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KAIST Team Develops an Insect-Mimicking Semiconductor to Detect Motion
The recent development of an “intelligent sensor” semiconductor that mimics the optic nerve of insects while operating at ultra-high speeds and low power offers extensive expandability into various innovative technologies. This technology is expected to be applied to various fields including transportation, safety, and security systems, contributing to both industry and society.
On February 19, a KAIST research team led by Professor Kyung Min Kim from the Department of Materials Science and Engineering (DMSE) announced the successful developed an intelligent motion detector by merging various memristor* devices to mimic the visual intelligence** of the optic nerve of insects.
*Memristor: a “memory resistor” whose state of resistance changes depending on the input signal
**Visual intelligence: the ability to interpret visual information and perform calculations within the optic nerve
With the recent advances in AI technology, vision systems are being improved by utilizing AI in various tasks such as image recognition, object detection, and motion analysis. However, existing vision systems typically recognize objects and their behaviour from the received image signals using complex algorithms. This method requires a significant amount of data traffic and higher power consumption, making it difficult to apply in mobile or IoT devices.
Meanwhile, insects are known to be able to effectively process visual information through an optic nerve circuit called the elementary motion detector, allowing them to detect objects and recognize their motion at an advanced level. However, mimicking this pathway using conventional silicon integrated circuit (CMOS) technology requires complex circuits, and its implementation into actual devices has thus been limited.
< Figure 1. Working principle of a biological elementary motion detection system. >
Professor Kyung Min Kim’s research team developed an intelligent motion detecting sensor that operates at a high level of efficiency and ultra-high speeds. The device has a simple structure consisting of only two types of memristors and a resistor developed by the team. The two different memristors each carry out a signal delay function and a signal integration and ignition function, respectively. Through them, the team could directly mimic the optic nerve of insects to analyze object movement.
< Figure 2. (Left) Optical image of the M-EMD device in the left panel (scale bar 200 μm) and SEM image of the device in the right panel (scale bar: 20 μm). (Middle) Responses of the M-EMD in positive direction. (Right) Responses of the M-EMD in negative direction. >
To demonstrate its potential for practical applications, the research team used the newly developed motion detector to design a neuromorphic computing system that can predict the path of a vehicle. The results showed that the device used 92.9% less energy compared to existing technology and predicted motion with more accuracy.
< Figure 3. Neuromorphic computing system configuration based on motion recognition devices >
Professor Kim said, “Insects make use of their very simple visual intelligence systems to detect the motion of objects at a surprising high speed. This research is significant in that we could mimic the functions of a nerve using a memristor device.” He added, “Edge AI devices, such as AI-topped mobile phones, are becoming increasingly important. This research can contribute to the integration of efficient vision systems for motion recognition, so we expect it to be applied to various fields such as autonomous vehicles, vehicle transportation systems, robotics, and machine vision.”
This research, conducted by co-first authors Hanchan Song and Min Gu Lee, both Ph.D. candidates at KAIST DMSE, was published in the online issue of Advanced Materials on January 29.
This research was supported by the Mid-Sized Research Project by the National Research Foundation of Korea, the Next-Generation Intelligent Semiconductor Technology Development Project, the PIM Artificial Intelligence Semiconductor Core Technology Development Project, the National Nano Fab Center, and the Leap Research Project by KAIST.
2024.02.29 View 3978 -
Professor Shinhyun Choi’s team, selected for Nature Communications Editors’ highlight
[ From left, Ph.D. candidates See-On Park and Hakcheon Jeong, along with Master's student Jong-Yong Park and Professor Shinhyun Choi ]
See-On Park, Hakcheon Jeong, Jong-Yong Park - a team of researchers under the leadership of Professor Shinhyun Choi of the School of Electrical Engineering, developed a highly reliable variable resistor (memristor) array that simulates the behavior of neurons using a metal oxide layer with an oxygen concentration gradient, and published their work in Nature Communications. The study was selected as the Nature Communications' Editor's highlight, and as the featured article posted on the main page of the journal's website.
Link : https://www.nature.com/ncomms/
[ Figure 1. The featured image on the main page of the Nature Communications' website introducing the research by Professor Choi's team on the memristor for artificial neurons ]
Thesis title: Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing.
( https://doi.org/10.1038/s41467-022-30539-6 )
At KAIST, their research was introduced on the 2022 Fall issue of Breakthroughs, the biannual newsletter published by KAIST College of Engineering.
This research was conducted with the support from the Samsung Research Funding & Incubation Center of Samsung Electronics.
2022.11.01 View 5642 -
Neuromorphic Memory Device Simulates Neurons and Synapses
Simultaneous emulation of neuronal and synaptic properties promotes the development of brain-like artificial intelligence
Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic computing designed to rigorously mimic the human brain with semiconductor devices.
