Generative AI Industry Market Operation Analysis: AI 'Content Production' to Reach Explosive Singularity by 2026
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Generative AI is a technology capable of autonomously creating new content or products, such as text, images, audio, and video. This technology relies on advancements in machine learning and natural language processing, enabling AI systems to understand and mimic human creative processes, thereby producing entirely new and valuable content. The emergence of generative AI has significantly propelled the application of AI technology in fields like content creation, design, and art.
With continuous technological advancements and the expansion of application scenarios, the market size of generative AI continues to grow. According to market research institutions, the generative AI market is expected to experience explosive growth in the coming years, becoming a key driver of the global AI industry.
Generative AI Industry Market Operation Analysis
Generative AI relies on technological progress in fields like deep learning and natural language processing, which provide robust technical support for its development.
As generative AI technology continues to evolve, its application scenarios are broadening, including content creation, design, art, gaming, and more. The demand in these fields offers vast market opportunities for generative AI.
Generative AI requires large amounts of data to train models, making data security and privacy protection critical issues. In the future, generative AI will integrate and innovate with other technologies, such as combining with blockchain technology to achieve content copyright protection, and with virtual reality technology to enable immersive content creation. Beyond existing fields like content creation, design, and art, generative AI will expand into more areas, such as healthcare, education, and manufacturing.
As consumer demand for personalized and customized content continues to grow, generative AI will gradually become a key tool to meet these needs. In summary, the generative AI industry will maintain rapid development in the future.
Generative AI Industry Prospects Research
Generative AI is a major technological innovation of our time, poised to spawn new industries, models, and drivers of growth, serving as a core element in developing new productive forces. It should be planned and developed with a global perspective, striving to position at the forefront of the AI era and making greater contributions to realizing the dream of a technologically strong nation and the great rejuvenation of the nation.
Currently, generative AI is in its early stages of development, with large model enhancement technologies like Retrieval-Augmented Generation (RAG) and precision algorithm enhancements still having significant room for growth.
For example, the recently highlighted text-to-video application Sora illustrates that while the Sora system can output corresponding videos based on input prompts, it currently cannot accurately simulate the physical properties of complex scenes or understand the causal relationships between entities. For example, in a juice-spilling video generated by Sora, entities have two stable states: one with the cup standing upright and another with the juice already spilled. However, the most complex physical state—the process of juice flowing out of the cup—was not generated.
Lu Yanxia, Research Director at IDC China, believes that currently viable or profitable models include office scenarios such as meeting transcription, meeting summaries, and digital avatars. The revenue growth of generative AI will be reflected in the subscription fees for collaborative office software and meeting software.
In industries like gaming, entertainment, and live streaming, text-to-image tools for assisting art design are expected to be implemented quickly. Lu Yanxia attributes this to the fact that such applications do not have strict standards for AI-generated results and allow for some flexibility.
Additionally, intelligent customer service and digital employees will also benefit.
Generative AI is an artificial intelligence technology that uses machine learning models and deep learning techniques to create new content—such as text, images, audio, or video—by analyzing patterns in historical data.
Unlike systems that generate output based on predefined rules or data, generative AI autonomously produces entirely new content, akin to human creativity. For instance, the widely discussed chatbot ChatGPT, which employs the core GPT-3 model, can generate high-quality natural language text for applications like chatting, writing, and automated customer service.
Generative AI Industry Market Opportunities Generative AI is driving the mobile industry towards full-scale intelligence. IDC predicts that AI smartphone shipments will reach 170 million units in 2024, accounting for 15% of global smartphone shipments. The next generation of AI phones will feature more powerful storage, display, and imaging capabilities, collaborating with AIGC applications to generate hundreds of billions of GB of content, offering operators new growth opportunities.
Li Peng, Senior Vice President of Huawei and President of ICT Sales and Service, stated that the intelligent content production methods represented by AIGC, new connection objects and scenarios such as digital humans and smart vehicles, and the new "storage-computing" model of cloud-edge-device collaboration will generate hundreds of billions of GB of AIGC content, unleashing trillions of GB of traffic dividends. Huawei forecasts that by 2026, AI will produce over 250 billion high-quality images and more than 70 million short videos, marking the singularity of a "content production" explosion.
"Intelligence enables a leap in content production efficiency, stimulates exponential growth in network traffic, and reconstructs information flow; diverse content fosters multi-dimensional experiences, driving multi-metric monetization and reconstructing value flow; connectivity breaks through the constraints of time and space, supporting the acquisition of new value and reconstructing the space-time flow," Li Peng noted, emphasizing that this accelerates society's transition into the intelligent era.