WiMi Researches a Quantum Machine Learning Framework for Enhanced Privacy Protection
WiMi Hologram Cloud (NASDAQ: WIMI) announced the development of a hybrid quantum-classical model aimed at enhancing privacy protection in machine learning applications. The model combines quantum computing acceleration capabilities with classical computer stability, utilizing differential privacy optimization algorithms.
The framework features a quantum layer for feature extraction and complex transformations, while the classical layer implements differential privacy protection through techniques like Laplace or Gaussian noise. The model is currently being tested through simulation on classical computers due to current quantum hardware limitations.
This innovative approach aims to strengthen privacy protection in sensitive data applications while maintaining model performance, particularly targeting future applications in medical data analysis and financial risk assessment.
WiMi Hologram Cloud (NASDAQ: WIMI) ha annunciato lo sviluppo di un modello ibrido quantistico-classico volto a migliorare la protezione della privacy nelle applicazioni di apprendimento automatico. Il modello combina la velocizzazione tramite calcolo quantistico con la stabilità dei computer classici, utilizzando algoritmi di ottimizzazione della privacy differenziale.
Il framework prevede uno strato quantistico per l'estrazione delle feature e trasformazioni complesse, mentre lo strato classico implementa la protezione della privacy differenziale tramite tecniche come il rumore di Laplace o Gaussiano. Attualmente il modello è in fase di test tramite simulazione su computer classici a causa delle attuali limitazioni dell'hardware quantistico.
Questo approccio innovativo mira a rafforzare la protezione della privacy in applicazioni di dati sensibili mantenendo al contempo la performance del modello, con particolare riferimento a future applicazioni in analisi di dati medici e valutazione del rischio finanziario.
WiMi Hologram Cloud ( NASDAQ: WIMI) anunció el desarrollo de un modelo híbrido cuántico-clásico orientado a mejorar la protección de la privacidad en aplicaciones de aprendizaje automático. El modelo combina la aceleración de la computación cuántica con la estabilidad de los ordenadores clásicos, utilizando algoritmos de optimización de privacidad diferencial.
El marco presenta una capa cuántica para la extracción de características y transformaciones complejas, mientras que la capa clásica implementa la protección de privacidad diferencial mediante técnicas como ruido de Laplace o Gaussiano. El modelo se está probando actualmente mediante simulación en ordenadores clásicos debido a las limitaciones actuales de los hardware cuánticos.
Este enfoque innovador busca fortalecer la protección de la privacidad en aplicaciones de datos sensibles sin comprometer el rendimiento del modelo, apuntando especialmente a futuras aplicaciones en análisis de datos médicos y evaluación de riesgos financieros.
WiMi Hologram Cloud (나스닥: WIMI)는 기계 학습 응용에서 개인 정보 보호를 강화하기 위한 하이브리드 양자-고전 모델의 개발을 발표했습니다. 이 모델은 양자 컴퓨팅 가속 기능과 고전 컴퓨터의 안정성을 결합하고 차등 프라이버시 최적화 알고리즘을 활용합니다.
프레임워크는 특징 추출과 복잡한 변환을 위한 양자 계층을 특징으로 하며, 반면에 고전 계층은 Laplace 또는 Gaussian 노이즈와 같은 기법으로 차등 프라이버시 보호를 구현합니다.
현재 양자 하드웨어의 한계로 인해 고전 컴퓨터에서의 시뮬레이션을 통해 모델이 테스트 중입니다.
이 혁신적 접근법은 모델의 성능을 유지하면서 민감한 데이터 응용에서 프라이버시 보호를 강화하는 것을 목표로 하며, 특히 의료 데이터 분석 및 재무 위험 평가와 같은 향후 응용을 지향합니다.
WiMi Hologram Cloud (NASDAQ: WIMI) a annoncé le développement d'un modèle hybride quantique-classique visant à renforcer la protection de la vie privée dans les applications d'apprentissage automatique. Le modèle combine les capacités d'accélération du calcul quantique avec la stabilité des ordinateurs classiques, en utilisant des algorithmes d'optimisation de la confidentialité différentielle.
Le cadre comporte une couche quantique pour l'extraction de caractéristiques et des transformations complexes, tandis que la couche classique met en œuvre la protection de la confidentialité différentielle par des techniques telles que le bruit de Laplace ou Gaussien.
Le modèle est actuellement testé via des simulations sur des ordinateurs classiques en raison des limitations actuelles du matériel quantique.
Cette approche innovante vise à renforcer la protection de la vie privée dans les applications de données sensibles tout en préservant la performance du modèle, en particulier en visant des applications futures dans l'analyse de données médicales et l'évaluation du risque financier.
