Current Development Status and Future Trends of Generative AI Industry
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Recently, the stunning debut of Sora has once again drawn public attention to the widespread application of artificial intelligence. With the extensive use of generative AI, it is estimated that by 2027, the entire AI industry will consume 85 to 134 terawatt-hours of electricity annually, highlighting the enormous demand for power resources driven by AI technology.
Current Development Status and Future Trends of Generative AI Industry
Generative AI, also known as AIGC (AI-Generated Content), is regarded as a significant milestone marking the transition of artificial intelligence from version 1.0 to 2.0. It holds vast application prospects in fields such as search engines, artistic creation, entertainment (films, music, and gaming), as well as finance, education, healthcare, and industrial sectors.
Since the end of last year, with the emergence of large models capable of reasoning, generative AI has broken free from rigid frameworks and is steadily advancing toward true intelligence. This development undoubtedly brings new opportunities and challenges to numerous industries.
Generative AI, or AIGC (Artificial Intelligence Generated Content), is a crucial indicator of the transition from the AI 1.0 era to the AI 2.0 era.
The convergence and accumulation of technologies such as GAN, CLIP, Transformer, Diffusion, pre-trained models, multimodal techniques, and generative algorithms have spurred the explosive growth of AIGC. Continuous algorithmic innovation, the qualitative leap in AIGC capabilities driven by pre-trained models, and the diversification of AIGC content through multimodal approaches have endowed AIGC with more versatile and robust foundational capabilities. Over 80% of data in human society consists of unstructured formats like images, audio, and video, which cannot be processed by computers as easily as text. Extracting value from this data has become a major direction in big data transformation. With the support of large AI models, text, images, and sound can now be tokenized into units suitable for AI training, shifting focus from countless permutations to fundamental building blocks. This approach maximizes the utility of existing data elements, ushering in a new era of unified data processing.
Since early this year, general artificial intelligence represented by cognitive models has sparked a global frenzy. International companies like OpenAI, Microsoft, and Google continue to invest heavily, while China has seen a "thousand-model war" with numerous tech firms racing to develop solutions. According to the "China AI Large Model Map Research Report" released by the Ministry of Science and Technology, China and the US lead significantly in released large models, accounting for over 80% of the global total.
Currently, the generative AI sector has produced 13 unicorn companies (valued at over $1 billion). Among the five new AI unicorns emerging in 2023, two are generative AI companies: Cohere and Runway.
These 13 generative AI companies achieved unicorn status in an average of just 3.6 years. In contrast, reaching unicorn status typically takes seven years - meaning the timeline has been nearly halved.
A recent McKinsey report titled "The Economic Potential of Generative AI: The Next Productivity Frontier" indicates that applying the 63 analyzed generative AI use cases across industries could add $2.6-$4.4 trillion annually to the global economy. This projection doesn't include all potential applications - if unstudied use cases are considered, the economic impact of generative AI could double. <span style="text-decoration:underline;">Generative AI Market Value Forecast</span>
Statista predicts that the annual growth rate will slow down in 2024, but the overall market value will still increase by 48.4%, reaching $66.6 billion. Double-digit growth will continue in the coming years, with generative AI reaching a value of $100 billion by 2026, a 65% increase in just two years. By 2030, this figure is expected to double, exceeding $207 billion.
In global comparisons, the United States will remain the world's largest generative AI market, with an expected value of $37.3 billion by 2026, a 60% increase from this year. As the second-largest market globally, China's market will further grow, with its valuation increasing by 72% over the next two years to reach $14.7 billion. Germany's generative AI market ranks third with a 60% growth rate, expected to reach a valuation of $4.5 billion by 2026.
In the foreseeable future, as demand for generative AI becomes deeper and broader, the need for computing power will also grow exponentially. This trend will also benefit the high-performance chip industry, greatly promoting the research, development, and sales of processors, computing cards, servers, and other related computing components.