Researchers Create Synthetic Synapse That Could Potentially Lead to Intelligent Machines

Artificial Intelligence  

Scientists have reported the development of a first-of-its-kind synthetic synapse that mimics the plasticity of the human brain, bringing us one step closer to human-like artificial intelligence.

Building a computer that learns and remembers like a human brain is a complex challenge. Our brains contain over 86 billion neurons and trillions of connections—or synapses—that can grow stronger or weaker over time. By studying biological synapses, researchers have applied their findings to the development of neuromorphic engineering.

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Now Chinese scientists report in ACS' journal Nano Letters the development of a first-of-its-kind synthetic synapse that mimics the plasticity of the real thing, bringing us one step closer to human-like artificial intelligence.

While the human brain still holds many secrets, one thing we do know is that the flexibility, or neuroplasticity, of neuronal synapses is a critical feature. In the synapse, many factors, including how many signaling molecules get released and the timing of release, can change. 

"This work would offer a broad new vista for the 2D material electronics and guide the innovation of neuro-electronics fundamentally."

This mutability allows neurons to encode memories, learn and heal themselves. In recent years, researchers have been building artificial neurons and synapses with some success but without the flexibility needed for learning. Tian-Ling Ren and colleagues set out to address that challenge.

The researchers created the artificial synapse out of aluminum oxide and twisted bi-layer graphene. 

By applying different electric voltages to the system, they found they could control the reaction intensity of the receiving "neuron." The team says their novel dynamic system could aid in the development of biology-inspired electronics capable of learning and self-healing.

"This work would offer a broad new vista for the 2D material electronics and guide the innovation of neuro-electronics fundamentally," write the authors of the study.

SOURCE  ACS

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