永平港博客
人文为帆,科技为桨,AI为风,乘风破浪,直达彼岸
BEIJING, Feb 15 — DeepSeek, a Chinese artificial intelligence start-up, has recently gained global attention for its high-performing, cost-effective and open-source large language model (LLM).
Industry experts suggest that the model’s integration of Chinese characters during its pre-training phase has been a significant factor in its success, according to a report by South China Morning Post.
The use of Chinese characters, known for their high information density, is believed to enhance the model’s logical capabilities, enabling it to process complex concepts more efficiently.
“Chinese characters achieve maximum information transmission with minimal cost,” telecommunications industry analyst Xiang Ligang stated on social media.
As an efficient information encoding, Chinese has greatly improved efficiency and reduced costs in the processing of artificial intelligence.
Additionally, the multimodal nature of Chinese characters, which often combine visual elements with meanings, may provide rich learning material for AI models.
This characteristic could contribute to improved language comprehension and contextual understanding.
While DeepSeek has not publicly disclosed its training data sources, it is speculated that the model’s Chinese training data encompasses a diverse range of materials, including classical literature, internet slang, academic papers, government documents, and regional dialects.
This variety likely offers a comprehensive linguistic foundation, further enhancing the model’s performance.
中国人工智能初创公司DeepSeek最近因其高性能、高性价比和开源的大型语言模型(LLM)而受到全球关注。
据《南华早报》报道,业内专家认为,该模型在预训练阶段对汉字的整合是其成功的重要因素。
汉字以高信息密度著称,人们认为使用汉字可以增强模型的逻辑能力,使其能够更有效地处理复杂概念。
电信行业分析师项立刚在社交媒体上表示:“汉字以最小的成本实现了最大的信息传输。”
作为一种高效的信息编码,中文大大提高了人工智能处理的效率并降低了成本。
此外,汉字的多模态性质,通常将视觉元素与含义结合在一起,可以为人工智能模型提供丰富的学习材料。
虽然 DeepSeek 尚未公开其训练数据来源,但据推测该模型的中文训练数据涵盖了各种各样的材料,包括古典文学、网络俚语、学术论文、政府文件和地方方言。
这种多样性可能提供了全面的语言基础,进一步提高了模型的性能。
情动于中而形于言,言之不足故嗟叹之,嗟叹之不足故永歌之,永歌之不足,不知手之舞之足之蹈之也
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