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I. Industry Development
\[RUNTO Technology: China's Smart Glasses Market Sales Reached 1.454 Million Units in 2025\]
Recently, data agency RUNTO Technology released a report on domestic smart glasses sales. The data indicates that in 2025, the sales volume of smart glasses in China reached 1.454 million units, a year-on-year increase of 211%.
Based on product form and function, RUNTO Technology pointed out that AR glasses and audio glasses saw year-on-year sales increases of 83% and 135% respectively, while photography glasses achieved a breakthrough from zero to 500,000 units.
\[Google (GOOG) Officially Releases AR Glasses Prototype\]
The MWC 2026 conference is currently underway. As an exhibitor, Google showcased its latest Galaxy XR headset and AR glasses prototype in the Android XR exhibition area, allowing users to experience these products on-site.
\[Meta Launches FrameSync, Enhancing VR Experience Smoothness\] Meta recently announced a new feature for Meta Quest aimed at improving user comfort in VR, but its implementation requires developer involvement.
This new framework, FrameSync, aims to eliminate or mitigate unstable frame rate timings in VR games and applications, smoothing frame rate output and reducing the likelihood of motion sickness.
According to the official Meta blog, FrameSync is a completely new backend system that will replace three existing technologies: adaptive frame timing, fixed latency, and AppSW half-rate.
\[Alibaba's QA1 AI Glasses Make Their Debut at MWC\] The Mobile World Congress 2026 (MWC 2026) recently opened in Barcelona, Spain, showcasing cutting-edge smart terminals such as AI phones, robots, and XR, with global manufacturers vying to exhibit new products and showcase their technologies.
On the opening day, Alibaba's Qianwen officially announced its first AI hardware product—the Qianwen AI Glasses—marking the transition of Qianwen from a mobile app to a physical hardware product. This is a significant milestone in Alibaba's comprehensive implementation of its integrated software and hardware AI strategy.
Furthermore, it's worth noting that the Qianwen AI Glasses are planned for overseas market launch later this year, establishing a global presence. This showcase at MWC serves as a crucial prelude to its international expansion.
\[Qualcomm (QCOM) to Commercialize 6G in 2029, Collaborating with Global Partners to Promote Technology Deployment\] During MWC 2026, Qualcomm's CFO and COO, Akash Palkhiwala, delivered a keynote speech titled "Unlocking the AI-Native Future with 6G," systematically sharing Qualcomm's core vision, architectural design, and commercial deployment plans for 6G technology.
Akash stated that 6G, a once-in-a-decade major architectural upgrade in mobile communications, will become the first native AI network. It will reconstruct the wireless network system through three core pillars: connectivity, computing, and sensing. Qualcomm is working with global industry partners to accelerate technology development, planning to launch pre-commercial 6G terminals in 2028 and achieve commercial deployment of 6G in 2029.
II. Market Dynamics
\[Samsung (SSNGY) Smart Glasses Details Revealed! Camera at Eye Level, Three-Way Collaboration Coming\]
On March 7th, Samsung, in an interview with CNBC, revealed key details of its smart glasses. According to the report, the device will place a camera at eye level and heavily rely on a smartphone to process the visual information captured by the camera; therefore, most computational tasks will not be performed on the glasses themselves.
This solution enables contextual prompts, object recognition, and real-time AI suggestions. Because the camera is at eye level, the system can see what the user is doing and transmit the data to the phone for analysis.
Meanwhile, this smart glasses will adopt a three-way collaboration model, with Qualcomm providing the chips, Google providing the system platform, and the three companies jointly developing the chips, hardware, and Android XR mixed reality platform.
\[WiMi (WIMI) Quantum Entanglement Enables a New Paradigm for Non-Classical Feature Processing and Dimensionality Reduction\]
Against the backdrop of the accelerated convergence of artificial intelligence and quantum computing, two cutting-edge technologies, traditional deep learning models are gradually showing bottlenecks in terms of computational cost, model scalability, and theoretical interpretability. Especially in high-dimensional data processing tasks such as image recognition, while classical convolutional neural networks have achieved widespread success, their dependence on large-scale parameters, deep structures, and high-performance computing power poses challenges in resource-constrained scenarios and next-generation computing architectures.
