In 2021, a dish of living human brain cells figured out how to play the 1970s arcade game Pong. It took just five minutes for the collection of neurons, called DishBrain, to learn how to move the paddle and hit the ball, marking the first time that a lab-grown neural network had ever completed a goal-oriented task.
In a study published the following year, researchers at the Australian startup Cortical Labs said the breakthrough not only offered new insights into how the brain works, but could provide the platform for a new era of ultra-intelligent biological computers capable of thinking like a human.
Cortical Labs referred to it not as artificial intelligence, but actual intelligence. By combining real neurons with hardware, biocomputers have the potential to solve general tasks that current AI systems struggle with, while also requiring just a fraction of the energy.
Hundreds of millions of years of evolution have made the human brain extremely energy efficient. The 86 billion neurons of an average brain require just 20 watts of power to function – roughly the same amount as an LED bulb.
By contrast, the inefficient architecture of current artificial intelligence systems means that even simple tasks require massive amounts of power. Facial recognition, for example, requires thousands of times more energy for an AI to perform compared to a human simply recognising a face.
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