Your inner monologue may be less constant than you think--more like a fridge light that turns on when you look. Thinking doesn't always involve words. Breakthroughs, discoveries, and DIY tips sent six days a week. When I first started researching this story, I assumed I was writing about other people: those fascinating outliers who reportedly lack an internal monologue--the experience of actively speaking words in your mind as a sort of private narration of your life. Then I got on a Zoom call with Dr. Russell Hurlburt, a psychologist at the University of Nevada, Las Vegas, who has spent 50 years studying inner experience, and somewhere in the first ten minutes, I started to wonder: What if I'm talking about myself?

Scientists are one step closer to reading people's minds after developing new technology that can decode internal speech with nearly 80 per cent accuracy. Some people are unable to speak due to disease or injury, but devices called brain-machine interfaces (BMIs) can help patients communicate again. Also known as'speech decoders', BMIs can capture brain activity during inner speech – words thought within the mind without making any movement or sound – and translate it into language. Until now, it has been difficult to achieve highly accurate results. Researchers from the California Institute of Technology implanted tiny devices in specific areas of the brains of two participants.

AI can now guess what tune you're singing in your head - without you ever uttering a sound. Scientists in California have created a mind-reading machine that reveals the song being thought about simply by studying the brain's electrical activity. The finding opens the door to strange future scenarios, such as those portrayed in the series'Black Mirror', where AI can record and playback everything you've ever seen and heard. The finding opens the door to strange future scenarios, such as those portrayed in the series'Black Mirror', where AI can record and playback everything you've ever seen and heard Researcher Brian Pasley has previously used a deep-learning algorithm trained with brain activity, to turn a person's thoughts into digital speech. His team has now improved on that earlier research and applied the findings to music to create a new AI.