AI network made of DNA can identify 'molecular handwriting'

Scientists have developed a neural network using DNA, which can correctly identify numbers encoded in molecules using machine learning, an advance that may pave the way for biological machines with artificial intelligence.

Artificial neural networks are mathematical models inspired by the human brain. Despite being much simplified compared to their biological counterparts, artificial neural networks function like networks of neurons and are capable of processing complex information.

The ultimate goal for this work is to programme intelligent behaviours (the ability to compute, make choices, and more) with artificial neural networks made out of DNA.

"In this work, we have designed and created biochemical circuits that function like a small network of neurons to classify molecular information substantially more complex than previously possible," said Lulu Qian, assistant professor at California Institute of Technology in the US.

To illustrate the capability of DNA-based neural networks, researchers chose a task that is a classic challenge for electronic artificial neural networks: recognising handwriting.

Human handwriting can vary widely, and so when a person scrutinises a scribbled sequence of numbers, the brain performs complex computational tasks in order to identify them.

Artificial neural networks networks must be "taught" how to recognise numbers, account for variations in handwriting, then compare an unknown number to their so-called memories and decide the number's identity.

In the study published in the journal Nature, researchers showed that a neural network made out of carefully designed DNA sequences could carry out prescribed chemical reactions to accurately identify "molecular handwriting."