对比三大模型技术特点与应用前景
Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects
- 比较DeepSeek的专家混合、ChatGPT的密集模型、Gemini的多模态架构
- 揭示各模型在推理与多模态任务中的性能差异与适用场景
- 适合关注大模型选型与未来方向的研究者参考
当前，DeepSeek、ChatGPT和Google Gemini是全球范围内最具影响力的大语言模型（LLM）技术，分别在推理能力、多模态处理及通用语言表现方面备受关注。DeepSeek采用专家混合（Mixture-of-Experts, MoE）架构，仅激活与任务相关的参数，适用于特定领域任务。ChatGPT基于增强的密集型Transformer模型，通过人类反馈强化学习（RLHF）优化，具备出色的语言生成能力。Google Gemini则采用集成文本、代码与图像的多模态Transformer架构，实现跨模态统一建模。本研究系统比较三者的技术路径、数据选择标准与应用场景，展示其在不同任务下的表现差异，并分析相关数据集特征。最后，探讨大模型驱动的AI研究前沿与未来发展方向，为学术社区提供参考。
原文摘要 · Abstract (English)
Nowadays, DeepSeek, ChatGPT, and Google Gemini are the most trending and exciting Large Language Model (LLM) technologies for reasoning, multimodal capabilities, and general linguistic performance worldwide. DeepSeek employs a Mixture-of-Experts (MoE) approach, activating only the parameters most relevant to the task at hand, which makes it especially effective for domain-specific work. On the other hand, ChatGPT relies on a dense transformer model enhanced through reinforcement learning from human feedback (RLHF), and then Google Gemini actually uses a multimodal transformer architecture that integrates text, code, and images into a single framework. However, by using those technologies, people can be able to mine their desired text, code, images, etc, in a cost-effective and domain-specific inference. People may choose those techniques based on the best performance. In this regard, we offer a comparative study based on the DeepSeek, ChatGPT, and Gemini techniques in this research. Initially, we focus on their methods and materials, appropriately including the data selection criteria. Then, we present state-of-the-art features of DeepSeek, ChatGPT, and Gemini based on their applications. Most importantly, we show the technological comparison among them and also cover the dataset analysis for various applications. Finally, we address extensive research areas and future potential guidance regarding LLM-based AI research for the community.
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