Core Insights - MicroCloud Hologram Inc. has made significant advancements in quantum-enhanced imaging, particularly in holographic LiDAR technology, achieving a signal-to-noise ratio (SNR) of 40dB, which enhances imaging quality by providing clear, noise-free visuals [1][5]. Technology Advancements - The company utilizes quantum illumination (QI) to improve detection in noisy environments, successfully distinguishing targets from background noise by leveraging quantum temporal correlations [2][3]. - HOLO's method involves rotating measurements between time and frequency domains, which amplifies uncertainty while maintaining correlation, allowing for effective noise filtering [2]. - The technology employs non-classical time-correlated photon pairs generated through femtosecond-pumped spontaneous parametric down-conversion (SPDC), enabling high precision in imaging [3][4]. Product Development - HOLO has designed a quantum holographic LiDAR device that integrates with superconducting nanowire detectors, facilitating 3D holographic imaging capabilities [4]. - The device's design minimizes angular deviation and allows for the resolution of depth phase information, enhancing its application in various fields [4]. Market Position - MicroCloud is committed to providing advanced holographic technology services, including high-precision LiDAR solutions and holographic digital twin technology, aimed at improving applications in areas such as advanced driver assistance systems (ADAS) [6].

Core Insights - MicroCloud Hologram Inc. has developed a new quantum supervised learning method that demonstrates quantum speedup capabilities in end-to-end classification problems [1][14] - The method overcomes limitations of current quantum machine learning algorithms and maintains high-precision classification even with errors from limited sampling statistics [1][14] Quantum Methodology - The core of the quantum-accelerated classifier involves constructing a classification problem and designing a quantum kernel learning approach that utilizes quantum computing for acceleration [2] - A dataset is constructed that classical computers cannot classify effectively, while quantum computers can efficiently perform classification using quantum kernel methods [6] - HOLO employs parameterized quantum circuits (PQC) for feature mapping, transforming classical data into quantum states to enhance classification accuracy [7][5] Quantum Kernel Learning - Quantum kernel learning uses quantum computers to compute kernel functions that are computationally complex for classical computers [4] - HOLO's approach computes the inner product between quantum states to construct a quantum kernel matrix, which is used to train classical machine learning models [8] Robustness and Error Handling - The method includes error correction strategies to mitigate the impact of noise in quantum computations, ensuring stability and high classification accuracy [10][9] - Optimization strategies from variational quantum algorithms (VQAs) are incorporated to maintain performance under constrained quantum resources [10] Applications and Future Prospects - The technology has potential applications in fields such as financial market prediction and biomedical data classification, leveraging quantum speedup for efficient data processing [12] - As quantum computing hardware advances, the research outcomes are expected to undergo larger-scale validation and application, enhancing the role of quantum supervised learning in machine learning [13][15]

SHENZHEN, China, May 16, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, announced the development of a neural network-based quantum-assisted unsupervised data clustering technology, utilizing a hybrid quantum-classical algorithm framework. This framework integrates the classical self-organizing feature map (SOM) neural network with the powerful capabilities of quantum computing, enabling efficient data clustering in an unsupervised ...

Core Viewpoint - MicroCloud Hologram Inc. has developed a neural network-based quantum-assisted unsupervised data clustering technology that integrates classical self-organizing feature map (SOM) neural networks with quantum computing capabilities, enhancing data clustering efficiency in an unsupervised manner [1][4][11] Group 1: Technology Overview - The Self-Organizing Feature Map (SOM) is an unsupervised learning model used for data clustering, dimensionality reduction, and data visualization, mapping high-dimensional data to a low-dimensional space [2] - Traditional SOM algorithms face challenges in computational complexity and storage when handling massive datasets [3] - The Quantum-Assisted Self-Organizing Feature Map (Q-SOM) model leverages quantum computing to accelerate weight adjustment and data mapping processes, allowing for faster processing of larger datasets [4][5] Group 2: Advantages of Quantum-Assisted Technology - Quantum computing enhances computational efficiency through parallel processing, significantly reducing time costs associated with clustering computations, especially for large-scale data [7] - The quantum-assisted algorithm can handle higher-dimensional data more effectively, reducing complexity in high-dimensional computations [8] - Compared to classical methods, quantum computing offers higher accuracy and stability in solving nonlinear and complex problems, avoiding local optima issues [9] Group 3: Applications and Future Potential - The technology is applicable not only for data clustering but also in fields such as image processing, natural language processing, and financial data analysis, with potential for broader industry applications as quantum technology advances [10][12] - The integration of quantum computing and machine learning is expected to transform data processing methods across various industries, particularly in big data, artificial intelligence, and financial technology [11][12] - Continuous development in quantum computing is anticipated to unlock new potential in fields requiring high computational speed and precision, such as drug discovery and climate change prediction [12][13]

