# From Large Language Models to Large Multimodal Models: A Literature Review
## 5 Comparative Analysis from the View of Globalization  
In this section, we delve into the development status of large-scale models across diverse global regions, analyzing their latest achievements as well as examining the safety, limitations, and other contextual factors that shape this status. By integrating case studies along with economic and political analysis, we strive to offer a comprehensive understanding of the landscape of large-scale models from the view of globalization. **The United States (USA)** holds a core and leadership position in various aspects of large model development, encompassing data, computational power, and model architecture. A suite of emblematic large models has originated within USA, including OpenAI's GPT series [2; 3; 4; 5; 85] and DALL-E series [157; 158; 159], Google's Transformer and PaLM series [6; 7], DeepMind's Gemini series [160; 161], and Meta (Facebook)'s LLaMA series [8; 9], to name a few. Furthermore, the monopolistic edge in high-performance hardware enjoyed by the USA, embodied by NVIDIA's computing GPUs such as the A100 and H100, provides speed and efficiency advantages for training large models. The USA's leadership in large model development is deeply rooted in its strong innovation ecosystem, backed by substantial private investments and a culture that encourages risk-taking. Socioeconomically, the presence of Silicon Valley and other tech hubs fosters a competitive environment that spurs advancements. Culturally, the emphasis on free speech and information access has enabled the creation of vast datasets. However, this leadership is not without controversy. Models such as GPT-4 [5], while groundbreaking in the technological realm, have raised ethical concerns in the safety realm over data bias, potential misuse, and the exacerbation of existing social inequalities. Moreover, the environmental costs of these models, as well as production of the related hardware, poses additional carbon challenges due to their massive energy consumption [162; 163]. **China** is demonstrating robust momentum in the development of large models, accompanied by a vibrant market. Robust backing from the Chinese government and scientific community has spurred intense competition among several leading enterprises, including Baidu, Alibaba, Tencent, and others seeking to innovate in the AI large model field. Chinese companies adopt an ecosystem-diverse and systematic approach, typically rolling out a series of models to create a holistic technological ecosystem. Examples include Baidu's ERNIE series [164; 165; 166] of large models and its derivative ERNIEbot, Huawei's PanGu series [10; 11; 49] model, Alibaba's Tongyi series, Tencent's HunYuan series. Additionally, Chinese universities actively participate in large model development and research, partner ing with tech companies or independently creating multiple large models, with Tsinghua University's CPM [36; 37; 167] series and GLM [168] being one such instance. China's progress in AI is fueled by a combination of state-driven policies, significant investment, and a large domestic market. The socioeconomic context is characterized by a digital economy that thrives on massive data generation, which, coupled with government support, accelerates AI innovation. Politically, the central government's strategic plans, such as \"Made in China 2025\", prioritize AI, demonstrating a top-down commitment. The case of China showcases how supportive state-driven policies and strong company-government partnership can drive innovation; however, this also raises questions about data privacy, given the state's involvement. While China has initiated the establishment of a relevant legal framework for data protection, ensuring in practice that all data sources and processing by international giants such as Tencent, Baidu, Alibaba, and ByteDance strictly adhere to regulatory requirements remains a complex issue. **South Korea** is capitalizing on its semiconductor industry's computational strength to follow closely behind the USA in large model development.