By guest author: Nielo Wait, VRZ Champions LinkedIn: https://www.linkedin.com/in/nielo/ YouTube: Slopfiction Caveat: These ideas were articulated with the assistance of artificial intelligence — barely legal em dashes and all. Two AIs walk into a bar. Bartender: “Sorry, we don’t serve minors.” As the western AI begins to litigate, the eastern AI forks the bartender, open-sources the quantized version, and shouts, "The next round is on me!" USA, run by lawyers, is trying to legislate its way into AI dominance. China, run by engineers, is shipping fast, hard-coding its own vision of what AI should be. Both are building futures. But the difference in approach is already warping the GenAI landscape — and who gets to shape it. That’s the frame: GenAI isn’t good or bad. It’s just barely legal . Not in the smirking, R-rated LoRa sense. In the sense that the rulebook doesn’t exist yet, the court cases are unresolved, the ethics are wea...
It’s a common lament: “I asked ChatGPT for scientific references, and it returned the names of non-existent papers.” How and why does this happen? Why would large language models (LLMs) such as ChatGPT create fake information rather than admitting they don’t know the answer? And why is this such a complex problem to solve? LLMs are an increasingly common presence in our digital lives. (Less sophisticated chatbots do exist, but for simplification, I’ll refer to LLMs as “chatbots” in the rest of the post.) These AI-driven entities rely on complex algorithms to generate responses based on their training data. In this blog post, we will explore the world of chatbot responses and their constraints. Hopefully, this will shed some light on why they sometimes "hallucinate." How do chatbots work? Chatbots such as ChatGPT are designed to engage in conversational interactions with users. They are trained on large ...