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MicroCloud Hologram Inc. reports company news around holographic technology services and related quantum-security research for the Nasdaq-listed issuer under HOLO.
The company’s established business includes holographic LiDAR services, point-cloud algorithm architecture, imaging solutions, sensor chip design, vehicle intelligent vision technology for ADAS customers, and holographic digital twin services, with revenue mainly generated in China. Recent announcements also center on post-quantum cryptography and quantum-computing technologies, including quantum key distribution, quantum random number generation, Strong Designated Verifier Signature design, Grover-algorithm identity authentication, FPGA-based surface-code simulation, and hybrid quantum-classical 3D object detection models.
MicroCloud Hologram Inc. (NASDAQ: HOLO) has announced a breakthrough in optimizing scaling methods for open-source configurations using Deepseek LLM. The company developed a new dynamic balancing mechanism that efficiently adjusts the ratio of parameters to data volume in 7B and 67B configurations, addressing traditional performance bottlenecks in large language models.
HOLO has implemented key technical approaches including supervised fine-tuning (SFT) and direct preference optimization (DPO) to enhance the Deepseek LLM Base model. The company also developed a comprehensive dataset covering multiple fields and languages to support the model's pre-training phase.
The technology aims to improve efficiency in applications such as intelligent customer service, smart writing, and intelligent translation, contributing to industry digital transformation.
MicroCloud Hologram Inc. (NASDAQ: HOLO) has announced a breakthrough in quantum physics research, developing Local Quantum Coherence (LQC) for detecting quantum phase transitions (QPT) in various quantum systems. The company's research applies LQC to several quantum models, including the one-dimensional Hubbard model, XY spin chain model, and Su-Schrieffer-Heeger model.
The research demonstrates that LQC can effectively detect quantum phase transitions at both zero and finite temperatures, offering advantages over traditional detection methods. HOLO's study revealed that LQC shows distinct behaviors in different quantum systems, particularly in quantum dots, providing new insights for quantum materials and device development.
The company's findings contribute to understanding quantum many-body systems and offer new theoretical tools for studying quantum phase transitions, potentially advancing the development of quantum technologies.
MicroCloud Hologram (NASDAQ: HOLO) announced plans to invest up to $200 million in developing quantum blockchain technology, focusing on derivatives and technological innovation in Bitcoin blockchain, quantum computing, and artificial intelligence. The company's key development is a quantum asymmetric consensus chain algorithm based on the Bitcoin blockchain, designed to enhance digital transaction security.
The technology integrates quantum signature technology with blockchain to protect against quantum computing threats. Unlike traditional stake consensus, HOLO's system eliminates mining operations, allowing stake holders to participate in consensus through a delegated proof-of-stake mechanism. The system employs a distributed ledger and peer-to-peer network, enabling independent transaction verification without centralized servers.
This investment aims to strengthen the company's position in quantum-secure blockchain solutions, with potential applications across finance, supply chain, and healthcare sectors.
MicroCloud Hologram (NASDAQ: HOLO) has announced the optimization of stacked sparse autoencoders through the DeepSeek open-source model, enhancing their anomaly detection capabilities. The company implements data normalization techniques to improve model training efficiency by scaling data to specific ranges.
HOLO's implementation utilizes a layered training strategy where the stacked sparse autoencoder learns features progressively, with each layer extracting deeper data patterns. The system employs denoising training and Dropout regularization to enhance model robustness and prevent overfitting.
The integration of the DeepSeek model enables distributed computing for parallel task execution, significantly reducing training time. The model uses pretraining and fine-tuning strategies to accelerate convergence and improve overall performance in anomaly detection applications.
MicroCloud Hologram (NASDAQ: HOLO) has announced a significant breakthrough in digital simulated quantum computing using the DeepSeek model. The company has developed a new neural network architecture called Quantum Tensor Network Neural Network (QTNNN), which optimizes quantum computing simulation while reducing computational resources.
