How is the generative AI industry developing? Bill Gates: Generative AI has reached its limit, the next breakthrough is the development of explainable AI
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With the continuous growth in the supply and demand for digital content, generative artificial intelligence (AIGC) technology has been widely implemented this year, further integrating the digital economy with the real economy. AIGC has opened a new frontier in human technological vision. Nowadays, everyone is talking about AIGC, and enterprises are increasingly recognizing the importance of data. Large models have driven an exponential increase in computing power demand. How to effectively utilize large models and implement AIGC technology in real-world industries is a question many tech companies are actively exploring and practicing.
Bill Gates: Generative AI has reached its limit, the next breakthrough is explainable AI
Bill Gates recently stated in an interview with Germany's Handelsblatt that although many within OpenAI, including Sam Altman, believe GPT-5 will significantly outperform GPT-4, he thinks there are many reasons to believe that current generative AI has reached its limit.
Data shows that compared to the arms race in large models, Bill Gates is more optimistic about AI Agents. He once said that in the near future, any internet user could have an AI Agent. Agents will not only change how everyone interacts with computers but also disrupt the software industry, marking the biggest computing revolution since the shift from command inputs to clicking icons.
Generative artificial intelligence AIGC (Artificial Intelligence Generated Content) is a significant milestone marking the transition from AI 1.0 to AI 2.0.
The accumulation and integration of technologies such as GAN, CLIP, Transformer, Diffusion, pre-trained models, multimodal techniques, and generative algorithms have spurred the explosion of AIGC. Continuous iterative innovation in algorithms, 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 general and robust foundational capabilities.
From the progressive development of computational intelligence, perceptual intelligence, to cognitive intelligence, AIGC has opened the door to cognitive intelligence for human society. Through training on a single large-scale dataset, AI has acquired knowledge across multiple domains. With appropriate adjustments and refinements to the model, it can perform tasks in real-world scenarios.
AIGC holds milestone significance for human society and artificial intelligence. In the short term, AIGC has transformed fundamental productivity tools. In the medium term, it will alter societal production relations. In the long term, it will drive a qualitative breakthrough in overall societal productivity. In this transformation of productivity tools, production relations, and productivity, the value of data as a production factor is greatly amplified.
AIGC has elevated data as a core resource of the era, accelerating the digital transformation process of society to some extent.
How is the Generative AI Industry Developing?
Since the beginning of this year, general artificial intelligence, represented by cognitive large models, has sparked a global trend. International companies like OpenAI, Microsoft, and Google have been ramping up their investments, while domestically, a "thousand-model war" has erupted, with numerous high-tech enterprises competing in research and development. According to the "China Artificial Intelligence Large Model Map Research Report" released by the Ministry of Science and Technology, China and the United States lead the world in the number of large models released, accounting for over 80% of the global total.
At the same time, large models are seen as a new engine for corporate transformation. A recent McKinsey report, "The Economic Potential of Generative AI: The Next Wave of Productivity," indicates that applying the 63 analyzed generative AI technologies across various industries could add $2.6 trillion to $4.4 trillion annually to the global economy. This projection does not include all generative AI applications; if unstudied applications are factored in, the economic impact could double.
Specifically, industry players widely believe that the generative AI market is on the verge of explosive growth on the demand side, potentially forming two trillion-dollar markets for both consumer (C-end) and business (B-end) applications. The demand for generative AI is surging, and general-purpose models are poised to revolutionize the traditional AI market, with productivity gains significantly boosting industrial development.
From the progression of computational intelligence to perceptual intelligence and now cognitive intelligence, AIGC (AI-generated content) has opened the door to cognitive intelligence for human society. Through training on large-scale datasets, AI has acquired knowledge across multiple domains. With minor adjustments, these models can perform tasks in real-world scenarios.
Notably, the popularity of ChatGPT this year has triggered an AI entrepreneurship boom. Starting in March, the number of new AIGC job postings surged dramatically, driven by the large-model startup wave. Major tech companies and unicorns have entered the fray, competing for talent, leading to a nearly 200% increase in new AIGC job postings by April. By the second half of the year, the number of new AIGC job postings stabilized.
From January to August 2023, the average salary for new AIGC job postings showed an upward trend. By March 2023, the average monthly salary for new AIGC positions exceeded 50,000 yuan, reaching 52,472 yuan—an 11.6% increase from January's 47,015 yuan. Starting in June, the average monthly salary for new AIGC positions stabilized at around 60,000 yuan.