MicroCloud Hologram Inc. Develops Quantum-Enhanced Deep Convolutional Neural Network Image 3D Reconstruction Technology

Rhea-AI Summary

MicroCloud Hologram (NASDAQ: HOLO) announced a quantum-enhanced deep convolutional neural network image 3D reconstruction technology system on December 18, 2025. The system integrates quantum convolutional layers, quantum fully connected layers and quantum-optimized 3D models across six core modules: dataset preparation, feature extraction, parameter generation, 3D reconstruction, precision evaluation, and interactive interface. The company says the approach uses quantum superposition and entanglement to improve feature extraction, accelerate training and raise reconstruction precision. The release also discloses cash reserves of over 3 billion RMB and a plan to invest more than $400 million in blockchain, quantum computing, quantum holography and related technologies.

Positive

• Cash reserves exceeding 3 billion RMB
• Planned investment of more than $400 million into frontier technologies
• Six modular architecture (dataset to interface) for 3D reconstruction

Negative

• No independent validation or quantified accuracy/speed metrics provided for the new system

Key Figures

Cash reserves >3 billion RMB Stated company cash reserves in multiple recent releases

Planned investment Over 400 million USD Planned spend on blockchain, quantum, holography, AI/AR and frontier tech

Core modules 6 modules Quantum-enhanced 3D reconstruction system architecture in this article

Qubits used 8 qubits + 4 auxiliary qubits QCNN architecture in prior AI-tagged releases

Current price $2.96 Price before this AI announcement

52-week range $2.77–$370.00 Pre-news 52-week low and high

Move from 52-week high -99.2% Price vs 52-week high before this news

Move from 52-week low 6.86% Price vs 52-week low before this news

Market Reality Check

$2.92 Last Close

Volume Volume 298,251 is below 20-day average 501,782 (relative volume 0.59). low

Technical Price $2.96 is trading below the 200-day MA at $9.42, reflecting a weak longer-term trend.

Peers on Argus 1 Up

Several peers like NEON (-3.76%), WBX (-6.25%), and ELTK (-2.02%) are down, suggesting broader softness, but momentum data flags only one peer (GAUZ +8.77%) and no clear sector-wide move tied to this AI announcement.

Historical Context

Date	Event	Sentiment	Move	Catalyst
Dec 04	Quantum 3D model	Positive	+4.3%	Launch of quantum-driven 3D intelligent model with six core subsystems.
Nov 20	Quantum sync tech	Positive	-2.3%	New quantum synchronization metric and experimental implementation on qubit system.
Nov 17	Quantum big data	Positive	+2.9%	Quantum-empowered big data real-time computing system with efficiency gains.
Nov 14	QCNN classifier	Positive	-9.9%	Next-gen QCNN multi-class classification reaching classical-like accuracy.
Nov 10	Quantum time theory	Positive	+0.0%	Theoretical framework treating time as quantum operator with new applications.

Pattern Detected

Recent quantum/AI announcements skew positive in tone but have produced mixed and often divergent price reactions, with several sizeable selloffs following seemingly favorable R&D updates.

Recent Company History

Over the past months, HOLO has repeatedly highlighted quantum and AI advances. On Nov 10 (news ID 933063), it detailed quantum time research with a flat 0% move. Subsequent quantum systems and models on Nov 17 (+2.91%, ID 936941), Nov 20 (-2.31%, ID 939215), and Dec 4 (+4.27%, ID 944182) drew mixed reactions. An AI-tagged QCNN release on Nov 14 (ID 936435) saw a sharper -9.91% drop, underscoring inconsistent trading responses to similar innovation news.

Market Pulse Summary

This announcement introduces a quantum-enhanced deep convolutional neural network 3D reconstruction system with six core modules spanning data preparation, feature extraction, parameter generation, reconstruction, and evaluation. It adds to a series of quantum and AI advances HOLO highlighted in late 2025, alongside disclosed cash reserves above 3 billion RMB and planned investment over 400 million USD in frontier technologies. Investors may track how these projects progress from technical architecture to concrete products and revenue impact.

Key Terms

quantum convolutional neural network technical

"This system first utilizes quantum convolutional neural network to complete the feature extraction..."

A quantum convolutional neural network is an advanced computer system that uses principles of quantum physics to analyze complex data more efficiently than traditional methods. It mimics how the brain recognizes patterns but operates at a level that could process vast amounts of information rapidly, potentially uncovering insights that help investors make better decisions. Its development could lead to faster, more accurate predictions in financial markets.

quantum entanglement medical

"...leveraging quantum superposition and quantum entanglement characteristics to efficiently extract..."

Quantum entanglement is a phenomenon where two or more particles become linked in such a way that the state of one instantly influences the state of the other, no matter how far apart they are. For investors, understanding entanglement highlights how new, highly interconnected technologies could disrupt traditional markets by enabling instantaneous sharing of information or capabilities across distances, potentially creating new opportunities or risks.

quantum superposition medical

"...integrates traditional convolutional layers, pooling layers, and quantum computing units, leveraging quantum superposition..."

