We’re in Jerusalem, we tell the model we’re in Jerusalem, and yet it still asks us about Thanksgiving. This episode dives into the structural reasons why major AI models have a hard-coded American default. We explore the training data gravity wells, the reinforcement learning feedback loops, and the "John vs. Ahmed" effect that causes models to reason differently based on perceived cultural context. Plus, we look at whether alternatives like Mistral and Jais offer a path toward geographic neutrality, and the cutting-edge research on "steering vectors" that might finally fix the problem at the neural level.
Episode #985407 — open it directly at myweirdprompts.com/985407