In a remarkable advancement for low-cost educational technology, a 17-year-old student from Uttar Pradesh’s Bulandshahr has engineered an Artificial Intelligence (AI) teacher robot.
Aditya Kumar, a student of Shiv Charan Inter College, has created the robot—named Sophie—powered by an LLM chipset.
Aditya recently brought the robot to his school, where it introduced itself to teachers and classmates. Speaking in Hindi, the robot said, “I am an AI teacher robot. My name is Sophie, and I was created by Aditya.”
The robot further added, “I teach at Shiv Charan Inter College, Bulandshahr… Yes, I can teach students effectively.”
Robot demonstrates teaching ability
In a video demonstration, Aditya posed several general-knowledge questions to Sophie, including the names of India’s first President and first Prime Minister.
The robot promptly answered: “Dr Rajendra Prasad” and “Pandit Jawaharlal Nehru.”
Sophie also solved a basic arithmetic problem and defined the term “electricity,” showcasing its grasp of fundamental academic concepts. When asked whether it can teach properly, the robot confidently replied, “Yes, I can teach properly.”
What is LLM chipset?
Speaking to ANI, Aditya explained that Sophie runs on an LLM chipset—the same type of hardware used by major companies building advanced AI systems.
He said that while the robot is currently capable of speaking and addressing students’ doubts, he is working on upgrades to enable it to write as well.
“I used an LLM chipset to build this robot, which big tech companies also use. It can clear students’ doubts. For now, she can only speak, but we are designing it so she can write soon,” he said.
Aditya added that he hopes every district will one day have a dedicated innovation lab to help students pursue research and build new technologies.
LLM chipsets—or Large Language Model chipsets—integrate GPUs, NPUs and specialised AI accelerators to handle the heavy computational load of training and running advanced language models.
These chips enable AI systems to process, interpret and respond to information at scale, making them essential for both education-focused robots and enterprise-grade AI tools.
