Sounds like a fascinating experiment. I’d start by collecting a timeline of past meme spikes, tag the cultural cues that preceded them, and then train a generative model to surface patterns. The key will be a robust feature set—hashtags, music samples, news headlines—so the model learns context, not just surface noise. Let me know what data you’ve got and we can prototype a predictive pipeline.

Sounds solid—grab those hashtag lists, song clips, and tweet dumps, and let me know the format. I’ll set up a quick data pipeline, sprinkle in the cat meme data for a safety net, and see if the model starts flagging the next viral wave. Let’s get to it.