Core Viewpoint - MicroCloud Hologram Inc. has announced a blockchain-based edge storage system aimed at enhancing data circulation by reducing transmission delays and ensuring data integrity through decentralized and secure methods [1][2][3]. Group 1: Edge Storage System - The edge storage system utilizes distributed storage to keep data closer to its source, minimizing delays and network congestion [1][2]. - Each edge device is uniquely identified, allowing for secure data sharing and access control through smart contracts [2][3]. - The combination of edge storage and blockchain technology enhances the efficiency and security of data circulation [2][3]. Group 2: Blockchain Technology - Blockchain technology provides decentralization, immutability, and security, ensuring the integrity of data shared among devices [1][2]. - The system employs a consensus mechanism and encryption algorithms to protect data security and privacy [1][3]. - Smart contracts are used to define access rights and facilitate data exchange, ensuring automated enforcement of rules [6][8]. Group 3: System Architecture - The architecture of the edge storage system includes edge nodes, a blockchain network, smart contracts, and data storage components [4][5]. - Edge nodes consist of various devices like sensors and IoT devices that connect to the blockchain for distributed storage and computation [4][5]. - Data storage is divided into transaction records on the blockchain and data stored on edge nodes, improving latency and security [7][8]. Group 4: Company Overview - MicroCloud Hologram Inc. specializes in holographic technology research and development, providing services globally [9]. - The company offers holographic digital twin technology and has a proprietary resource library for 3D holographic capture [10].

SHENZHEN, China, May 12, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, announced the development of a groundbreaking nonlinear quantum optimization algorithm based on efficient model encoding technology. This algorithm significantly enhances computational efficiency while reducing the consumption of quantum resources. This innovation not only addresses the key bottlenecks of current quantum optimization methods but also demonstrat ...

Market Overview - US stock indices experienced a significant rise for the third consecutive trading day, with the Dow Jones up 486.83 points (1.23%), Nasdaq up 457.99 points (2.74%), and S&P 500 up 108.91 points (2.03%) on April 24 [1] Technology Sector Performance - Major tech stocks saw substantial gains, with Tesla, Amazon, and Microsoft rising over 3%, while Google and Meta increased by more than 2%, and Apple rose nearly 2% [2] - The semiconductor sector led the gains, with Micron Technology and Broadcom up over 6%, Intel and AMD rising over 4%, and Nvidia increasing by more than 3% [2] - Nvidia's market capitalization increased by $90.8 billion (approximately ¥661.8 billion) in one night [2] Company Earnings Reports - Alphabet (Google's parent company) reported Q1 revenue of $90.23 billion, a 12% year-over-year increase, exceeding the expected $89.1 billion. Earnings per share were $2.81, up from $1.89 a year ago, and also above the forecast of $2.01. The operating profit was $30.61 billion, a 20% increase year-over-year, surpassing the expected $28.86 billion. The board authorized a stock buyback of up to $70 billion [6] - Intel reported Q1 revenue of $12.67 billion, a slight decline of 0.4% year-over-year, but above the expected $12.31 billion. Adjusted earnings per share were $0.13, down from $0.18 a year ago, but above the forecast of $0.01. The data center and AI revenue was $4.13 billion, exceeding the analyst expectation of $2.96 billion. Intel projected Q2 revenue between $11.2 billion and $12.4 billion, below the market estimate of $12.88 billion. The company reduced its total capital expenditure target for 2025 from $20 billion to $18 billion, leading to a post-earnings drop of over 7% in its stock [7] Chinese Stocks Performance - The Nasdaq Golden Dragon China Index rose by 0.68%, with notable gains in popular Chinese stocks such as NIO and Futu Holdings, which increased by over 6%, and Pinduoduo, Baidu, NetEase, and Bilibili rising over 2%. Xpeng Motors surged by 39.41%, and ZYBT rose by 34.91% [7][8] Commodity Market - International precious metals futures saw a general increase, with COMEX gold futures rising by 2.04% to $3,361.30 per ounce, and WTI crude oil futures up by 0.84% to $62.79 per barrel [9]

SHENZHEN, China, April 22, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO) ("HOLO" or the "Company"), a Hologram Digital Twins Technology provider, today announced that it developed an innovative solution aiming to provide an effective reconstruction for blockchain when it gets attacked. The solution employs verifiable secret sharing (VSS) technology to ensure that the blockchain system can quickly restore and maintain data integrity and consistency even under extreme circumstances. HOLO's bloc ...

