Remote viewing (RV) research explores the human capacity to perceive information about distant or concealed targets beyond the known senses. Traditional RV protocols can yield rich qualitative data but are slow, resource-intensive, and vulnerable to human biases during tasking and judging. In an IRVA-funded pilot, I established AIRV: a fully automated RV pipeline that (i) randomly selects image targets from a database, (ii) generates “viewing” outputs via AI (text/image generation), and (iii) applies automated judging using multimodal similarity metrics. In that pilot, a hardware Random Event Generator (REG) was used to drive generative models that produced transcript images, which were then statistically compared to their targets using semantic and visual embeddings.
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Published on October 23, 2026
