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| 1 minute read

Fungal neural networks to tackle climate change?

It's widely accepted that we know relatively little about the fungi kingdom compared to its size, which is somewhat surprising given its importance to virtually all ecosystems on the planet. Fungi are responsible for decomposing organic matter to provide nutrients to soil, and even help to move nutrients between plants. The more we can understand about fungal networks, the better chance we have of being able to engineer these networks to our advantage.

But just because fungi is a natural kingdom doesn't mean fungi research will not generate IP. Anyone who has seen the Netflix documentary Fantastic Fungi will have heard the story of the American mycologist Paul Stamets, who developed and patented a fungus-based method for exterminating colonies of termites. Normally, termites are good at detecting diseases in their populations, and guard the entrances to their colonies so that any infected termites can be killed. Stamets was able to use a fungus to mask infectious termites so that they could pass into the colony undetected, whereupon the disease would spread through the population. 

That's why I'm excited to hear about a new study that proposes to use AI-based techniques to simulate fungal networks, so we can learn more about how these networks develop. The study proposes to research the potential for mycological networks to act as carbon traps to help tackle climate change. The potential for the generation of world-changing IP in this field is enormous. 

And machine learning will be used to build up a picture of the function of fungal networks and their role as carbon sinks - something that absorbs more carbon-containing compounds - such as carbon dioxide from the atmosphere - than it releases.


neural networks, fungi, mycology, artificial intelligence