The future of AI lies squarely in the physical realm, according to many industry figures such as Nvidia CEO Jensen Huang. Much of the evolution of AI in recent years has, as expected, been in aid of building machines that can learn quicker, think faster, and interact with the physical world in a more compelling way.
Checkmate
Nearly 40 years ago, the scientist Rodney Brooks authored a significant robotics paper that argued real-world robotics should focus on simpler, layered behavioral systems to understand the world rather than complex internal models.
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His comments in the study ‘Elephants Don’t Play Chess‘ signalled a major paradigm shift in the way scientists saw the training and learning process for robots then and in the future. It challenged the established status quo for how scientists considered physical AI, and proved fairly divisive at the time.
The old sense-model-act-plan (SMPA) approach to AI – in which robots would scan a room to build a 3D digital map inside their memory and plan the optimal path within that map – was out. Instead, Brooks proposed that when a robot changes the world around itself, it doesn’t need to compute the impact of everything – just the most relevant parts.
One man saw it coming
Brooks co-founded the company now known as iRobot alongside two colleagues from MIT’s AI lab in the same year as he published his seminal paper, although back then it was called IS Robotics.
The first product was Geghis, an insect-like space explorer that weighed 1kg and served as a prototype for low-cost space exploration. Then, more than 10 years later in 2002, the company launched its first Roomba robot vacuum cleaner.
Despite enjoying success through the decades, iRobot filed for bankruptcy in December 2025 and the company was eventually taken private and absorbed into the operations of Chinese company Shenzhen Picea Robotics.
