信通院-2018世界人工智能产业发展蓝皮书（英文版）-2018.9-80页-3mb

2018 World AI Industry Development Blue Book Summary

Core Content

The 2018 World AI Industry Development Blue Book is a comprehensive report on the global AI industry, published by the China Academy of Information and Communications Technology (CAICT) and featuring research from Gartner. It provides an in-depth analysis of the current state of AI technology, industry trends, and key players worldwide, offering guidance for AI development and industrial application. The report is organized into five main sections: Industrial Development Environment, Technical Environment, World AI Enterprises, World Investment and Financing, and Industrial Developments.

Main Views

• The AI industry is in a new era of rapid growth and application, driven by technological innovation and supportive policies.
• The report emphasizes global collaboration and communication in AI, highlighting the importance of building "Chinese Solutions" and "Global Wisdom" to address common challenges.
• The development of AI algorithms has evolved from symbolic computing to neural networks and deep learning, with open-source frameworks playing a central role in accelerating innovation.
• Computing power is a critical factor in AI development, with the rise of GPU technology and specialized AI chips such as TPU and Tesla V100 enabling significant performance improvements.
• Data is considered the cornerstone of AI development, providing the raw materials for training and improving AI systems.

Key Information

1. Industrial Development Environment

• The 2018 World AI Conference was held in Shanghai, organized by multiple Chinese government bodies and the Shanghai Municipal People's Government, with the goal of promoting AI integration with the real economy.
• The conference focused on globalization, sophistication, specialization, and marketization.
• The AI industry map was developed jointly by the Research Institute of Information and Industrialization and the Data Research Center of CAICT, covering industrial chain, distribution, research institutions, and policy.

2. Technical Environment

• AI algorithms have evolved significantly, from symbolic computing to neural networks and deep learning.
• Open-source deep learning frameworks such as TensorFlow, Caffe, PaddlePaddle, and Theano are widely used and have become a key driver of AI development.
• Computing power has improved rapidly, with the introduction of GPUs and the development of AI-specific chips (e.g., TPU, Tesla V100) leading to significant performance gains.
• The computing architecture is shifting from traditional CPU-centric systems to GPU-centric ones, optimized for AI applications.

3. World AI Enterprises

• The report covers the structure, scale, and regional distribution of global AI enterprises.
• AI enterprises are categorized based on technical level (algorithm, hardware, etc.) and product/solution level (application in specific industries).
• The AI industry map includes basic supporting layer, software algorithm layer, and industry application layer, with detailed descriptions of each layer's key players and technologies.

4. World Investment and Financing

• Investment data is sourced from platforms like CB Insights, IT Oranges, and Sprouts, and is based on the AI business directory.
• The report highlights the scale and distribution of global AI investments, offering insights into the growth and trends of the AI industry from a financial perspective.

5. Industrial Developments

• The report discusses the current state and future trends of AI technologies and applications, including industrial solutions and application cases of leading AI companies.
• It emphasizes the importance of technology integration, innovation, and application demonstration in building a strong AI industry.

Data Sources and Scope

• AI Enterprises: Data is sourced from the CAICT Data Research Center Monitoring Platform.
• Investment and Financing: Data from CB Insights, IT Oranges, and Sprouts.
• Patent Data: From the CAICT Intellectual Property Center, using PatSnap and other professional databases.
• Paper Data: From Web of Science, based on AI-related keywords.
• Industrial Application Data: From Qixin and major research institutions such as CAICT, PwC, MarketsandMarkets, and Grand View Research.
• Currency: All market data is presented in RMB, unless otherwise specified.

Conclusion

The 2018 World AI Industry Development Blue Book offers a detailed overview of the global AI landscape, focusing on technological development, policy frameworks, enterprise structures, and investment trends. It serves as a reference for AI practitioners and researchers, aiming to promote innovation, collaboration, and application in the AI field. The report underscores the importance of data, computing power, and open-source technologies in driving AI progress and highlights the strategic role of AI in shaping the future of industry and society.