Researchers at the University of California, Davis, have developed a brain-computer interface (BCI) that enables a man with amyotrophic lateral sclerosis (ALS) to produce natural-sounding, expressive speech and sing melodies in real time. This AI-powered neural implant translates brain signals into audio with a latency as low as 10 to 25 milliseconds, allowing for near-instantaneous communication without the usual delays associated with speech synthesis. The system decodes neural activity every 10 milliseconds and achieves approximately 97% accuracy in converting brain signals into speech. This breakthrough represents a major advancement in BCI technology, offering new communication possibilities for people with paralysis and severe speech disabilities. The implant not only restores the ability to speak but also captures intonations and pitch, enabling the patient to sing. Additional research from institutions including UC San Francisco and teams in Shanghai is advancing similar technologies, with some systems achieving over 90% accuracy in thought-to-text translation. These developments hold promise for a range of neurological conditions, including stroke and Parkinson's disease, by potentially restoring speech and cognitive functions through electroceuticals and brain stimulation techniques. The technology has received FDA approval for decoding imagined speech, marking a critical step toward wider clinical application.