A new computer now operating at University College London mimics the randomness found in nature and can instantly recover from crashes by repairing its own corrupted data. Such a machine could be instrumental in keeping mission-critical systems working at all times in the face of technological breakdowns. For example, it could allow drones to reprogram themselves in the face of combat damage.

It could also help in building realistic models of the human brain. “Everyday computers are ill suited to modeling natural processes such as how neurons work or how bees swarm. This is because they plod along sequentially, executing one instruction at a time,” writes New Scientist.

“Nature isn’t like that,” said UCL computer scientist Peter Bentley. “Its processes are distributed, decentralized and probabilistic. And they are fault tolerant, able to heal themselves. A computer should be able to do that.”

New Scientist describes why today’s computers are not a great fit for advancements in modeling. “Today’s computers work steadily through a list of instructions: one is fetched from the memory and executed, then the result of the computation is stashed in memory. That is then repeated – all under the control of a sequential timer called a program counter. While the method is great for number-crunching, it doesn’t lend itself to simultaneous operations.”

For this new computer now operating at UCL, Bentley and UCL’s Christos Sakellariou “have created a computer in which data is married up with instructions on what to do with it. For example, it links the temperature outside with what to do if it’s too hot. It then divides the results up into pools of digital entities called ‘systems,’” according to the article.

Bentley further explained how the systems work together. “Each system has a memory containing context-sensitive data that means it can only interact with other, similar systems. Rather than using a program counter, the systems are executed at times chosen by a pseudorandom number generator, designed to mimic nature’s randomness. The systems carry out their instructions simultaneously, with no one system taking precedence over the others, says Bentley.”