A showcase meant to signal India’s growing artificial intelligence ambitions spiralled into controversy after Galgotias University was accused of passing off a commercially available robot dog as its in-house innovation at the India AI Summit in New Delhi.Though the university denied the allegations, saying it never claimed its indigenous development, the quadruped robot, which drew heavy crowds and camera attention at the university’s pavilion, quickly became one of the most talked-about attractions at the event. Videos of the machine walking, saluting visitors and interacting with delegates flooded social media, with many users hailing it as a sign of indigenous robotics progress.However, the narrative shifted after tech observers and robotics enthusiasts identified the machine as a commercially sold quadruped developed by Chinese robotics firm Unitree. Users circulated product videos and catalog images, alleging the robot resembled the Unitree Go2, a widely available industrial and research robot.The backlash intensified when social media posts claimed the university had showcased the robot as part of a high-value indigenous AI ecosystem, fuelling accusations of exaggeration and “AI optics”. Some social media users said the viral clip generated more eyeballs than many serious research exhibits, but for the “wrong reasons”.Responding to the criticism, Galgotias University released a statement, saying that it was procured from a Chinese manufacturer for academic purposes.It said the robotic dog was acquired from Unitree, a global robotics company based in China, and was being used as a learning tool for students.“Let us be clear, Galgotias has not built this robodog, nor have we claimed to do so. What we are building are minds that will soon design, engineer and manufacture such technologies in Bharat,” the university added.Nevertheless, the episode reignited a debate over demonstrative technology showcases and original deep-tech development.While global summits often feature commercially sourced robots for demonstration, critics argue clearer attribution is essential, especially when public funding, institutional credibility and national innovation claims intersect.
