The field of Artificial Intelligence (AI) is making significant strides with the introduction of an innovative technological tool. Researchers from the School of Engineering at the Hong Kong University of Science and Technology (HKUST) have formulated a liquid metal-based electronic logic device that closely mirrors the intelligent prey-capture system linked to Venus flytraps.

This unique tool possesses memory and counting capabilities, enabling it to interact intelligently to varying stimulus sequences without the need for supplementary electronic components. By understanding this inherent "intelligence" of nature, the device offers a fresh perspective for the development of "embodied intelligence".

Venus flytraps have always aroused interest due to their distinct predator capture mechanism, which enables them to accurately differentiate between various external stimuli. For instance, thanks to the sensory hairs on these carnivorous plants, they can distinguish between environmental disturbances like raindrops (single touch) and insects (double touch), facilitating potent prey capture.

Inspired by this mechanism, Prof. SHEN Yajing, Associate Professor of the Department of Electronic and Computer Engineering (ECE) at HKUST, alongside Associate Professor Dr. YANG Yuanyuan of Xiamen University, crafted the Liquid Metal-based Logic Module (LLM). The LLM utilizes extension/contraction deformation of liquid metal wires, thereby regulating the cathodic output according to the stimuli applied to the anode and the gate. LMM can remember the duration and interval of electrical stimuli, calculate the accumulation of signals from multiple stimuli, and deliver considerable logical functions similar to Venus flytraps.

By creating an artificial Venus flytrap system, including the LMM-driven intelligent decision-making device, switch-based sensory hair, and a soft electric actuator-based petal, the researchers replicated the prey-capturing mechanism of Venus flytraps. This work paves the way for LMM's applications in areas such as functional circuit integration, filtering, and artificial neural networks.

Prof. Shen highlights that AI is commonly associated with the replication of animal nervous systems. However, many plants demonstrate unique intelligence through specific material and structural combinations. This direction offers a new way to understand 'intelligence' in nature, and to construct 'life-like intelligence'.

Indeed, it took several years of effort to achieve the conceptual verification and simulation of the intelligence of Venus flytraps. Yet, it should be noted that this work is in its preliminary stage. Further investigation and development are needed, such as designing more efficient structures, scaling down devices, and boosting system responsiveness.

Disclaimer: The above article was written with the assistance of AI. The original sources can be found on ScienceDaily.