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AI加速上车,座舱端侧模型、智能驾驶系统都要求更多算力

Core Insights - The automotive industry is increasingly integrating AI technologies, with significant advancements in end-to-end models expected to process data volumes ten times greater than before [1][5] - Major companies like Tencent, Intel, and BMW are actively developing and showcasing AI capabilities in smart cockpit systems at the Shanghai International Auto Show [1][2] Group 1: AI Integration in Automotive - Tencent has launched an end-side model for smart cockpits, collaborating with various car manufacturers to enhance user experience through local inference and cloud support [1][2] - The integration of AI in smart cockpits allows for personalized user interactions, such as ordering coffee through voice commands, demonstrating the blend of social and entertainment ecosystems with automotive technology [2] Group 2: Technical Challenges and Requirements - The deployment of end-side models in vehicles requires sufficient computational power, with Qualcomm's 8295 chip being highlighted for its capability to support these models effectively [4] - There are concerns regarding the "AI hallucination" problem, where models may not always provide accurate predictions, necessitating improved training with industry-specific data [4] Group 3: Future Projections - The industry anticipates that modular end-to-end models will be mass-produced within the year, while unified models are expected to be ready by 2026 or 2027 [5] - The evolution of smart driving technology is compared to the progression of language models, indicating a shift from weak expert systems to strong expert systems, with future demands for increased computational power [5]