Neuromorphic computing aims to realize artificial intelligence (AI) by mimicking the mechanisms of neurons and synapses that make up the human brain. Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses still remains a challenge. To address these issues, a research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices.
Similar to commercial graphics cards, the artificial synaptic devices previously studied often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost efficiency.
The human brain consists of a complex network of 100 billion neurons and 100 trillion synapses. The functions and structures of neurons and synapses can flexibly change according to the external stimuli, adapting to the surrounding environment. The research team developed a neuromorphic device in which short-term and long-term memories coexist using volatile and non-volatile memory devices that mimic the characteristics of neurons and synapses, respectively. A threshold switch device is used as volatile memory and phase-change memory is used as a non-volatile device. Two thin-film devices are integrated without intermediate electrodes, implementing the functional adaptability of neurons and synapses in the neuromorphic memory.
Professor Keon Jae Lee explained, "Neurons and synapses interact with each other to establish cognitive functions such as memory and learning, so simulating both is an essential element for brain-inspired artificial intelligence. The developed neuromorphic memory device also mimics the retraining effect that allows quick learning of the forgotten information by implementing a positive feedback effect between neurons and synapses.”
This result entitled “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse” was published in the May 19, 2022 issue of Nature Communications.
-Publication:Sang Hyun Sung, Tae Jin Kim, Hyera Shin, Tae Hong Im, and Keon Jae Lee (2022) “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse,” Nature Communications May 19, 2022 (DOI: 10.1038/s41467-022-30432-2)
-Profile:Professor Keon Jae Leehttp://fand.kaist.ac.kr
Department of Materials Science and EngineeringKAIST
2022.05.20 View 9847 -
Energy-Efficient AI Hardware Technology Via a Brain-Inspired Stashing System
Researchers demonstrate neuromodulation-inspired stashing system for the energy-efficient learning of a spiking neural network using a self-rectifying memristor array
Researchers have proposed a novel system inspired by the neuromodulation of the brain, referred to as a ‘stashing system,’ that requires less energy consumption. The research group led by Professor Kyung Min Kim from the Department of Materials Science and Engineering has developed a technology that can efficiently handle mathematical operations for artificial intelligence by imitating the continuous changes in the topology of the neural network according to the situation. The human brain changes its neural topology in real time, learning to store or recall memories as needed. The research group presented a new artificial intelligence learning method that directly implements these neural coordination circuit configurations.
Research on artificial intelligence is becoming very active, and the development of artificial intelligence-based electronic devices and product releases are accelerating, especially in the Fourth Industrial Revolution age. To implement artificial intelligence in electronic devices, customized hardware development should also be supported. However most electronic devices for artificial intelligence require high power consumption and highly integrated memory arrays for large-scale tasks. It has been challenging to solve these power consumption and integration limitations, and efforts have been made to find out how the human brain solves problems.
To prove the efficiency of the developed technology, the research group created artificial neural network hardware equipped with a self-rectifying synaptic array and algorithm called a ‘stashing system’ that was developed to conduct artificial intelligence learning. As a result, it was able to reduce energy by 37% within the stashing system without any accuracy degradation. This result proves that emulating the neuromodulation in humans is possible.
Professor Kim said, "In this study, we implemented the learning method of the human brain with only a simple circuit composition and through this we were able to reduce the energy needed by nearly 40 percent.”
This neuromodulation-inspired stashing system that mimics the brain’s neural activity is compatible with existing electronic devices and commercialized semiconductor hardware. It is expected to be used in the design of next-generation semiconductor chips for artificial intelligence.
This study was published in Advanced Functional Materials in March 2022 and supported by KAIST, the National Research Foundation of Korea, the National NanoFab Center, and SK Hynix.
-Publication:
Woon Hyung Cheong, Jae Bum Jeon†, Jae Hyun In, Geunyoung Kim, Hanchan Song, Janho An, Juseong Park, Young Seok Kim, Cheol Seong Hwang, and Kyung Min Kim (2022)
“Demonstration of Neuromodulation-inspired Stashing System for Energy-efficient Learning of Spiking Neural Network using a Self-Rectifying Memristor Array,” Advanced FunctionalMaterials March 31, 2022 (DOI: 10.1002/adfm.202200337)
-Profile:
Professor Kyung Min Kimhttp://semi.kaist.ac.kr https://scholar.google.com/citations?user=BGw8yDYAAAAJ&hl=ko
Department of Materials Science and EngineeringKAIST
2022.05.18 View 8449 -
What Guides Habitual Seeking Behavior Explained
A new role of the ventral striatum explains habitual seeking behavior
Researchers have been investigating how the brain controls habitual seeking behaviors such as addiction. A recent study by Professor Sue-Hyun Lee from the Department of Bio and Brain Engineering revealed that a long-term value memory maintained in the ventral striatum in the brain is a neural basis of our habitual seeking behavior. This research was conducted in collaboration with the research team lead by Professor Hyoung F. Kim from Seoul National University. Given that addictive behavior is deemed a habitual one, this research provides new insights for developing therapeutic interventions for addiction.