The breakthrough has resulted in two major achievements: a 50% reduction in computational resource consumption and a 30% improvement in simulation accuracy when handling large-scale quantum systems. The company's innovation focuses on optimizing the Tensor Network method through deep learning technology, making it possible to simulate quantum systems more efficiently.
This advancement is particularly significant as hardware implementation of quantum computers still faces technical challenges. The optimized technology will benefit various fields including quantum chemistry, materials science, drug development, finance, and artificial intelligence applications.
MicroCloud Hologram Inc. (NASDAQ: HOLO) announces its research progress in high-order quantum switch technology for quantum holographic communication. The company is developing an innovative quantum switch composed of two quantum switches controlled by a high-order quantum system, enabling flexible adjustment of application sequences.
The research includes detailed simulation models for qubit transmission, quantum switch operations, and environmental factors. HOLO has also developed a novel quantum error correction algorithm using redundant qubits and complex encoding techniques to enhance communication reliability.
The company's work encompasses advanced quantum mechanics theories, mathematical models, and specialized quantum simulation software to predict qubit communication scenarios. This research aims to achieve more efficient and secure quantum communication, potentially impacting information security, computational capabilities, and sensing technologies.
MicroCloud Hologram Inc. (NASDAQ: HOLO) has announced plans to invest up to $200 million in Bitcoin or other digital currencies and their related securities derivatives as part of its capital reserve strategy. The company, which currently holds cash reserves of approximately $257 million, aims to enhance its portfolio diversity and risk tolerance through this initiative.
The investment represents a strategic move to explore the digital currency space while promoting the convergence of holographic AI and quantum computing with digital currencies. HOLO emphasizes that this program will help them understand market mechanisms, price fluctuations, and investment strategies in the digital currency market, supporting their future business expansion and capital operations.
The company plans to maintain active surveillance of market trends and intensify collaboration with partners to promote sustainable development in the digital currency market.
MicroCloud Hologram Inc. (NASDAQ: HOLO) has announced the integration of DeepSeek large model API into their Holographic Digital Human GPT technology. This integration enhances the system's semantic understanding and interaction capabilities, providing users with more natural and proactive services.
The implementation includes customized optimization of the DeepSeek API, advanced semantic understanding technologies, and improved text generation capabilities. The enhanced system can now better understand user intent, detect emotional tendencies, and generate high-quality content across various applications.
HOLO has implemented comprehensive security measures and plans to expand the technology's application across multiple industries, including aerospace, automotive manufacturing, machinery manufacturing, furniture design, fashion, telecommunications, and healthcare. The company aims to continue advancing AI-driven conversational systems through ongoing technological innovation.
MicroCloud Hologram Inc. (NASDAQ: HOLO) has announced plans to integrate DeepSeek's R1 model into its holographic AI applications. The initiative aims to enhance HOLO's capabilities in holographic digital content generation and interaction, leveraging R1's advanced reasoning abilities and autonomous learning features.
The DeepSeek R1 model, known for its multi-stage loop training approach, has shown exceptional performance in math, code, and natural language reasoning tasks. HOLO plans to utilize R1's deep learning algorithms to improve the accuracy of 3D object reconstruction and holographic image generation.
The open-source nature of DeepSeek R1 will enable HOLO to perform customized development to meet various customer needs. The company commits to increasing R&D investment in AI and holographic technology to deliver more innovative products and services for an enhanced holographic experience.
MicroCloud Hologram (NASDAQ: HOLO) has announced breakthroughs in quantum systems research through the combination of detection fields and quantum trajectories. The company has successfully developed a method for studying quantum bits and physical interaction parameters through detection field interaction, requiring highly precise control and advanced experimental equipment.
HOLO's quantum trajectory simulation process involves determining initial quantum system states and detection field parameters, calculating their interaction, and analyzing random measurement records to understand system evolution patterns. The company's analytical method demonstrates broad applicability across different measurement strategies and input quantum states.
The research has shown superior measurement accuracy by calculating the theoretical lower bound of average discrimination error, which consistently proves lower than the average inference error across all test cases. This advancement provides more precise data and reliable results for quantum system research.