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Higher Mental Functions of the Brain: Language01:10

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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相关实验视频

Updated: Jun 12, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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大型语言模型减少了在线问答平台上公众的知识共享.

R Maria Del Rio-Chanona1,2,3, Nadzeya Laurentsyeva4,5, Johannes Wachs6,7,3

  • 1Department of Computer Science, University College London, London WC1E 6EA, United Kingdom.

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概括

像ChatGPT这样的大型语言模型 (LLM) 正在减少像Stack Overflow这样的平台上的人为生成的内容. 数据的减少可能会阻碍未来人工智能模型的开发.

关键词:
在这里,我们可以看到AIAIAI.聊天GPT 聊天 在GPT 聊天在线公共产品在线公共产品网络 网络 网络 网络 网络

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科学领域:

  • 人工智能的人工智能
  • 计算机科学 计算机科学
  • 数据科学数据科学数据科学

背景情况:

  • 大型语言模型 (LLM) 提供了人类生成数据的替代品的潜力.
  • 越来越多地使用LLM可能会减少对培训未来AI模型至关重要的人类生成内容的可用性.

研究的目的:

  • 调查大型语言模型 (LLM),特别是ChatGPT对人类生成内容生产的影响.
  • 为了量化ChatGPT发布后堆溢出活动的减少.

主要方法:

  • 在ChatGPT发布后记录了堆溢出活动的减少.
  • 使用的反事实比较Stack Overflow与受ChatGPT影响较小的资源 (例如,俄罗斯/中国同行,数学论坛).
  • 分析了用户体验层次的后质量和内容创建的变化.

主要成果:

  • 在ChatGPT发布后的六个月内,堆溢出活动相对于未受影响的平台而言下降了25%.
  • 与流行的编程语言相关的帖子下降更为明显.
  • 没有观察到后质量的显著变化;所有用户体验级别的内容创建都下降了.

结论:

  • 像ChatGPT这样的LLM不仅取代了低质量或初学者内容,还取代了经验丰富的用户的内容.
  • 广泛采用LLM正在减少培训未来AI模型所必需的公共数据的产生,这带来了重大挑战.
  • 这种培训数据的减少对人工智能开发的持续进步具有关键意义.