Core Viewpoint - The demand for AI training and inference integrated machines is increasing as AI applications become more prevalent, with nearly a hundred manufacturers launching related products in the domestic market this year [1][2]. Market Demand and Trends - The sales of training and inference integrated machines have shown significant growth, with companies like Digital China and ZTE reporting strong market performance [2][7]. - The shift in demand from training to inference is driven by the lower barriers to entry for AI, particularly after the rise of DeepSeek, which has encouraged many small and medium enterprises to develop their own AI applications [2][3]. - The integrated machines are designed to support the entire process of large model training, inference, and application development, catering to the need for ready-to-use solutions [2][3]. Industry Applications - The integrated machines are being adopted across various sectors, including government, education, healthcare, and telecommunications, with ZTE reporting sales covering 15 industries [2][8]. - Specific applications include AI education platforms, medical diagnostic tools, and automotive design solutions, showcasing the versatility of these machines in different fields [7]. Future Market Outlook - The market for training and inference integrated machines is expected to grow significantly, with IDC predicting a 260% increase in the intelligent agent market by 2025 [4][5]. - The integration of AI capabilities into business processes is seen as essential for future development, with a focus on personalized solutions for various industries [5][6]. Challenges and Considerations - The deployment of integrated machines faces challenges related to the complexity of AI ecosystems and the need for deep integration of hardware and software [9][10]. - Companies are advised to enhance the scalability of integrated machines and incorporate cloud management systems to better support the development of AI models and applications [9][10].
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