WiMi Announced a Federated Learning Framework Based on Layered and Sharded Blockchain Technology
WiMi Hologram Cloud Inc. (NASDAQ: WIMI) has announced a new federated learning framework based on layered and sharded blockchain technology. This framework aims to address key issues in federated learning, including information interaction, data security, privacy protection, computational efficiency, and system scalability.
The framework divides the IoT network into a multi-layer structure with multiple shards, optimizing information processing efficiency. It uses an adaptive consensus algorithm to identify and reject abnormal models, ensuring accuracy and reliability. The system employs encryption and distributed ledger technology to enhance data security and privacy.
WiMi's framework improves computational efficiency through sharding and parallel processing, making it suitable for real-time learning scenarios in large-scale IoT devices. The flexible design allows for seamless adaptation to various network environments, from small LANs to global scale deployments.
WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ha annunciato un nuovo framework di apprendimento federato basato su tecnologia blockchain stratificata e suddivisa. Questo framework mira a risolvere questioni chiave nell'apprendimento federato, inclusi l'interazione delle informazioni, la sicurezza dei dati, la protezione della privacy, l'efficienza computazionale e la scalabilità del sistema.
Il framework suddivide la rete IoT in una struttura multilivello con più shard, ottimizzando l'efficienza del trattamento delle informazioni. Utilizza un algoritmo di consenso adattivo per identificare e rifiutare modelli anomali, garantendo accuratezza e affidabilità. Il sistema impiega tecnologie di crittografia e registri distribuiti per migliorare la sicurezza dei dati e la privacy.
Il framework di WiMi migliora l'efficienza computazionale tramite sharding e elaborazione parallela, rendendolo adatto a scenari di apprendimento in tempo reale in dispositivi IoT su larga scala. Il design flessibile consente un'adattamento senza soluzione di continuità a vari ambienti di rete, da piccole LAN a implementazioni su scala globale.
WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ha anunciado un nuevo marco de aprendizaje federado basado en tecnología de blockchain en capas y fragmentada. Este marco tiene como objetivo abordar cuestiones clave en el aprendizaje federado, incluyendo la interacción de información, la seguridad de datos, la protección de la privacidad, la eficiencia computacional y la escalabilidad del sistema.
El marco divide la red IoT en una estructura de múltiples capas con múltiples fragmentos, optimizando la eficiencia del procesamiento de información. Utiliza un algoritmo de consenso adaptativo para identificar y rechazar modelos anómalos, asegurando precisión y fiabilidad. El sistema emplea tecnología de cifrado y libro mayor distribuido para mejorar la seguridad de los datos y la privacidad.
El marco de WiMi mejora la eficiencia computacional a través de la fragmentación y el procesamiento paralelo, lo que lo hace adecuado para escenarios de aprendizaje en tiempo real en dispositivos IoT a gran escala. El diseño flexible permite una adaptación sin problemas a diversos entornos de red, desde pequeñas LAN hasta implementaciones a escala global.
WiMi Hologram Cloud Inc. (NASDAQ: WIMI)는 층별 및 분할 블록체인 기술에 기반한 새로운 연합 학습 프레임워크를 발표했습니다. 이 프레임워크는 정보 상호작용, 데이터 보안, 개인 정보 보호, 컴퓨터 효율성 및 시스템 확장성을 포함한 연합 학습의 주요 문제를 해결하는 것을 목표로 합니다.
이 프레임워크는 IoT 네트워크를 여러 샤드가 있는 다층 구조로 나누어 정보 처리 효율성을 최적화합니다. 적응형 합의 알고리즘을 사용하여 비정상 모델을 확인하고 거부하여 정확성과 신뢰성을 보장합니다. 시스템은 데이터 보안과 개인 정보를 강화하기 위해 암호화 및 분산 원장 기술을 사용합니다.
WiMi의 프레임워크는 샤딩 및 병렬 처리를 통해 컴퓨팅 효율성을 개선하여 대규모 IoT 장치에서 실시간 학습 시나리오에 적합합니다. 유연한 설계를 통해 작은 LAN에서 글로벌 규모의 배포에 이르기까지 다양한 네트워크 환경에 원활하게 적응할 수 있습니다.
WiMi Hologram Cloud Inc. (NASDAQ: WIMI) a annoncé un nouveau cadre d'apprentissage fédéré basé sur une technologie blockchain en couches et fragmentée. Ce cadre vise à résoudre des problèmes clés dans l'apprentissage fédéré, notamment l'interaction des informations, la sécurité des données, la protection de la vie privée, l'efficacité computationnelle et l'évolutivité du système.
Le cadre divise le réseau IoT en une structure multi-couches avec plusieurs fragments, optimisant ainsi l'efficacité du traitement de l'information. Il utilise un algorithme de consensus adaptatif pour identifier et rejeter des modèles anormaux, garantissant ainsi précision et fiabilité. Le système utilise des technologies de cryptage et de registre distribué pour améliorer la sécurité des données et la vie privée.
