Large language models (LLMs), like ChatGPT, are fascinating but often misunderstood. While some see them as advanced tools or companions, others question their true nature—just complex algorithms lacking sentience or inner thoughts. Despite their extensive training on internet data, LLMs can still falter, especially when posed with specific prompts. One such query—“Was there ever a seahorse emoji?”—exhibits how these models can spiral into confusion. Interestingly, there has never been a seahorse emoji; this misconception exemplifies the Mandela effect—a collective false memory shared by many. While LLMs don’t possess memories or consciousness, they can reflect human errors and beliefs based on their training data, showcasing a unique form of “hallucination.” Consequently, when users interact with these models, they inadvertently unleash echoes of human confusion, making LLMs seem eerily human-like, yet fundamentally non-human. As more information clarifies misunderstandings, future models may correct these errors, enhancing their reliability.
Source link
