AI image models fail botany test

Diffusion models prioritize statistical plant-likeness over biological rules, making them unreliable for expert applications without custom fine-tuning. Training data bias ensures popular flora like roses are rendered perfectly while exotic species like Stapeliads suffer from low-quality reference sets, leading to "impossible ecology" hallucinations in current SaaS generators. The community identifies LoRAs and local Stable Diffusion setups as the only viable solutions for the high-precision technical visualization required by niche industries and scientific worldbuilding.