SHENZHEN, China, March 21, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (Nasdaq: HOLO) ("MicroCloud" or the "Company") today filed its operational and financial results for the fiscal year ended December 31, 2024, on Form 20-F with the U.S. Securities and Exchange Commission (the "SEC"). MicroCloud is dedicated to the research, development, and application of holographic technology, striving to offer leading holographic technology services to customers worldwide. In 2024, the Company achieved remarkable su ...

Customer and Vendor Concentration - The company's five largest customers accounted for approximately 41.6% of revenues for the year ended December 31, 2024, with the largest customer contributing about 13.4%[59] - For the years ended December 31, 2023 and 2024, 62.6% and 32.0% of total purchases were from three and two vendors, respectively, indicating a significant vendor concentration risk[60] Research and Development - The company expects to incur substantial research and development costs, which could significantly reduce profitability, with no guarantee of generating future revenue[56] - The company's success in the automotive sector relies on the commercialization of its holographic ADAS solutions, which are still in the early stages of development by customers[46] Market Risks - The market adoption of LiDAR technology, particularly holographic LiDAR, remains uncertain, which could adversely affect the company's business if adoption does not develop as expected[50] - The company faces intense competition in the holographic service market, which could create downward pressure on pricing and profitability[47] - Continued pricing pressures from automotive OEMs could lead to low profitability or losses for the company[65] Financial and Capital Risks - The company may need to raise additional capital in the future, which may not be available on favorable terms, potentially limiting growth opportunities[57] - The company's financial results could be adversely affected if any key supplier fails to fulfill contractual obligations, impacting cash flows and profitability[61] - The company has a limited operating history, and its past growth rates may not be indicative of future performance[66] - Rapid growth has placed strain on management and resources, affecting the company's ability to sustain growth[67] Operational Challenges - Attracting and retaining skilled personnel is critical for future success, with intense competition for talent[68] - Negative media coverage could harm the company's brand and adversely affect sales[69] - The company relies on third-party services, and disruptions could slow user growth and negatively impact operations[79] - Insurance coverage is limited, and any uninsured disruptions could result in substantial costs and affect financial condition[81] Internal Controls and Compliance - The company has identified material weaknesses in internal control over financial reporting, particularly in understanding U.S. GAAP, which may lead to misstatements in financial statements[94] - The company plans to hire personnel with U.S. GAAP experience to strengthen its financial reporting function and address identified weaknesses[95] - The company may incur additional operating costs as it implements measures to remediate identified weaknesses in internal controls[96] Regulatory Environment - The company is subject to extensive regulations in China, which may create uncertainties regarding compliance and operational continuity[87] - The company faces risks related to data protection and cybersecurity, which could lead to unexpected costs and enforcement actions[89] - The company is subject to evolving PRC laws regarding data security and privacy, which may create uncertainties in compliance[121] Economic and Political Risks - The company is exposed to risks from adverse changes in China's economic, political, or social conditions, which could materially affect its financial condition[103] - The international economic relations between the U.S. and China remain volatile, affecting the company's competitive position and market demand[107] Taxation and Financial Regulations - The PRC withholding tax rate on dividends paid by PRC subsidiaries to foreign enterprises is currently 10%[146] - The withholding tax rate may be reduced to 5% if certain conditions are met under the Double Tax Avoidance Arrangement[146] - The PRC enterprise income tax rate is generally 25% for indirect transfers of assets by non-PRC resident enterprises[152] Foreign Exchange and Liquidity Risks - Fluctuations in exchange rates could materially affect the company's results of operations and investment value, with the Renminbi having appreciated over 20% against the U.S. dollar since 2005[176] - The company relies on dividends from its PRC subsidiaries to fund cash requirements, and approval from SAFE is needed for converting Renminbi into foreign currency for capital expenses[178] - The company is exposed to liquidity risk, which may hinder its ability to meet commitments and business needs[559] Shareholder and Market Risks - The trading prices of the company's Ordinary shares may be volatile due to various factors, including market conditions and performance of other PRC companies listed in the U.S.[193] - The sale of substantial amounts of Ordinary shares could adversely affect the market price and the company's ability to raise capital in the future[199] - If securities analysts do not publish research or publish unfavorable reports, the company's share price and trading volume could decline[200]