Lets talk about llms

Differently. (ChatGPT and LLMs—a friendly reminder) (Assume everything is possible—another friendly reminder.) LLMs are great. LLMs are easy and efficient. Yeah? But for how long? Let’s reject the premise that everything goes right. Let’s talk about it going wrong. What if it does go wrong? Seriously — what happens when we go wrong? Notice I said we . (One last friendly reminder.) How far can we go? Can I use an LLM to generate a five-page website for my cousin’s apartment house? Sure I can. Can I get into a fight with my cousin and then poison his already SEO-optimized apartment website? Sure I can. Can that website be scraped and its content end up in training data? You see where this is going. Can I do it a hundred times simply by saying /loop x100 ? I could do all of these things—but why would I? Because human beings do things for reasons as petty, envy, anger and spite, business. Considering training and post-training cutoffs, I could potentially poison ChatGPT’s perception of lesser-known people, businesses and properties—those with only a small online presence. Correcting that damage could take far more effort than filing a Google takedown request. Worse still, unless you regularly ask ChatGPT about yourself or your property, how would you even discover that you were being trashed? With Google, you can search your name and see what appears. With an LLM, the damage may remain invisible until someone asks the right question. “Meh. You would need thousands of articles and websites trashing someone before they appeared in ChatGPT’s training data and had any real impact.” Yeah—and? /loop My cousin’s apartment is merely the simplest analogy: ordinary human envy, equipped with extraordinary automation. So, what happens when we go wrong? What happens when we become so reliant on ChatGPT that it becomes our daily source of information—and we begin treating it as a credible authority? What happens when we tell our friends and family something we “read on ChatGPT”? It m