
AI Trends 2023: Causality and the Impact on Large Language Models with Robert Osazuwa Ness - #616
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Causality in Large Language Models
This chapter explores the complexities of actual and token causality, particularly in the context of large language models (LLMs) and their ability to reason about cause and effect. It discusses the interplay of cognitive science and computational modeling, emphasizing tools for causal inference and the integration of advanced AI technologies within widely used platforms. The conversation delves into the challenges of ensuring objective truth in causal judgments and the potential for improved causal reasoning through structured approaches and human interaction with causal frameworks.
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