LeCun的演讲以询问“大型语言模型是否需要感官基础以获得意义和理解能力？”为开始。他认为，首先我们需要理解什么是语言模型，以及为什么需要它。其次，演讲中提到了不同的大型语言模型，例如OpenAI的GPT和Facebook的Roberta。他强调了这些模型的语言能力和生成文本的质量。
LeCun提出了一个有趣的问题：“为什么要让计算机理解语言？”他强调，人类语言是含义、知识和思想的媒介。他认为，我们需要向计算机传递这种媒介，以便计算机能够像人类一样理解世界。
他还讨论了最新的研究，探讨了感官输入是否能够帮助大型语言模型更好地理解。他提出了一些解决方案，例如使用多模态输入和结合视觉和语言数据等。
在演讲的结尾，LeCun总结了该主题，并强调将来需要更深入的研究来解决这个问题，并向观众提出了一些引人深思的问题。
综上所述，LeCun的演讲探讨了大型语言模型是否需要感官基础以获得意义和理解能力的问题，并提出了解决方案和开放性问题。
Slides链接：https://drive.google.com/file/d/1BU5bV3X5w65DwSMapKcsr0ZvrMRU_Nbi/view
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