Artificial Intelligence has made huge leaps in recent years, but one major issue remains unresolved: reliability. AI systems can generate convincing answers that may contain factual errors, hallucinations, or biased conclusions.
This limitation prevents AI from being used safely in high-stakes domains such as healthcare, finance, law, and infrastructure.
Modern AI models are probabilistic systems. They predict likely outputs rather than verifying facts. This means even advanced models can confidently provide incorrect information.
Scaling models larger does not eliminate this problem. The fundamental trade-off between hallucinations and bias creates a reliability ceiling that no single model can surpass.
For AI to become truly autonomous and trustworthy, a new layer of infrastructure is required one that verifies AI outputs instead of trusting them by default.
Key Insight : AI progress is now limited less by intelligence and more by trustworthiness.
@Mira - Trust Layer of AI #Mira $MIRA
