With neuronal data, AI models predict grammar, meaning and context of spoken sentences (opens in new tab)

By applying machine-learning models to single-cell brain recordings taken from humans in conversation, a research team identified both individual and collective neuronal activity that reflected key features of language. The work, published in Nature, offers unprecedented insight into how neurons encode linguistic information, suggesting that brain activity may one day be used to infer speech-related thoughts, which could be transformative for some patients.