3min chapter

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) cover image

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)

CHAPTER

The Connection Between Causal Discovery and Downstream Machine Learning

The trend that I saw was actually connecting the learning of causal structure to downstream machine learning tasks. For example, as paper called on the generalization and adaptation performance of causal models. This is using an idea from causal inference called independence of mechanism. And so they use that intuition to basically say, well, the more right my graph is, the faster it should adapt to the new data set.

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