Causality in AI
Robert discusses his recent work on causal reasoning and large language models, highlighting the intersection of probabilistic machine learning and causal inference. He shares insights from his collaborative research, which explores benchmarks and applications in the realm of causality, emphasizing the potential impact of LLMs in this field.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Are LLMs Good at Causal Reasoning? with Robert Osazuwa Ness - 638
Related Questions
Can you explain causality in machine learning in the context of the episode Are LLMs Good at Causal Reasoning? with Robert Osazuwa Ness - 638 and the clip Causal Discovery Insights?
Can you explain causality in machine learning as discussed in the episode Causality 101 with Robert Ness - #342 and the clip Causal Representation Learning?
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 888: Marc Andreessen | Exploring the Power, Peril, and Potential of AI and the clip The Power of Computer Creativity?