A analysis group led by the Faculty of Engineering of the Hong Kong College of Science and Expertise (HKUST) has developed a liquid metal-based digital logic machine that mimics the clever prey-capture mechanism of Venus flytraps. Exhibiting reminiscence and counting properties, the machine can intelligently reply to varied stimulus sequences with out the necessity for added digital parts. The clever methods and logic mechanisms within the machine present a contemporary perspective on understanding “intelligence” in nature and provide inspiration for the event of “embodied intelligence.”
The distinctive prey-capture mechanism of Venus flytraps has at all times been an intriguing analysis focus within the realm of organic intelligence. This mechanism permits them to successfully distinguish between numerous exterior stimuli corresponding to single and double touches, thereby distinguishing between environmental disturbances corresponding to raindrops (single contact) and bugs (double touches), making certain profitable prey seize. This performance is primarily attributed to the sensory hairs on the carnivorous crops, which exhibit options akin to reminiscence and counting, enabling them to understand stimuli, generate motion potentials (a change {of electrical} indicators in cells in response to stimulus), and bear in mind the stimuli for a brief period.
Impressed by the interior electrical sign accumulation/decay mannequin of Venus flytraps, Prof. SHEN Yajing, Affiliate Professor of the Division of Digital and Laptop Engineering (ECE) at HKUST, who led the analysis, joined arms along with his former PhD pupil at Metropolis College of Hong Kong, Dr. YANG Yuanyuan, now Affiliate Professor at Xiamen College, proposed a liquid metal-based logic module (LLM) based mostly on the extension/contraction deformation of liquid steel wires. The machine employs liquid steel wires in sodium hydroxide resolution because the conductive medium, controlling the size of the liquid steel wires based mostly on electrochemical results, thereby regulating cathode output based on the stimuli utilized to the anode and gate. Analysis outcomes reveal that the LLM itself can memorize the period and interval {of electrical} stimuli, calculate the buildup of indicators from a number of stimuli, and exhibit important logical capabilities much like these of Venus flytraps.
To reveal, Prof. Shen and Dr. Yang constructed a synthetic Venus flytrap system comprising the LLM clever decision-making machine, switch-based sensory hair, and mushy electrical actuator-based petal, replicating the predation technique of Venus flytraps. Moreover, they showcased the potential purposes of LLM in purposeful circuit integration, filtering, synthetic neural networks, and extra. Their work not solely supplies insights into simulating clever behaviors in crops, but additionally serves as a dependable reference for the event of subsequent organic sign simulator gadgets and biologically impressed clever techniques.
“When folks point out ‘synthetic intelligence’, they often consider intelligence that mimics animal nervous techniques. Nonetheless, in nature, many crops may also reveal intelligence by means of particular materials and structural mixtures. Analysis on this path supplies a brand new perspective and method for us to grasp ‘intelligence’ in nature and assemble ‘life-like intelligence’,” mentioned Prof. Shen.
“A number of years in the past, when Dr. Yang was nonetheless pursuing her PhD in my analysis group, we mentioned the concept of developing clever entities impressed by crops collectively. It’s gratifying that after a number of years of effort, we’ve got achieved the conceptual verification and simulation of Venus flytrap intelligence. Nonetheless, it’s price noting that this work remains to be comparatively preliminary, and there’s a lot work to be achieved sooner or later, corresponding to designing extra environment friendly constructions, decreasing the scale of gadgets, and enhancing system responsiveness,” added Prof. Shen.