Alibaba is moving into the smart glasses market with a device powered by its own AI models, part of a wider $52.4 billion furthering of AI and cloud computing. The Quark AI Glasses marks the company’s first step into the wearables category and is due to launch in China by the end of 2025.
The glasses will run on Alibaba’s Qwen large language model and its AI assistant, Quark. Quark is already available as an app in China, but this will be the first time the company is pairing it with hardware to reach more users.
The Hangzhou-based firm has been one of China’s more active AI developers, rolling out models designed to compete with systems from companies like OpenAI. By moving into smart glasses, it joins a growing group of tech players betting on wearables as the next major computing platform alongside smartphones.
Pushing into hardware
The Quark AI Glasses will enter a market that already includes Meta’s smart glasses made with Ray-Ban and a model launched this year by Xiaomi. Alibaba’s version will offer hands-free calling, music streaming, real-time translation, meeting transcription, and a built-in camera.
Alibaba operates a broad set of services in China and the glasses will connect to that ecosystem. Users will be able to access navigation, make payments through Alipay, compare prices on Taobao, and tap into other Alibaba-owned platforms like mapping and travel booking.
While the company has outlined some features, it has not revealed the price or detailed specifications.
The data behind the devices
Smart glasses like Alibaba’s depend on AI systems that can recognise images, interpret context, and respond in natural language. The abilities rely on huge amounts of labelled data – information that has been reviewed and tagged by humans so the AI can learn from it.
That process often involves “human-in-the-loop” (HITL) systems, where people provide input at key stages of training and testing. To understand how this works in practice, AI News spoke with Henry Chen, co-founder of Sapien, a company that manages large, distributed workforces for data labelling. Chen discussed common misunderstandings, the demand for skilled contributors, and how China’s AI growth is influencing the industry.
Misconceptions about HITL
One common belief is that HITL is simply data labelling. Chen said it’s more complex, involving decisions on edge cases, judgement calls, and ongoing evaluation. “Continuous feedback is what makes HITL work instead of one-off datasets,” he said.
Another misconception is that the work is low-skilled. Chen said the rise of industry-specific AI has created demand for domain experts like doctors, lawyers, and scientists to contribute their knowledge.
Sapien works with 1.8 million contributors in 110 countries. For complex tasks like contextual understanding or visual recognition, maintaining quality is critical. Chen said the company uses peer validation, contributor reputation tracking, and aligned incentives to ensure…
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