TOKYO (AP) — A small robot with a clip-like hand and enough smarts to know which drinks are popular is part of an effort to make convenience stores even more convenient.

On a recent day in Tokyo, the robot named TX SCARA slid back and forth behind the refrigerated shelves in the back of a FamilyMart store.

The hand on the end of its mechanical arm grasped a bottle or can from the stacks to the side, then the robot slithered to the right spot and placed the drink on the shelf — in a place chosen after its artificial intelligence and tiny cameras matched the kind of beverage to what’s running short.

Conversational AI platform Jio Haptik has tied up with Microsoft Azure to improve its existing hindi language chatbots | Photo Credit: Getty Images.

He claimed that using the data from Haptik and cognitive models from Microsoft, the team could come up with a highly accurate solution for Hindi — not only written in Devanagari but also Hindi written in Roman script.

Every year, more than 69 million people around the world suffer traumatic brain injury, which leaves many of them unable to communicate through speech, typing, or gestures. These people’s lives could dramatically improve if researchers developed a technology to decode language directly from noninvasive brain recordings. Today, we’re sharing research that takes a step toward this goal. We’ve developed an AI model that can decode speech from noninvasive recordings of brain activity.

From three seconds of brain activity, our results show that our model can decode the corresponding speech segments with up to 73 percent top-10 accuracy from a vocabulary of 793 words, i.e., a large portion of the words we typically use on a day-to-day basis.

Decoding speech from brain activity has been a long-standing goal of neuroscientists and clinicians, but most of the progress has relied on invasive brain-recording techniques, such as stereotactic electroencephalography and electrocorticography. These devices provide clearer signals than noninvasive methods but require neurosurgical interventions. While results from that work suggest that decoding speech from recordings of brain activity is feasible, decoding speech with noninvasive approaches would provide a safer, more scalable solution that could ultimately benefit many more people. This is very challenging, however, since noninvasive recordings are notoriously noisy and can greatly vary across recording sessions and individuals for a variety of reasons, including differences in each person’s brain and where the sensors are placed.