Aphyr on AI hallucination: why we can't trust systems trained to sound confident

Aphyr examines the fundamental problem with large language models—they're optimized to produce plausible text, not accurate text—and argues this creates a broken foundation for tools builders are deploying. For indie makers relying on AI for features or automation, the takeaway is harder than it looks: there's no simple fix for systems that have learned to lie convincingly.