Quantum superposition is a property of tiny particles where a single object can exist in multiple possible states at the same time until it is measured; think of it as a coin spinning so fast it is both heads and tails until you stop it. For investors, superposition is the key principle that gives quantum computers their potential to solve certain problems far faster than conventional machines, which can reshape industries, change competitive advantages and influence the value of tech and cybersecurity investments.

lidar technical

"Its holographic technology services include holographic light detection and ranging (LiDAR) solutions..."

Lidar, which stands for Light Detection and Ranging, is a technology that uses laser beams to create detailed, three-dimensional maps of the environment. It works like a sophisticated eye that measures distances by bouncing light off objects, helping machines see and understand their surroundings. For investors, lidar is important because it enables advancements in autonomous vehicles, robotics, and mapping, which can drive innovation and growth in related industries.

adas technical

"...providing services to customers offering holographic advanced driving assistance systems (ADAS)."

Advanced Driver Assistance Systems (ADAS) are electronic systems in vehicles that assist the driver with safety tasks. Examples include automatic emergency braking, lane keeping assist, and adaptive cruise control. These systems use sensors and cameras to improve vehicle safety.

digital twin technical

"MicroCloud Hologram Inc. also provides holographic digital twin technology services..."

A digital twin is a live virtual replica of a physical asset, process, or system that mirrors real-world behavior using data and models so users can test changes, predict problems, and measure performance without touching the real thing. For investors, digital twins matter because they can lower maintenance costs, speed product development, improve uptime and reliability, and make future cash flows and risks easier to forecast — like using a flight simulator to safely train and tune a real airplane.

augmented reality technical

"...frontier technology fields such as artificial intelligence AR. MicroCloud Hologram Inc.'s goal..."

Augmented reality is technology that layers computer-generated images, information or sounds onto your view of the real world through devices like phones, tablets or smart glasses — like seeing navigation arrows or product labels projected onto what you’re looking at. It matters to investors because it creates new ways to sell hardware, software, services and ads, can change customer engagement and recurring revenue models, and carries adoption and privacy risks that affect company value.

virtual reality technical

"...virtual reality technologies, the quantum-enhanced deep convolutional neural network image 3D reconstruction..."

Virtual reality is a computer-created, immersive environment experienced through headsets and related hardware that replaces your view of the real world with sights and sounds, sometimes including motion or touch—like stepping into a digital room. For investors it matters because VR is a platform for new products and services (games, training, virtual meetings, advertising) where hardware sales, software ecosystems and user engagement determine who captures long-term revenue and growth.

AI-generated analysis. Not financial advice.

SHENZHEN, China, Dec. 18, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively launches a quantum-enhanced deep convolutional neural network image 3D reconstruction technology system. This system first utilizes quantum convolutional neural network to complete the feature extraction of input images, then generates the core parameters of the 3D model through quantum fully connected layers, and finally imports these parameters into the quantum-optimized 3D model to complete the reconstruction, forming a unique advantageous technical mode.

This technical system encompasses six core modules: quantum-optimized dataset preparation, quantum-assisted feature extraction, quantum-enhanced parameter generation, quantum-accelerated 3D reconstruction, quantum-precision model evaluation, and interactive application interface. Each module possesses its own independent functional positioning while also collaborating and connecting with each other, jointly building a complete and efficient technical architecture.

The quantum-optimized dataset preparation module is the technical foundation. The quantum-enhanced deep convolutional neural network image 3D reconstruction technology requires massive high-quality 3D model data as training samples to ensure that the deep learning algorithm can precisely learn the morphological features and structural patterns of 3D models. This module is responsible for the collection and preparation of 3D model data, while employing quantum computing technology for data preprocessing and cleaning, significantly improving the quality and usability of the dataset. High-quality datasets directly determine the precision and robustness of the algorithm. The dataset covers 3D models of various categories and morphologies, and combined with quantum data augmentation technology, further enhances the universality and generalization ability of the algorithm.

The quantum-assisted feature extraction module undertakes the core processing tasks. This module uses quantum convolutional neural networks to perform feature extraction and representation on input images. The quantum convolutional neural network integrates traditional convolutional layers, pooling layers, and quantum computing units, leveraging quantum superposition and quantum entanglement characteristics to efficiently extract higher-level deep features from input images, breaking through the feature extraction bottlenecks of traditional algorithms.

The quantum-enhanced parameter generation module achieves the transformation from features to models. This module precisely maps the high-dimensional feature vectors output by the quantum encoder to three-dimensional space through quantum fully connected layers or quantum optimization regression algorithms. These quantum-optimized parameters can flexibly control key attributes of the 3D model such as shape, size, and pose, achieving more refined model regulation.

The quantum-accelerated 3D reconstruction module completes the final model generation. This module inputs the quantum-enhanced parameters into the pre-built 3D model to generate high-precision 3D reconstruction results. The module incorporates quantum deconvolution layers and quantum upsampling layers, using the parallel processing capabilities of quantum computing to quickly map the feature vectors output by the encoder to three-dimensional space, significantly improving reconstruction efficiency and model precision.

