Using generative AI and natural language processing on multiple UFO sighting databases, we finally have the tools to answer questions like Hynek first posed in 1972
175 strangers filed independent reports about the same thing. 96% agreed on the color. 100% agreed on the sound. I ran the data on the Tinley Park Lights.
My first approach to analyzing 152,000 UFO sightings had a 34% accuracy rate. I almost published it anyway. Here's what went wrong with semantic embeddings, why I pivoted to LLM extraction, and the methodology that actually worked.
If we exist within a simulation, we cannot "break out" of it. This isn't a practical limitation—it's a logical impossibility. Instead can we use random behavior to let our simulators know we're on to them?