Le cadre de WiMi améliore l'efficacité computationnelle grâce au sharding et au traitement parallèle, ce qui le rend adapté aux scénarios d'apprentissage en temps réel dans des dispositifs IoT à grande échelle. La conception flexible permet une adaptation sans couture à divers environnements de réseau, des petites LAN jusqu'aux déploiements à l'échelle mondiale.
WiMi Hologram Cloud Inc. (NASDAQ: WIMI) hat ein neues föderiertes Lernframework basierend auf geschichteter und shard-basierter Blockchain-Technologie angekündigt. Dieses Framework zielt darauf ab, wichtige Probleme im föderierten Lernen anzugehen, einschließlich Informationsinteraktion, Datensicherheit, Datenschutz, Rechenleistung und Systemskalierbarkeit.
Das Framework unterteilt das IoT-Netzwerk in eine mehrschichtige Struktur mit mehreren Shards und optimiert die Effizienz der Informationsverarbeitung. Es verwendet einen adaptiven Konsensalgorithmus, um anomale Modelle zu identifizieren und abzulehnen, was Genauigkeit und Zuverlässigkeit gewährleistet. Das System nutzt Verschlüsselung und verteilte Hauptbuchtechnologien, um die Datensicherheit und den Datenschutz zu verbessern.
Das Framework von WiMi verbessert die Recheneffizienz durch Sharding und parallele Verarbeitung, sodass es sich für Echtzeitszenarien in groß angelegten IoT-Geräten eignet. Das flexible Design ermöglicht eine nahtlose Anpassung an verschiedene Netzwerkumgebungen, von kleinen LANs bis hin zu globalen Bereitstellungen.
- Developed a new federated learning framework addressing key issues in the field
- Improved computational efficiency and reduced latency through sharding and parallel processing
- Enhanced data security and privacy protection using encryption and distributed ledger technology
- Increased system scalability and adaptability to various network environments
- None.
In the federated learning framework based on layered and sharded blockchain technology, the IoT network is finely divided into a multi-layer structure, and each layer is subdivided into multiple shards, aiming to optimize the information interaction and processing efficiency. The strategy of multiple layers and multiple shards enables the communication between nodes to be restricted to the same shard, which significantly reduces the complexity of information interaction and greatly reduces the global communication cost. And the sharding mechanism ensures that each shard can execute local training tasks independently and in parallel, accelerating the overall learning process. At the same time, cross-shard data exchange is performed only when the model parameters are updated, which not only ensures the training efficiency, but also further strengthens the data security and privacy protection.
In response to the abnormal or malicious behavior that may occur in federated learning, WiMi has developed a highly adaptive consensus algorithm. The algorithm is able to accurately identify and reject abnormal models, effectively resist interference caused by malicious or erroneous data, and ensure the accuracy and reliability of learning results. The application of blockchain technology records the transaction details of every model update, provides an untampered audit log, enhances system transparency, and establishes a foundation of trust among participants.
With the help of encryption and distributed ledger technology, WiMi's federated learning framework ensures the security of data during transmission and storage, effectively guarding against data leakage and tampering. Distributed ledger uses cryptographic techniques to protect the security and integrity of data, such as hash functions, public and private key encryption, and other techniques. These techniques prevent problems such as data tampering, forgery, and theft. In addition, data privacy can be further protected by restricting user access to data through smart contracts or other permission control mechanisms.
The sharding and parallel processing mechanism greatly improves computational efficiency and reduces latency, which is particularly suitable for real-time learning scenarios of large-scale IoT devices. The flexible layering and sharding design enables the system to seamlessly adapt to all kinds of network environments from small LANs to global scale. This design not only improves the scalability of the system, but also enables it to be flexibly deployed and operated in different network environments to meet diverse needs.
The federated learning framework builds an efficient, secure, and scalable IoT learning platform through layered and sharded technologies, adaptive consensus algorithms, encryption and distributed ledger technologies, and flexible computing architectures, laying a solid foundation for future large-scale machine learning applications. The federated learning framework based on layered and sharded blockchain not only overcomes the limitations of traditional federated learning, but also creates a brand-new path to safer and more efficient data collaboration, which is a profound insight and layout for future smart life. Whether it is smart home, smart city, or Industry 4.0, federated learning technology based on layered and sharded blockchain shows broad application prospects, and is expected to promote the digital transformation of all industries, and build a smarter, safer, and more efficient future society. In the era of the Internet of Everything, WiMi will also continue to explore and practice, leading the way to a new era of smarter, safer and more efficient data collaboration.
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.
View original content:https://www.prnewswire.com/news-releases/wimi-announced-a-federated-learning-framework-based-on-layered-and-sharded-blockchain-technology-302274111.html
SOURCE WiMi Hologram Cloud Inc.
FAQ
What is the main feature of WiMi's new federated learning framework?
How does WiMi's framework enhance data security in federated learning?
What is the impact of WiMi's (WIMI) new framework on computational efficiency?
How does WiMi's federated learning framework address system scalability?