The quantum-precision model evaluation and application extension module ensures technical implementation. The quantum-precision model evaluation module precisely measures the differences and errors between the generated model and the original model through quantum computing technology, optimizing algorithm parameters and improving the training dataset based on this data, continuously enhancing the precision and robustness of the 3D reconstruction model. The application interface module is responsible for the visual presentation of the 3D reconstruction model, building a convenient user interaction interface that supports users in real-time adjustment of model attributes and parameters to meet customized design and personalized needs.

Compared to traditional 3D reconstruction algorithms, the technical system proposed by HOLO, relying on the deep fusion of quantum computing and deep learning, possesses significant advantages of higher precision and stronger adaptability. Through quantum-accelerated training for deep learning on massive data, it precisely extracts image features and structural information to generate 3D models that better meet actual needs.

With the rapid development of quantum computing, deep learning, computer vision, and virtual reality technologies, the quantum-enhanced deep convolutional neural network image 3D reconstruction technology system will have broader application prospects. In the medical field, this technology can be used to achieve precise classification and diagnosis of cases; in the robotics field, it can improve the precision of robot obstacle avoidance; in manufacturing, it can achieve efficient and precise item modeling. In the future, this technology can also deeply integrate with technologies such as augmented reality and virtual reality, combined with the continuous breakthroughs in quantum computing, to expand richer application scenarios.

About MicroCloud Hologram Inc.

MicroCloud Hologram Inc. (NASDAQ: HOLO) is committed to the research and development and application of holographic technology. Its holographic technology services include holographic light detection and ranging (LiDAR) solutions based on holographic technology, holographic LiDAR point cloud algorithm architecture design, technical holographic imaging solutions, holographic LiDAR sensor chip design, and holographic vehicle intelligent vision technology, providing services to customers offering holographic advanced driving assistance systems (ADAS). MicroCloud Hologram Inc. provides holographic technology services to global customers. MicroCloud Hologram Inc. also provides holographic digital twin technology services and owns proprietary holographic digital twin technology resource libraries. Its holographic digital twin technology resource library utilizes a combination of holographic digital twin software, digital content, space data-driven data science, holographic digital cloud algorithms, and holographic 3D capture technology to capture shapes and objects in 3D holographic form. MicroCloud Hologram Inc. focuses on developments such as quantum computing and quantum holography, with cash reserves exceeding 3 billion RMB, and plans to invest more than 400 million in USD from the cash reserves to engage in blockchain development, quantum computing technology development, quantum holography technology development, and derivatives and technology development in frontier technology fields such as artificial intelligence AR. MicroCloud Hologram Inc.'s goal is to become a global leading quantum holography and quantum computing technology company.

Safe Harbor Statement

This press release contains forward-looking statements as defined by the Private Securities Litigation Reform Act of 1995. Forward-looking statements include statements concerning plans, objectives, goals, strategies, future events or performance, and underlying assumptions and other statements that are other than statements of historical facts. When the Company uses words such as "may," "will," "intend," "should," "believe," "expect," "anticipate," "project," "estimate," or similar expressions that do not relate solely to historical matters, it is making forward-looking statements. Forward-looking statements are not guarantees of future performance and involve risks and uncertainties that may cause the actual results to differ materially from the Company's expectations discussed in the forward-looking statements. These statements are subject to uncertainties and risks including, but not limited to, the following: the Company's goals and strategies; the Company's future business development; product and service demand and acceptance; changes in technology; economic conditions; reputation and brand; the impact of competition and pricing; government regulations; fluctuations in general economic; financial condition and results of operations; the expected growth of the holographic industry and business conditions in China and the international markets the Company plans to serve and assumptions underlying or related to any of the foregoing and other risks contained in reports filed by the Company with the Securities and Exchange Commission ("SEC"), including the Company's most recently filed Annual Report on Form 10-K and current report on Form 6-K and its subsequent filings. For these reasons, among others, investors are cautioned not to place undue reliance upon any forward-looking statements in this press release. Additional factors are discussed in the Company's filings with the SEC, which are available for review at www.sec.gov. The Company undertakes no obligation to publicly revise these forward-looking statements to reflect events or circumstances that arise after the date hereof.

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SOURCE MicroCloud Hologram Inc.

FAQ

What did MicroCloud Hologram (HOLO) announce on December 18, 2025?

MicroCloud Hologram announced a quantum-enhanced deep convolutional neural network 3D reconstruction technology system built around six core modules.

How much cash does MicroCloud Hologram (HOLO) report and what investment is planned?

The company reports cash reserves of over 3 billion RMB and plans to invest more than $400 million in blockchain, quantum computing, quantum holography and related fields.

What are the six core modules of HOLO's quantum 3D reconstruction system?

They are quantum-optimized dataset preparation, quantum-assisted feature extraction, quantum-enhanced parameter generation, quantum-accelerated 3D reconstruction, quantum-precision model evaluation, and an interactive application interface.

How does HOLO say quantum computing improves its 3D reconstruction?

HOLO says quantum convolution and entanglement enable more efficient high-level feature extraction, quantum layers map features to 3D parameters, and quantum parallelism accelerates reconstruction.

Will HOLO's announcement immediately change HOLO's revenue or guidance for 2026?

The announcement does not include any revenue figures or formal financial guidance or timelines for commercialization.