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WiMi Researches Reinforcement Learning-Based Blockchain Federated Learning Framework to Optimize Model Aggregation Strategy and Security

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WiMi Hologram Cloud (NASDAQ: WIMI) announced research into integrating Reinforcement Learning (RL) with blockchain-based federated learning frameworks. The initiative aims to optimize model aggregation strategies and enhance security in federated learning systems. The RL algorithm can dynamically adjust model aggregation timing, participant selection, and transaction costs to balance information timeliness and data bias.

The framework has potential applications in healthcare for secure data sharing, financial services for risk management, and IoT for device collaboration. This research represents an innovation combining AI, blockchain, and reinforcement learning to address trust and efficiency challenges in traditional federated learning.

WiMi Hologram Cloud (NASDAQ: WIMI) ha annunciato una ricerca per integrare l'apprendimento per rinforzo (RL) con framework di apprendimento federato basati su blockchain. L'iniziativa mira a ottimizzare le strategie di aggregazione dei modelli e migliorare la sicurezza nei sistemi di apprendimento federato. L'algoritmo RL può regolare dinamicamente il timing dell'aggregazione dei modelli, la selezione dei partecipanti e i costi di transazione per bilanciare la tempestività delle informazioni e il bias dei dati.

Il framework ha potenziali applicazioni nella sanità per la condivisione sicura dei dati, nei servizi finanziari per la gestione del rischio e nell'IoT per la collaborazione tra dispositivi. Questa ricerca rappresenta un'innovazione che combina IA, blockchain e apprendimento per rinforzo per affrontare le sfide di fiducia ed efficienza nell'apprendimento federato tradizionale.

WiMi Hologram Cloud (NASDAQ: WIMI) anunció una investigación para integrar el aprendizaje por refuerzo (RL) con marcos de aprendizaje federado basados en blockchain. La iniciativa tiene como objetivo optimizar las estrategias de agregación de modelos y mejorar la seguridad en los sistemas de aprendizaje federado. El algoritmo RL puede ajustar dinámicamente el tiempo de agregación del modelo, la selección de participantes y los costos de transacción para equilibrar la puntualidad de la información y el sesgo de datos.

El marco tiene aplicaciones potenciales en la salud para compartir datos de forma segura, en servicios financieros para la gestión de riesgos, y en IoT para la colaboración entre dispositivos. Esta investigación representa una innovación que combina IA, blockchain y aprendizaje por refuerzo para abordar los desafíos de confianza y eficiencia en el aprendizaje federado tradicional.

WiMi 홀로그램 클라우드 (NASDAQ: WIMI)는 강화 학습 (RL)을 블록체인 기반의 연합 학습 프레임워크와 통합하는 연구를 발표했습니다. 이 이니셔티브는 모델 집계 전략을 최적화하고 연합 학습 시스템의 보안을 강화하는 것을 목표로 하고 있습니다. RL 알고리즘은 모델 집계 타이밍, 참여자 선택 및 거래 비용을 동적으로 조정하여 정보의 적시성과 데이터 편향을 균형 있게 조절할 수 있습니다.

이 프레임워크는 안전한 데이터 공유를 위한 헬스케어, 위험 관리를 위한 금융 서비스 및 장치 간 협력을 위한 IoT에서 잠재적인 응용 프로그램을 가지고 있습니다. 이 연구는 AI, 블록체인 및 강화 학습을 결합한 혁신을 나타내며 전통적인 연합 학습에서 신뢰성과 효율성 문제를 해결하고자 합니다.

WiMi Hologram Cloud (NASDAQ: WIMI) a annoncé des recherches sur l'intégration de l'apprentissage par renforcement (RL) avec des frameworks d'apprentissage fédéré basés sur la blockchain. L'initiative vise à optimiser les stratégies d'agrégation des modèles et à renforcer la sécurité des systèmes d'apprentissage fédéré. L'algorithme RL peut ajuster dynamiquement le timing de l'agrégation des modèles, la sélection des participants et les coûts de transaction pour équilibrer la pertinence de l'information et le biais des données.

