Still, meat demand in the world is increasing as populations and economies grow. Global production of meat has doubled from 159 million tonnes in 1986 to almost 318 million in 2014, according to the UN’s Food and Agriculture Organisation (FAO) . Even in countries where it is not a luxury, meat consumption stubbornly refuses to fall. Both in the US and in the UK, it is estimated that the proportion of the population who are vegetarians – let alone vegans – is in the single digits.

As Keiffer says, “it's going to be hard to tell people who did not have the advantage of eating meat and are just beginning to discover it, that they can't have it”. So, whatever replacements for meat that Tetrick and Muchnick come up need to taste and feel like the original product. But they also have to be scaleable, accessible, and hopefully, healthier. So how is AI helping them to do this?

Building blocks

For people like Tetrick and Muchnick, the way to start is a change in perspective. Their idea of a muffin is very different from how the average person sees one. They see a toolbox where we see a pantry; they see a chemical experiment where we see a treat. “The muffin needs to aerate, it needs to bun, it needs to brown. It needs a texture, it needs to have a shelf life”, explains Tetrick. (He offers no word on how tasty it needs to be, however.)

Their aim is to find a way to make the muffin do all this, but using different ingredients. It is a “very difficult puzzle” to solve, says Ricardo San Martin, visiting professor at the Alternative Meat Lab of the University of California in Berkeley. On the one hand, every single aspect of the experience, from the taste and texture to the way the food changes when it is heated, is the product of specific molecules or a micro-component, like proteins or fats. In our current diet, many of these come from animal ingredients.