On the hardware foundation of a 300% increase in AI chip computing power, 2025 has seen an explosive deployment of domain-specific large models. According to the latest industry research, leading enterprises have broken through the performance ceiling of general-purpose models by building proprietary training datasets for niche scenarios. Take legal translation as an example: NetEase Youdao’s dedicated inference cluster enables its large model 2.0 to achieve military-grade precision in complex tasks such as clause analysis. This “domain-specific computing power” configuration model is now creating a demonstration effect in high-end service markets like healthcare and finance.
The search engine sector is undergoing a revolutionary overhaul of its underlying architecture. Traditional keyword-matching retrieval technologies are gradually being replaced by “intent understanding engines.” Weibo Smart Search, leveraging real-time data streams and a hundred-billion-parameter model, has achieved dual breakthroughs in response speed and result accuracy. Notably, these new search services consume five to seven times the computing power of traditional models, forcing companies to accelerate the construction of dedicated AI data centers.
The evolution of the browser ecosystem is even more disruptive. Products like Quark, by integrating multimodal large models, have transformed into composite AI workstations covering office, creation, and analysis tasks. Behind this is the collaborative innovation of edge computing chips and cloud computing power—local NPUs handle real-time tasks while complex computations are offloaded to cloud GPU clusters. This “end-cloud integrated” infrastructure layout has enabled browsers to exceed tens of billions of daily AI service calls.