Ce cadre a des applications potentielles dans le secteur de la santé pour le partage sécurisé des données, dans les services financiers pour la gestion des risques, et dans l'IoT pour la collaboration entre dispositifs. Cette recherche représente une innovation combinant IA, blockchain et apprentissage par renforcement pour répondre aux défis de confiance et d'efficacité dans l'apprentissage fédéré traditionnel.

WiMi Hologram Cloud (NASDAQ: WIMI) hat eine Forschung zur Integration von Verstärkungslernen (RL) mit blockchain-basierten föderierten Lernframeworks angekündigt. Die Initiative zielt darauf ab, die Strategien zur Modellaggregation zu optimieren und die Sicherheit in föderierten Lernsystemen zu verbessern. Der RL-Algorithmus kann die Zeitpunkte der Modellaggregation, die Auswahl der Teilnehmer und die Transaktionskosten dynamisch anpassen, um die Aktualität von Informationen und Datenverzerrungen ins Gleichgewicht zu bringen.

Das Framework hat potenzielle Anwendungen im Gesundheitswesen für sichere Datenaustausch, im Finanzwesen für Risikomanagement und im IoT für die Zusammenarbeit zwischen Geräten. Diese Forschung stellt eine Innovation dar, die KI, Blockchain und Verstärkungslernen kombiniert, um Herausforderungen in Bezug auf Vertrauen und Effizienz im traditionellen föderierten Lernen zu begegnen.

Positive
  • Research initiative combines three cutting-edge technologies: AI, blockchain, and reinforcement learning
  • Technology has practical applications in healthcare, financial services, and IoT sectors
  • Framework aims to optimize transaction costs while maintaining learning effectiveness
Negative
  • None.

Insights

This research announcement on reinforcement learning and blockchain federated learning, while technically complex, has minimal immediate impact on WiMi's business operations or stock value. The framework is still in early research stages without any concrete implementation timeline, revenue potential, or commercial partnerships.

The technology aims to optimize data sharing and model training across different participants while maintaining privacy and reducing costs. However, the announcement lacks specific metrics, development milestones, or clear monetization strategy. For a small-cap company ($83.5M) in the competitive AR/hologram space, pure research initiatives without clear path to commercialization typically don't move the needle on valuation.

The company's broad focus across multiple emerging technologies (AR, blockchain, AI) rather than concentrated expertise in core profitable areas raises concerns about resource allocation and execution capability. Investors should watch for future updates showing actual product development and revenue generation from this research.

BEIJING, Nov. 8, 2024 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the initiation of exploring the integration of Reinforcement Learning (RL) into the federated learning framework. RL, as a significant branch of machine learning, has become a crucial tool for optimizing the federated learning process due to its decision-making capabilities in complex environments.

Reinforcement Learning is a machine learning approach that enables an intelligent agent to learn optimal strategies through interactions with the environment. In a blockchain-based federated learning framework utilizing reinforcement learning, the reinforcement learning algorithm can dynamically adjust the timing of model aggregation, selection of data participants, and transaction costs. This achieves a balance between information timeliness and data bias, as well as intelligent control over transaction costs, ultimately optimizing the overall learning performance.

In federated learning, there can be significant differences in the datasets of different participants, known as the data bias problem. Additionally, model updates need to be aggregated at the appropriate timing to avoid outdated information affecting overall learning performance. The reinforcement learning algorithm can simulate interactions with the environment to learn when to upload model updates and how to select the most effective models for aggregation under different data distributions. This helps find the optimal balance between information timeliness and data bias. The cost of blockchain transactions, including the consumption of computational resources and network bandwidth, is another important consideration in federated learning. Reinforcement learning can intelligently predict network conditions, resource availability, and transaction priorities to dynamically adjust the frequency and scale of model aggregation. This ensures learning effectiveness while minimizing overall transaction costs. By applying reinforcement learning algorithms to optimize model aggregation strategies, not only does it significantly improve federated learning efficiency and model accuracy, but it also effectively reduces transaction costs.

