Researchers at Stanford University have developed a brain-computer interface (BCI) capable of decoding inner speech—the silent monologue people imagine in their heads—with up to 74% accuracy. This technology uses electrodes combined with artificial intelligence to interpret brain activity related to imagined speech, enabling individuals with paralysis to communicate without physically attempting to speak. The system has been tested on participants with severe paralysis, decoding sentences from a vocabulary of up to 125,000 words in real time. This breakthrough, published on August 14, 2025, represents a potential advancement in speech neuroprostheses and could significantly improve communication for people unable to speak due to neurological conditions. The implant's ability to translate inner speech into spoken words bypasses the need for physical speech attempts, which distinguishes it from most existing technologies. Researchers suggest that with further improvements in implant hardware and recognition software, future systems could restore fluent and rapid speech solely through inner speech decoding. Thousands of paralyzed patients have shown interest in BCI trials, though only a few meet the strict medical criteria required for participation. The innovation also raises discussions about brain transparency and ethical considerations regarding decoding thoughts.