The default FLUX DEV model lacks diversity in many aspects in the moment. Therefore, using cheap frontal flash photography as training data for a LoRa model seems an effective way to explore the bandwidth of the FLUX DEV model. This LoRa training experiment aims to challenge both the stereotypical visuals of FLUX and the representation of age and gender in its motifs. Consequently, the training data was specifically selected to include images of diverse objects, scenes, and people, captured using blurry, grainy, cheap flash-based analog photography. Special attention was given to images where isolated objects are highlighted by the flash while the rest of the image fades into darkness due to the lack of light. Mostly frontal flashed suburban and wildly overgrown forest scenes are in the training data + cropped wild perspectives of people.