WiMi Hologram Cloud (NASDAQ: WIMI) kündigte die Entwicklung eines hybriden Quanten-Klassik-Modells an, das darauf abzielt, den Datenschutz in Anwendungen des maschinellen Lernens zu verbessern. Das Modell kombiniert Beschleunigungsfähigkeiten der Quantenberechnung mit der Stabilität klassischer Computer und nutzt Algorithmen zur Optimierung der Differentialprivatsphäre.
Das Framework verfügt über eine quanten-Schicht zur Merkmalextraktion und zu komplexen Transformationen, während die klassische Schicht den Schutz der Differentialprivatsphäre durch Techniken wie Laplace- oder Gaußsche Rauschen implementiert.
Das Modell wird derzeit aufgrund der Einschränkungen der Quantenhardware durch Simulationen auf klassischen Computern getestet.
Dieser innovative Ansatz zielt darauf ab, den Datenschutz in Anwendungen mit sensiblen Daten zu stärken, während die Modellleistung erhalten bleibt, insbesondere mit Blick auf zukünftige Anwendungen in medizinischer Datenanalyse und finanzieller Risikobewertung.
أعلنت WiMi Hologram Cloud (بورصة ناسداك: WIMI) عن تطوير نموذج هجين كوانتومي-كلاسيكي يهدف إلى تعزيز حماية الخصوصية في تطبيقات التعلم الآلي. يجمع قدرات تسريع الحوسبة الكوانتية مع استقرار الحواسيب الكلاسيكية، باستخدام خوارزميات تحسين خصوصية تفاضلية.
الإطار يحتوي على طبقة كوانتية لاستخراج الميزات والتحولات المعقدة، بينما تطبق الطبقة الكلاسيكية حماية الخصوصية التفاضلية من خلال تقنيات مثل ضوضاء لابلاس أو Gaussiane (جاوسية).
يتم حالياً اختبار النموذج عبر المحاكاة على أجهزة كلاسيكية بسبب قيود الأجهزة الكوانتية الحالية.
يهدف هذا النهج المبتكر إلى تعزيز حماية الخصوصية في تطبيقات البيانات الحساسة مع الحفاظ على أداء النموذج، مع التركيز بشكل خاص على التطبيقات المستقبلية في تحليل بيانات طبية وتقييم المخاطر المالية.
WiMi Hologram Cloud（纳斯达克股票代码：WIMI）宣布开发一种混合量子-经典模型，旨在提升机器学习应用中的隐私保护。该模型将 量子计算加速能力与经典计算的稳定性 相结合，利用差分隐私优化算法。
该框架具有用于特征提取和复杂变换的 量子层，而 经典层通过 Laplace 或高斯噪声等技术实现差分隐私保护。由于当前量子硬件的限制，该模型目前通过在经典计算机上的仿真进行测试。
这一创新方法旨在在敏感数据应用中加强隐私保护，同时保持模型性能，尤其面向未来在 医疗数据分析和金融风险评估 的应用。
- Development of innovative hybrid quantum-classical model combining advanced technologies
- Enhanced privacy protection capabilities through differential privacy mechanisms
- Potential applications in high-value sectors like medical data and financial risk assessment
- Current testing limited to simulations due to quantum hardware constraints
- Technology still in research phase with no immediate commercialization timeline
The hybrid model uses a quantum layer to handle feature extraction and complex transformations, while the classical layer is responsible for implementing differential privacy protection and making final decisions. The quantum layer leverages the superposition and entanglement properties of quantum bits to achieve efficient data encoding and information extraction. The classical layer, on the other hand, uses established differential privacy techniques by adding appropriate noise to obscure the impact of individual data points. Based on the output from the quantum layer, the classical layer applies differential privacy mechanisms such as Laplace noise or Gaussian noise to ensure that the model's sensitivity to individual data changes remains below a predefined threshold. At the same time, by adjusting the noise level and model complexity, the model seeks the optimal balance between privacy protection and model accuracy. Due to the limitations of current quantum hardware, the model is initially tested through simulation on classical computers to verify the effectiveness of the differential privacy mechanism and assess its impact on model performance.
The hybrid quantum-classical model developed by WiMi strengthens privacy protection and effectively prevents the leakage of sensitive information. The introduction of differential privacy protection technology increases the model's tolerance to noise and data perturbations, helping to improve its generalization ability and opening new pathways for the practical application of quantum computing.
In the future, with advancements in quantum technology and the deepening of differential privacy quantum machine learning theory, we anticipate the emergence of more innovative applications in fields such as medical data analysis and financial risk assessment. Quantum machine learning will usher in a new era of data science, protecting privacy while unlocking new possibilities.
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.
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SOURCE WiMi Hologram Cloud Inc.
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