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Let’s be honest: Most of what we call artificial intelligence today is really just pattern-matching on autopilot. It looks impressive until you scratch the surface. These systems can generate essays, compose code and simulate conversation, but at their core, they’re predictive tools trained on scraped, stale content. They do not understand context, intent or consequence.
It’s no wonder then that in this boom of AI use, we’re still seeing basic errors, issues and fundamental flaws that lead many to question whether the technology really has any benefit outside its novelty.
These large language models (LLMs) aren’t broken; they’re built on the wrong