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4min chapter
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)
Inducing Causal Structure for Interpretable Neural Networks
The next paper you wanted to talk about is the inducing causal structure for interpretable neural networks. Is this one related to simulation as well? I don't think the authors, well, maybe they were. You would be used. So if our goal is to figure out how to be intentional about extracting causal information from simulators, you could apply this technique. And so that's an interesting direction for understanding how we can incorporate causal information more systematically and intentionally into models like foundation or large language models.
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