Core Viewpoint - WiMi Hologram Cloud Inc. has developed a Quantum Computing-Based Feedforward Neural Network (QFNN) algorithm that addresses computational bottlenecks in traditional neural network training, utilizing Quantum Random Access Memory (QRAM) for efficient data processing [1][10]. Quantum Algorithm Development - The QFNN algorithm incorporates key quantum computing subroutines, particularly in the feedforward and backpropagation processes, providing exponential speedup in both stages of neural network training [2][4]. - Classical feedforward propagation, which involves multiple matrix-vector multiplications, is enhanced by the quantum algorithm through the use of quantum state superposition and coherence, allowing computations to be performed in logarithmic time [3][6]. Computational Efficiency - The quantum algorithm significantly reduces computational complexity, shifting from a dependency on the number of connections (O(M)) in classical networks to a dependency solely on the number of neurons (O(N)) in the quantum framework [6][7]. - This reduction in complexity leads to at least a quadratic speedup in training large-scale neural networks, making it particularly advantageous for ultra-large-scale datasets [7]. Overfitting Mitigation - WiMi's quantum algorithm demonstrates inherent resilience to overfitting, a common issue in deep learning, due to the intrinsic uncertainty of quantum computing, which acts similarly to regularization techniques [8][9]. Application Prospects - The QFNN algorithm has broad application potential in fields requiring high computational speed and data scale, such as financial market analysis, autonomous driving, biomedical research, and quantum computer vision [10][11]. - Additionally, the research lays the groundwork for quantum-inspired classical algorithms that can optimize computational complexity on traditional computers, providing a transitional solution until quantum computers become widely available [10]. Future Implications - The advancement of WiMi's QFNN algorithm marks a significant milestone in the intersection of quantum computing and machine learning, suggesting that quantum neural networks will play a crucial role in the future of artificial intelligence [11][12].

实习时间： 每周至少实习3天以上，实习时间不少于3个月，不满足的请勿投递，实习考核优秀者有留用机会。 岗位职责： 1、负责数据处理、分析、统计等工作，协助研究员完成量化投资相关课题的研究； 实习生招聘 工作地点： 深圳、广州、上海、北京 ，要求线下实习 简历投递截止日期： 2025年4月30日 2、协助进行金融工程策略模型的开发与跟踪等工作； 3、完成小组安排的其他工作。 基本要求： 1、数学、统计、物理、计算机、信息工程等理工科专业，或金融工程相关专业，硕士或博士在读，特别优秀的大四 保研亦可，非应届（2026年及之后毕业）； 2、熟练掌握Python等编程语言，熟悉SQL数据库，有优秀编程能力与编程规范； 3、有责任心，自我驱动能力强， 具有良好的信息搜集能力、逻辑思维能力、分析判断能力、言语和书面表达能力、 人际沟通能力。 加分项： 4、 具备扎实的金融市场基础知识，熟悉股票、债券、期货、指数及基金等核心概念； 5、数学基础好，有科研项目经历、有学术论文被SCI或EI收录； 6、熟悉Wind、 Bloomberg、天软等金融终端； 7、熟悉机器学习、深度学习，熟悉PyTorch、Linux，有GPU服务 ...

Core Insights - Nvidia's CEO Jensen Huang highlighted the company's commitment to autonomous vehicles during his keynote at GTC 2025, linking it to the historical impact of AlexNet on deep learning and computer vision [1][3][4] Automotive Industry Impact - The introduction of AlexNet in 2012, which achieved 84.7% accuracy in the ImageNET competition, inspired Nvidia to invest heavily in self-driving technology, marking over a decade of development in this area [2][3][4] - Nvidia has established partnerships with various automakers and tech companies, including a recent expanded collaboration with GM, to enhance the development of autonomous vehicles [4] - Major automotive companies such as Tesla, Wayve, and Waymo utilize Nvidia GPUs for their data centers, while others leverage Nvidia's Omniverse for creating digital twins of factories [5] Technology Utilization - Nvidia's Drive Orin system-on-chip, based on the Ampere architecture, is employed by companies like Mercedes, Volvo, and Toyota for their automated driving systems [5] - The safety-focused operating system, DriveOS, is also being adopted by Toyota and other manufacturers, further embedding Nvidia's technology in the automotive sector [5][6]

Core Insights - Gorilla Technology Group Inc. is focused on building smart cities and enhancing security through AI-powered solutions, emphasizing a consultative approach to meet customer needs [2][3]. Company Overview - Gorilla Technology Group Inc. is headquartered in London, UK, and operates as a global solution provider in Security Intelligence, Network Intelligence, Business Intelligence, and IoT technology [5]. - The company offers a range of solutions across various sectors, including Government & Public Services, Manufacturing, Telecom, Retail, Transportation & Logistics, Healthcare, and Education, utilizing AI and Deep Learning Technologies [5]. Technology and Solutions - The company specializes in urban operations, security enhancement, and resilience through AI-driven technologies such as intelligent video surveillance, facial recognition, license plate recognition, edge computing, post-event analytics, and advanced cybersecurity [6]. - By integrating these technologies, Gorilla aims to empower Smart Cities, improving efficiency, safety, and overall quality of life for residents [6].

As filed with the Securities and Exchange Commission on February 14, 2024. Registration No. 333-______ SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 FORM S-1 REGISTRATION STATEMENT UNDER THE SECURITIES ACT OF 1933 SS INNOVATIONS INTERNATIONAL, INC. (Exact name of registrant as specified in its charter) (State or other jurisdiction of incorporation or organization) Florida 3841 47-3478854 (Primary Standard Industrial Classification Code Number) (I.R.S. Employer Identification No.) 405, 3 Floor, i ...