Artificial intelligence “tongue” can distinguish between Pepsi and Coke

Beware, taste testers: a new “AI tongue” seems to be able to distinguish between Pepsi and Coca-Cola.

According to researchers at Penn State in Pennsylvania, they have created an electronic tongue that can distinguish between the two carbonated beverages.

According to scientists, the tongue can identify, categorize, and judge the freshness of food and beverages. It may also be used to identify food pollutants that cause illness in consumers, such as milk that has beyond its expiration date.

They have also created an algorithm within the tongue that mimics the thoughts of a human brain, helping it to become familiar with food tasting.

The new creation is made of graphene and chemical sensors that detect and measure the makeup of liquids and convert their findings into electronic signals.

During the research stages, the tongue was given different tasks to learn.

Scientists found that their creation could detect watered-down milk, different types of sodas, coffees and multiple fruit juices with more than 80 per cent accuracy.

Specifically, it reached accuracy levels of 98% when identifying the type of fruit and 99% when determining its age.

The study stated: ‘Although corrective actions exist for food adulteration and contamination incidents, monitoring food freshness is more challenging because of time-varying and complex chemical compositions present in food.

‘Spoilt food is dangerous to consume and possesses a diminished nutritional value.’

Scientists have said that while this study is focused on food detection, their research could extend to medical diagnostics too.

Professor Saptarshi Das, who works in engineering science and mechanics at Penn State, said: ‘We’re trying to make an artificial tongue, but the process of how we experience different foods involves more than just the tongue.

‘We have the tongue itself, consisting of taste receptors that interact with food species and send their information to the gustatory cortex – a biological neural network.’

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