Even advanced technology can struggle when the real world becomes unpredictable. In April 2026, a Waymo robotaxi in San Antonio, Texas, drove into a flooded lane during severe weather, prompting the company to recall about 3,800 vehicles for a software fix.

No one was injured, but the incident exposed a deeper challenge: intelligence is not just about processing data. It is about knowing where to look, what to notice, when to act and how to use previous experience when conditions change.

AI researchers are now looking at bees and other insects to help them design machines and robots that can make better decisions.

My research explores how bees learn, from identifying simple visual patterns to mastering high-level concepts, and how they adapt their behaviour when conditions change.

By combining behavioural experiments, neural recording (for example, measuring signals from the brain) and neuromorphic computing (an approach to computing inspired by the animal brain), my goal is to uncover the biological code that allows tiny brains to navigate a complex world and make efficient decisions. I have also worked in industry to translate these biological discoveries into robotic applications – bringing the intelligence of the hive to machine intelligence.

Research on honeybee decision making has shown that bees make rapid and accurate choices about whether to accept or reject flowers. They do not need perfect information. Instead, they combine sensory evidence, past experience and the likely value of a reward (for example, how much nectar they might gather).

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