A groundbreaking development in brain-computer interface (BCI) technology has enabled a stroke survivor to communicate through an AI-powered implant. The patient, who lost her ability to speak due to a brainstem stroke, can now form sentences at a rate of 78 words per minute using a device that translates her brain signals into text and speech. The experimental system, developed by researchers at UC San Francisco, uses artificial intelligence algorithms to decode neural patterns associated with attempted speech. The implant consists of a thin array of 253 electrodes placed on the surface of the brain, which captures signals from speech-related areas. These signals are then processed by AI models that convert them into text with 98% accuracy. This achievement represents a significant advance over previous BCI systems, which typically achieved much slower communication rates. The technology demonstrates particular promise for patients with conditions like stroke, ALS, and other neurological disorders that affect speech. While the system currently requires surgical implantation and is still experimental, researchers are working on less invasive alternatives. The success of this implementation highlights the potential of AI-driven neural interfaces to restore communication abilities and improve quality of life for individuals with severe speech impairments. The research team emphasizes that continued development could lead to more accessible and efficient communication solutions for patients worldwide.