Based on this reality, the WiMi R&D team recently released a core technology of hybrid quantum convolutional neural networks (QCNN), proposing and implementing a quantum kernel convolution (QKC) scheme that can run on current noisy medium-scale quantum (NISQ) devices, providing a practical engineering path for quantum-enhanced image classification models.
WiMi points out that classical convolutional layers essentially rely on sliding windows and linear weighted summation to extract local features. Quantum computing, however, inherently possesses the ability to represent high-dimensional Hilbert spaces and exhibits quantum parallelism. If local image patches can be mapped to quantum states, and feature mixing is achieved through controlled entanglement evolution, it may be possible to achieve equivalent or even more expressive feature extraction mechanisms at a lower parameter scale.
Based on this concept, the WiMi team proposed a modular quantum kernel convolution design method. This method preprocesses and blocks the input image in a classical manner, mapping each local image patch to a parameterized quantum state of a set of qubits. The mapping process employs a combination of angle encoding and amplitude encoding, controlling the quantum circuit depth while ensuring information fidelity, making the encoding process adaptable to the current limitations of gate depth and coherence time in quantum hardware.
After the convolution operation, this hybrid QCNN architecture introduces an entanglement-based quantum pooling mechanism for feature dimensionality reduction. Unlike max pooling or average pooling, common in classical pooling operations, quantum pooling does not directly compare or average numerical values. Instead, it compresses information from a multi-qubit system onto fewer qubits through controlled measurement and entangled state selection.
Furthermore, through analysis of intermediate quantum states and measurement results, WiMi validated the effectiveness of entanglement-based quantum pooling mechanisms in dimensionality reduction. Experiments show that quantum pooling not only compresses feature dimensions but also retains discriminative information crucial for classification tasks. This discovery provides a new entry point for the interpretability research of quantum neural networks and lays the foundation for future expansion onto more complex datasets and tasks.
This hybrid quantum convolutional neural network technology is not an isolated algorithmic innovation but an important step towards WiMi's long-term strategic goal of enabling quantum-enhanced artificial intelligence. By emphasizing low depth, modularity, and high compatibility with existing AI systems, this technology provides a realistic path for quantum computing to move from the laboratory to practical applications. Future research will further explore the application potential of this architecture in higher-resolution images, multi-channel data, and other sensory tasks, and continuously optimize circuit design in conjunction with the development of quantum hardware.
\[OpenAI Releases New Model Late at Night! Illusion Rate Drops by 29%!\] On March 4th, OpenAI officially released GPT 5.3 Instant, which shows improvements in tone of voice, relevance of responses, and fluency of dialogue.
The OpenAI team stated that they received user feedback that GPT 5.2 Instant sometimes refused to answer questions that could have been answered safely. When dealing with sensitive topics, the model's performance occasionally appeared overly conservative or didactic.
Furthermore, GPT 5.3 Instant optimizes the integration quality of online search results. The model can now more effectively balance search results with its own knowledge base and logical reasoning. For example, it can utilize existing cognitive graphs to provide in-depth background analysis of recent information, rather than simply listing and summarizing search information.
\[Huawei AI Glasses Rumored to Launch in April\] Recently, an insider posted on Weibo that Huawei's AI glasses will be launched in April this year. These glasses come in three color options: shimmering silver, titanium gray, and modern black. They feature a lightweight design and three built-in lithium batteries to ensure long battery life.
Functionally, they support taking photos, recording videos, playing audio, and real-time simultaneous interpretation. Leveraging the HarmonyOS system, they enable seamless cross-device collaboration and expand application possibilities across multiple scenarios. As an AI-powered product, they integrate Huawei's intelligent assistant, Xiaoyi, and, in conjunction with the camera, can achieve intelligent interactive functions such as AI object recognition.