MicroAlgo (NASDAQ: MLGO) has announced research on its new Quantum Information Recursive Optimization (QIRO) algorithm, designed to solve complex combinatorial optimization problems using quantum computing. The QIRO algorithm combines quantum computing with recursive algorithms, utilizing quantum state superposition and parallel computing capabilities. The algorithm works through five key stages: problem modeling, quantum state initialization, recursive quantum optimization, measurement/result extraction, and result verification. QIRO demonstrates significant advantages over traditional algorithms, including exponential improvements in computational efficiency and stronger global search capabilities. The algorithm shows promising applications in logistics, financial investment, artificial intelligence, and scientific research. MicroAlgo highlights QIRO's potential for solving real-world optimization challenges in resource allocation, network planning, and transportation logistics.

MicroAlgo plans significant share dilution through $0.8 offering to address $20M convertible bond obligation. Strategic debt restructuring impacts MLGO stockholders.

MicroAlgo Inc. has introduced a pioneering quantum algorithm based on Grover's search, aimed at efficiently identifying pure Nash equilibria within graphical games, enhancing game theory applications.

MicroAlgo (NASDAQ: MLGO) has unveiled a groundbreaking classifier auto-optimization technology based on Variational Quantum Algorithms (VQA). The technology features three key innovations: Adaptive Circuit Pruning (ACP) for reducing computational complexity, Hamiltonian Transformation Optimization (HTO) for improving optimization efficiency, and Quantum Entanglement Regularization (QER) for preventing model overfitting. The solution addresses major challenges in quantum machine learning, including high optimization complexity and noise sensitivity. The technology incorporates Variational Quantum Error Correction (VQEC) to enhance noise resilience in Noisy Intermediate-Scale Quantum (NISQ) devices. Experimental results show the method can reduce computational complexity by at least an order of magnitude while maintaining classification accuracy.

MicroAlgo converts $20M debt into equity at 30% below market value. New shares priced at $0.8 raise dilution concerns. See full impact analysis.

MicroAlgo unveils groundbreaking classical-quantum hybrid algorithm for Multi-Query Optimization, achieving unprecedented 99% qubit efficiency while reducing quantum computation errors.

Insider and Institutional Ownership 1.1% of MicroAlgo shares are owned by institutional investors. Comparatively, 40.1% of Semantix shares are owned by institutional investors. 22.7% of MicroAlgo shares are owned by insiders. Comparatively, 35.5% of Semantix shares are owned by insiders. Strong institutional ownership is an indication that large money managers, endowments and hedge funds believe […]

MicroAlgo Inc. has unveiled the Classical Boosted Quantum Optimization Algorithm, blending classical and quantum computing to solve constrained optimization.

MicroAlgo Inc. is set to issue additional shares at $0.8 each to settle obligations under a bond agreement. This move is part of their debt repayment strategy.

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MicroAlgo Inc. has introduced an innovative quantum image encryption algorithm that offers unparalleled image protection through revolutionary quantum key technology.

MicroAlgo unveils revolutionary distributed computing algorithm that overcomes quantum computer limitations through multi-simulator collaboration, marking a significant advance in quantum processing efficiency.

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