Report Overview
The report "China AI Foundation Software Market Research Report (2023)" aims to clarify the basic concepts and classifications of AI foundation software frameworks. By reviewing industry development and the value chain, it explores core industry drivers, analyzes current market trends, and builds a vendor competitiveness framework across three dimensions: applications, products, and ecosystems. The report evaluates the core competitive advantages and combined barriers of mainstream players, provides an objective assessment of the AI foundation software framework development in the Chinese market, and offers reference recommendations and key insights for future industry development.
Future Focus: OpenAI and GPT Practices
AI 2.0 is formed by the integration of large-scale data, cloud computing, and artificial intelligence technologies. It represents a platform-scale opportunity that will provide deeper and broader solutions across industries. With the arrival of AI 2.0, foundation models no longer require manually labeled data to learn from massive text corpora, and models can be fine-tuned at low cost to adapt to domain-specific tasks.
Applications, Platforms, and Infrastructure
Applications, platforms, and infrastructure related to AI 2.0 will become focal points for industry and investment. As the key platforms for training, managing, and deploying large AI models, AI foundation software is positioned to evolve with AI 2.0 and generate significant industrial opportunities.
Key Challenges: Data, Technology, and Business Models
Data: The quality and scale of training data are critical to model iteration. Current issues such as limited internal-external data sharing, uneven data categories, and missing extreme-case data highlight the need for exploration in AIGC structured data synthesis.
Technology: The inference capability of generative AI models is increasingly important. There is also growing demand for model trustworthiness and explainability, driving requirements for improved performance in AutoML, deep learning, and causal learning within foundational software.
Business models: As large foundation models mature, a hybrid approach of general foundation models plus domain-specific small models will be adopted by more enterprises. Consequently, AI foundation software that supports enterprises in building their own AI models will become more prevalent.
Industry Value Chain
AI foundation software is mainly located in the midstream of the industry value chain. The chain comprises upstream infrastructure and resource providers, midstream AI foundation software platforms and one-stop AI development platforms, and downstream enterprise application sectors. The upstream layer provides the computational foundation and data support required for deploying AI software.
Upstream Compute and Acceleration
Advances in upstream compute acceleration empower the development of AI foundation software. As the industry upstream for AI foundation software, basic compute provides essential support in both compute power and data supply.
Competitive Landscape of AI Foundation Software Vendors
Jiuzhang Yunji, Amazon, Huawei Cloud, Alibaba Cloud, Tencent Cloud, Databricks, and Baidu Cloud were rated as "Leaders" in the Chinese market AI foundation software segment. These vendors adopt large models and cloud-native technologies to enhance application data security, technical compatibility, and development and deployment capabilities for AI foundation software.
DataRobot, SenseTime, 4Paradigm, Transwarp, and Chuangxin Qizhi were rated as "Challengers" in the Chinese market. These vendors focus on improving product application cost-effectiveness, differentiating from competitors, and offering more openness in AI technology to drive growth.
Baihai Technology was rated as an "Expert" in the Chinese market. Vendors in this category are niche specialists with potential for developing high-quality application products and technological innovation.
