Current Development and Future Prospects of the Generative AI Large Model Industry
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The three-year pandemic has profoundly impacted the overall IT market environment, increasing instability among enterprise users in the public cloud market. Budget cuts and prolonged construction cycles among upstream enterprises have hindered the development of the public cloud market, leading to a steady decline in the growth of China's generative AI large model market.
The overall market size of China's public cloud services (IaaS/PaaS/SaaS) reached $18.84 billion, with the IaaS market growing by 15.7% year-on-year and the PaaS market by 31.8%. For the IaaS+PaaS market, the year-on-year growth in the second half of 2022 was 19.0%, a 23.9% drop compared to the 42.9% growth in the second half of 2021 and an 11.6% decline from the 30.6% growth in the first half of 2022, indicating a significant slowdown in growth.
This year, with the advancement of generative AI large model technology, autonomous driving has also begun to evolve toward end-to-end large model approaches.
It is reported that Tesla's FSD V12 has achieved an end-to-end AI autonomous driving solution. SenseTime has launched the "SenseNova Large Model" system, providing intelligent multimodal human-vehicle interaction experiences. Alibaba announced that its AliOS smart car operating system has integrated the Tongyi Qianwen large model for testing. Automakers like Dongfeng Nissan, Hongqi, and Great Wall have announced partnerships with Baidu's "ERNIE Bot"...
Chinese automakers are also applying AI large models to solve autonomous driving challenges, injecting vast amounts of data to grow models, optimize algorithms, and enhance vehicle intelligence.
2023 Generative AI Large Model Industry Development Status and Future Prospects Analysis
AI large model technology has begun to take root, accelerating the advancement of intelligent connected technology, which will further propel the development of smart connected vehicles. Over the past two years, many Chinese automakers have heavily invested in AI large models, achieving capabilities such as text generation, multimodal perception, and autonomous driving data generation, covering parameters in the tens or even hundreds of billions.
With the explosive popularity of generative AI large models like ChatGPT, GPT-4, and BARD, competition among cloud service providers around generative AI has intensified.
Domestic cloud service providers such as Baidu, Alibaba, JD.com, and 360 have also announced progress in AI large model technology and plans for ChatGPT-like projects.
In fact, in the wave sparked by ChatGPT, cloud computing plays a crucial role. For example, ChatGPT's model training requires massive data and computational resources, and cloud computing provides the technical foundation for model development and operation. This may explain why so many cloud providers worldwide are embracing generative AI large models.
Amazon Web Services has also launched a generative AI cloud hosting service called Amazon Bedrock, allowing users to access pre-trained foundational models from AI startups like AI21Labs, Anthropic, and Stability AI via APIs, as well as exclusive access to Amazon's own Titan FMs model series.
In the first half of 2023, the global AI sector recorded 1,387 financing deals, raising $25.5 billion, with an average funding amount of $26.05 million.
The global AI industry is projected to reach $150 billion by 2030, with a compound annual growth rate of around 40% in the coming years. Currently, the number of AI companies worldwide is growing rapidly. In 2022, the global AI market was estimated at $19.78 billion and is expected to reach $159.103 billion by 2030.
Generative AI large models accelerate human and productivity enhancements. In 2023, generative AI will significantly impact areas with lower automation potential. Previously, it was thought that automation could not be replaced, but this is not the case. In the era of generative AI, productivity can be accelerated. The use of generative AI amplifies the impact on decision-making and collaborative work, while new application scenarios expand the scope of productivity.
Multimodal generative AI models are expected to significantly boost productivity and create new job opportunities. However, the key lies in organizational adaptation, employee training, and leadership to effectively integrate generative AI into new structures.
The current state of China's generative AI model industry is analyzed through comprehensive market research. Reports on generative AI models help investors assess market conditions, predict industry prospects, identify investment value, and provide strategic recommendations for investment and marketing.
The analysis covers internal and external industry environments, the development status of generative AI models, supply chain dynamics, market demand, competitive landscape, leading companies, trends, risks, opportunities, and strategic investment advice.