Language Models' Semantic Shift
Andrew discusses how language models challenge the traditional separation of syntax and semantics, suggesting a potential shift in perspective. He predicts a future where the effectiveness of these models in practical tasks may overshadow philosophical debates on their true meaning.In this clip
From this podcast
Machine Learning Street Talk (MLST)
#83 Dr. ANDREW LAMPINEN (Deepmind) - Natural Language, Symbols and Grounding [NEURIPS2022 UNPLUGGED]
Related Questions
Can large language models replicate human behavior as discussed in Mindscape 292 | Jonathan Birch on Animal Sentience and in the episode Cameron Jones & Sean Trott: Understanding, Grounding, and Reference in LLMs and the clip Unraveling Model Interpretability?
What's your opinion on using large language models (LLMs) for scientific research, especially for generating new ideas for hypotheses as discussed in the episode "Neurosymbolic AI in Search with Professor Laura Dietz - Weaviate Podcast #49!" and the clip "Knowledge Graph Queries"?