The Fungal Digital Revolution
In a groundbreaking convergence of mycology and computer science, researchers at the Unconventional Computing Laboratory at the University of the West of England have successfully demonstrated that networks of living fungi can perform computational tasks traditionally reserved for silicon-based machines. This revolutionary approach to computing leverages the innate intelligence of fungal organisms, which have been evolving for over 1.5 billion years —far longer than human technological systems have existed.
Led by Professor Andrew Adamatzky, the team published their findings in the journal Science Advances in late 2022, revealing how mycelium—the vast underground network of fungal threads—can be utilized as biological information processors capable of solving complex problems while consuming minimal energy. The implications of this work extend beyond mere technological curiosity, potentially offering solutions to some of computing’s most pressing challenges: energy consumption, heat generation, and environmental sustainability.
The research represents a paradigm shift in our understanding of computation itself. While conventional computing relies on engineered systems with clear boundaries between hardware and software, fungal computing blurs these distinctions by utilizing living tissue that simultaneously serves as both physical infrastructure and problem-solving mechanism. This integration of form and function mirrors natural intelligence systems rather than the artificial separation characteristic of human-designed computers.
From Forest Floor to Computing Core
Mycelium networks, which can span thousands of acres in natural settings, function as sophisticated communication systems in nature. These fungal networks transmit electrical signals in patterns remarkably similar to those in conventional computing systems. In forest ecosystems, they serve as what mycologist Paul Stamets has termed the “natural internet of the soil,” transferring nutrients, carbon, and information between trees and other plants in a complex web of biological connectivity.
“What makes mycelium computing revolutionary is its inherent parallelism,” explains Dr. Adamatzky. “Unlike traditional computers that process information sequentially, fungal networks process multiple signals simultaneously across their entire structure—similar to how our brains work.”
The research team cultivated Pleurotus djamor (pink oyster mushroom) mycelium on hemp substrates embedded with microelectrodes. By introducing carefully calibrated electrical stimuli at different points in the network, they observed how signals propagated through the living system. These signals travel at speeds of approximately 0.5-2.6 centimeters per second—dramatically slower than electronic computers but with a degree of complexity and adaptability that silicon cannot match.
What distinguishes mycelial networks from traditional computing architecture is their adaptive plasticity. When faced with obstacles or damage, the network can reroute signals and even regenerate connections—a form of self-healing that conventional computers lack entirely. This resilience stems from the decentralized nature of fungal networks, which have no single point of failure and can continue to function even when portions are compromised.
Solving Problems Through Biological Intelligence
What’s particularly remarkable about fungal computing is its efficiency in solving certain classes of problems. The researchers demonstrated that mycelium networks excel at optimization challenges—specifically variations of the “traveling salesman problem” where the goal is to find the shortest possible route between multiple points.
When presented with this challenge, the fungal network naturally grows along optimal pathways between nutrient sources, effectively “computing” the most efficient solution through its biological growth patterns. This approach leverages the fungi’s evolutionary imperative to maximize resource acquisition while minimizing energy expenditure—a biological optimization algorithm refined over millions of years.
“The network achieved approximately 73% optimization efficiency compared to traditional algorithms, while consuming less than 0.1% of the energy,” notes Dr. Maria Simonova, co-author of the study. “What’s more fascinating is that the mycelium doesn’t simply find a workable solution—it continuously refines its pathways over time, improving efficiency through an ongoing process of growth and retraction.”
The team has also documented the network’s ability to perform rudimentary memory functions. When repeatedly exposed to the same stimulus patterns, the mycelium exhibited faster and more coordinated responses, suggesting a form of biological learning. This emergent property hints at applications beyond simple computation, potentially entering the realm of what could be considered primitive artificial intelligence—though grounded in biological rather than digital systems.
Environmental Computing
The environmental implications are substantial. While conventional computing infrastructure consumes enormous amounts of electricity and produces electronic waste, fungal computing systems are biodegradable, self-repairing, and operate at room temperature with minimal energy requirements.
Traditional data centers consume approximately 200-250 watts per square foot and require extensive cooling systems to prevent overheating. In contrast, fungal computing arrays operate at ambient temperatures and consume less than 5 watts per square foot, representing a potential 98% reduction in energy requirements. Furthermore, at the end of their operational life, mycelium computers can be composted rather than contributing to the growing crisis of electronic waste.
The Finnish environmental technology firm Fungi Computations Oy has already secured €3.2 million in funding to develop practical applications. Their prototype, unveiled at the Helsinki Tech Expo in March 2023, demonstrated a mycelium-based environmental sensing system that can monitor soil conditions and process the data within the same biological substrate. This integration of sensing and computation within a single biological system eliminates the need for separate sensors, processors, and transmission equipment.
“We’re moving toward computing that is not just environmentally neutral but environmentally positive,” explains Dr. Elina Järvinen, CEO of Fungi Computations Oy. “These systems can serve computational functions while simultaneously enhancing soil health and biodiversity—a dual benefit impossible with traditional computing infrastructure.”
Beyond Binary: The Fungal Advantage
Unlike conventional computers that operate on binary logic (0s and 1s), fungal computing leverages a more complex system of electrical potentials, chemical gradients, and growth patterns. This enables a form of “fuzzy logic” that may be better suited for addressing specific real-world issues involving uncertainty or multiple variables.
“Conventional computing excels at precision and speed for well-defined problems,” says Dr. Adamatzky. “Fungal computing offers something different—an adaptive, resilient system that excels at problems requiring spatial reasoning and parallel processing.”
This fundamental difference suggests complementary roles rather than competition between silicon and fungal computing. Traditional computers will likely remain superior for tasks that require precise calculations, while mycelium networks may offer advantages for problems that require adaptability, pattern recognition, and energy efficiency.
The non-binary nature of fungal signaling also presents intriguing possibilities for quantum-inspired computing. While not true quantum computation, the analog nature of mycelial information processing allows for states that exist along a continuum rather than in discrete values, potentially offering new approaches to problems that challenge conventional computing architectures.
Cross-Disciplinary Implications
The implications extend far beyond the field of computer science. Neurologists are studying these fungal information processing systems to understand emergent intelligence in decentralized networks better. Environmental scientists envision the potential for developing sensitive biological monitoring systems that can detect and respond to ecological changes.
Perhaps most intriguingly, the research challenges fundamental assumptions about intelligence and cognition. If a network of fungal cells can solve complex computational problems, it raises profound questions about the nature of intelligence itself. The work suggests that intelligence may be a property that emerges from networked systems regardless of their constituent materials—whether neurons, fungi, or silicon.
Philosophers of mind have begun incorporating these findings into discussions of panpsychism and distributed cognition. If problem-solving capability exists in fungal networks, how might we need to reconsider our definitions of cognition and consciousness? These questions push us toward a more inclusive understanding of intelligence that transcends anthropocentric and even zoocentric perspectives.
Future Directions
The research team is now investigating how various fungal species may be suited for different computational tasks. Preliminary results suggest that Cordyceps militaris, known for its complex parasitic lifecycle, demonstrates superior pattern recognition capabilities compared to other tested species.
While fungal computers won’t be replacing your laptop anytime soon, they point toward a future where biological and conventional computing systems might work in tandem—silicon for precision tasks and mycelium for adaptive, energy-efficient problem-solving.
“We’re not just building computers from fungi,” concludes Dr. Adamatzky. “We’re learning a completely different way of thinking about computation itself—one that’s been evolving in forests for over a billion years.”