With the continuous advancement of technology, blockchain-based federated learning frameworks based on reinforcement learning will play a crucial role in various fields such as healthcare, financial services, and the Internet of Things (IoT), promoting the security, efficiency, and widespread adoption of artificial intelligence technology. For example, in the healthcare industry, this framework can facilitate data sharing among hospitals, research institutions, and patients, accelerating the development of disease diagnosis and treatment plans while strictly protecting individual privacy. In the financial services industry, it can assist banks and financial institutions in building more secure and efficient credit assessment and risk management models. In the field of IoT, it enables intelligent collaboration among devices, enhancing the overall network's responsiveness and intelligence level.

WiMi's research on the blockchain-based federated learning framework using reinforcement learning represents a significant innovation at the intersection of artificial intelligence, blockchain technology, and reinforcement learning. It provides innovative approaches to address the trust, security, and efficiency issues faced by traditional federated learning. In the future, with further theoretical research and practical applications, the technological potential of blockchain-based federated learning using reinforcement learning will be more fully explored and widely applied in various industry sectors.

About WiMi Hologram Cloud

WiMi Hologram Cloud, Inc. (NASDAQ:WiMi) is a holographic cloud comprehensive technical solution provider that focuses on professional areas including holographic AR automotive HUD software, 3D holographic pulse LiDAR, head-mounted light field holographic equipment, holographic semiconductor, holographic cloud software, holographic car navigation and others. Its services and holographic AR technologies include holographic AR automotive application, 3D holographic pulse LiDAR technology, holographic vision semiconductor technology, holographic software development, holographic AR advertising technology, holographic AR entertainment technology, holographic ARSDK payment, interactive holographic communication and other holographic AR technologies.

Safe Harbor Statements

This press release contains "forward-looking statements" within the Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified by terminology such as "will," "expects," "anticipates," "future," "intends," "plans," "believes," "estimates," and similar statements. Statements that are not historical facts, including statements about the Company's beliefs and expectations, are forward-looking statements. Among other things, the business outlook and quotations from management in this press release and the Company's strategic and operational plans contain forward−looking statements. The Company may also make written or oral forward−looking statements in its periodic reports to the US Securities and Exchange Commission ("SEC") on Forms 20−F and 6−K, in its annual report to shareholders, in press releases, and other written materials, and in oral statements made by its officers, directors or employees to third parties. Forward-looking statements involve inherent risks and uncertainties. Several factors could cause actual results to differ materially from those contained in any forward−looking statement, including but not limited to the following: the Company's goals and strategies; the Company's future business development, financial condition, and results of operations; the expected growth of the AR holographic industry; and the Company's expectations regarding demand for and market acceptance of its products and services.

Further information regarding these and other risks is included in the Company's annual report on Form 20-F and the current report on Form 6-K and other documents filed with the SEC. All information provided in this press release is as of the date of this press release. The Company does not undertake any obligation to update any forward-looking statement except as required under applicable laws.

 

 

Cision View original content:https://www.prnewswire.com/news-releases/wimi-researches-reinforcement-learning-based-blockchain-federated-learning-framework-to-optimize-model-aggregation-strategy-and-security-302300038.html

SOURCE WiMi Hologram Cloud Inc.

FAQ

What is WiMi's (WIMI) latest research initiative announced in November 2024?

WiMi announced research into integrating Reinforcement Learning (RL) with blockchain-based federated learning frameworks to optimize model aggregation strategies and enhance security.

What are the key applications of WiMi's (WIMI) new blockchain federated learning framework?

The framework can be applied in healthcare for secure data sharing among hospitals, financial services for risk management models, and IoT for enabling intelligent device collaboration.

How does Reinforcement Learning improve WiMi's (WIMI) federated learning framework?

RL improves the framework by dynamically adjusting model aggregation timing, selecting data participants, and optimizing transaction costs to balance information timeliness and data bias.

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