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