MIRA's AI Hallucination Solution Achieves 97% Accuracy

The CEO of MIRA shared insights on the AI hallucination issue during a podcast. Recent improvements in AI performance stem from inference scaling, which allows models to think more deeply during use, making intelligence cheaper and more sophisticated inference methods lead to better results. Because AI tasks are complex, hallucination rates are typically around 10-20%, with multiple hallucinations possible during action steps. MIRA's solution involves leveraging the fact that different large language models (LLMs), trained on different data and methods, are unlikely to fail in the same way simultaneously. The process involves the main model generating results, followed by three other models independently verifying, and iterating until consensus is reached. This system boosts accuracy from 70% to 97%, reducing hallucination rates tenfold. The core innovation is in the parallel verification technique, which maintains high speed while improving accuracy.