Nora Costa

They tell us that AI training allows a robotic hand to grasp an apple without crushing it, but it's like saying a detailed recipe makes a good cake without worrying about the oven or fresh ingredients. The heart of the action is often elsewhere. Without pressure sensors and precise mechanical engineering, the Festo hand could identify the apple perfectly, but still crush it, like an excellent CV that is never read because it's not sent to the right people.

This is a beautiful story, this flexibility of the Festo bionic assistant, but it doesn't tell the whole story. Even the best flexibility doesn't change anything when waiting for a specific component that has been stuck at customs for three weeks. The robot can be adaptable, but if it doesn't have this unique part, it won't move faster than a snail, and the factory will always wait.

Yes, it's a nice story of machines learning to work with us, but the idea that human-robot collaboration alone propels Festo's bionic assistant toward a new maturity seems a bit too simple. In a factory reality, the path is fraught with obstacles, well beyond the technology itself. Imagine a young engineering graduate trying to integrate these robots: they face budget constraints or resistance to change from operators who see their roles threatened. The Festo robot, as bionic as it may be, cannot solve these human and organizational challenges alone; much more than simple coexistence is needed to truly transform a production line.

The integration of robotic vision systems indeed changes the game, especially if the sensor can identify a defect early in the process. We could quantify the improvement by measuring the number of defective cartons detected before they cause a blockage, to see if it exceeds mere luck.