Thu. Nov 25th, 2021
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    Luckily, science has lent a helping hand after researchers used artificial intelligence to crack the crowning technique for cooking first-class crepes.

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    The team at Monolith, an offshoot of Imperial College London, made their discovery after feeding dozens of popular recipes into an algorithm.

    “The whole point is to experiment with different ratios of ingredients and be confident the outcome will be the desired type of pancake – fluffy and not rubbery,” Monolith wrote in a blog post last week.

    After comparing the highest-rated entries, the machine learning model coughed out the best method for American-style pancakes.

    According to its suggestion, to get the fluffiest pancakes you’re best off frying your batter on a medium heat, and only flipping each cake once.

    To get the fluffiest pancakes, you're best off frying your batter on a medium heat, and only flipping each cake once

    3To get the fluffiest pancakes, you’re best off frying your batter on a medium heat, and only flipping each cake onceCredit: Alamy

    Seven ingredients – flour, sugar, baking powder, salt, milk, butter and eggs – are all you need to smash your Shrove Tuesday dinner out of the park.

    Monolith usually works with the likes of Airbus and Honda to develop the best engine or car prototype.

    When it applied its algorithm to pancake recipes, the AI predicted the right amount of ingredients for the fluffiest results. They are:Flour – 210gSugar – 48g Baking powder – 14g Salt – 6g Eggs – 2 Milk – 256g Butter – 25g 

    Seven ingredients – flour, sugar, baking powder, salt, milk, butter and eggs – are all you need to make the best pancakes

    3Seven ingredients – flour, sugar, baking powder, salt, milk, butter and eggs – are all you need to make the best pancakesCredit: Stewart Williams – The Sun

    Monolith said that hundreds of recipes were fed into its model to get the results.

    “We found over 800 recipes for American style fluffy pancakes,” said the firm in its blog post. 

    “However, we needed recipes with enough positive and negative reviews to train the model to predict what amount of ingredients would give us the fluffiest pancakes.

    “After elimination, we ended up with a dataset of 31 recipes with enough reviews to train a model to predict the right output.”

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