Habitual seeking behavior involves strong stimulus responses, mostly rapid and automatic ones. The ventral striatum in the brain has been thought to be important for value learning and addictive behaviors. However, it was unclear if the ventral striatum processes and retains long-term memories that guide habitual seeking.
Professor Lee’s team reported a new role of the human ventral striatum where long-term memory of high-valued objects are retained as a single representation and may be used to evaluate visual stimuli automatically to guide habitual behavior.
“Our findings propose a role of the ventral striatum as a director that guides habitual behavior with the script of value information written in the past,” said Professor Lee.
The research team investigated whether learned values were retained in the ventral striatum while the subjects passively viewed previously learned objects in the absence of any immediate outcome. Neural responses in the ventral striatum during the incidental perception of learned objects were examined using fMRI and single-unit recording.
The study found significant value discrimination responses in the ventral striatum after learning and a retention period of several days. Moreover, the similarity of neural representations for good objects increased after learning, an outcome positively correlated with the habitual seeking response for good objects.
“These findings suggest that the ventral striatum plays a role in automatic evaluations of objects based on the neural representation of positive values retained since learning, to guide habitual seeking behaviors,” explained Professor Lee.
“We will fully investigate the function of different parts of the entire basal ganglia including the ventral striatum. We also expect that this understanding may lead to the development of better treatment for mental illnesses related to habitual behaviors or addiction problems.”
This study, supported by the National Research Foundation of Korea, was reported at Nature Communications (https://doi.org/10.1038/s41467-021-22335-5.)
-ProfileProfessor Sue-Hyun LeeDepartment of Bio and Brain EngineeringMemory and Cognition Laboratoryhttp://memory.kaist.ac.kr/lecture
KAIST
2021.06.03 View 8106 -
KAIST International Symposium Highlights the Value of Science through Global Collaboration
The presidents of three premier science and technology universities shared their belief that universities should move forward to embrace social changes while maintaining the importance of academics for future generations during the KAIST International Symposium on February 16.
The symposium, one of the events to celebrate KAIST’s 50th anniversary, highlighted the future role of universities over the next 50 years by hosting a panel featuring ETH Zurich President Joël Mesot, Caltech President Thomas Rosenbaum, and KAIST President Sung-Chul Shin. Members of the foreign diplomatic corps representing seven countries also explored the new model of global collaboration in the second session.
President Rosenbaum of Caltech said that even though society is changing, the role of universities will not be different since the value of knowledge will always be important. He said that universities must embrace change.
He said that universities should move forward fearlessly if they believe it would impact wider society positively. He added that universities should also be courageous enough to take a new path based on longer-term perspectives and lessons learned from successes. One of the roles of universities is to establish various hypotheses and possible prospects, raise doubts, and go forward with a strong will for the future generations to come.
He cited LIGO (the Laser Inerferometer Gravitational-wave Observatory), as a good example of a successful university-research collaboration. LIGO is funded by the National Science Foundation in the US and operated by Caltech and MIT. Approximately 1300 scientists from around the world, including the Max Planck Society in Germany and the Science and Technology Facilities Council in the UK, participate in the LIGO Scientific Collaboration. In 2019, the international team of scientists detected the collision of two black holes with masses about 142 times the mass of the sun in the most massive collision ever detected. MIT Physicist Rainer Weiss shared the Nobel Prize in Physics with Professor Barry Barish and Professor Kip Thorn from the Department of Physics at Caltech in recognition of their contribution to the LIGO detector and the observation of gravitational waves.
President Mesot of ETH Zurich stressed that universities should foster young talents well versed with creative thinking and entrepreneurship in this new era. He also said that COVID-19 has reaffirmed the importance of science and global collaborations beyond borders to address global challenges such as pandemics. President Mesot said COVID-19 has taught us the value of science and R&D, adding that the roll-out of a vaccine in only one year would have been impossible without the decades-long R&D foundation that universities and industries have established.
He also gave the example of the MRI as a reason universities should provide strong basic science research foundation. In 1944 in the US, Dr. Isidor Isaac Rabi won the Nobel Prize in Physics for his discovery of nuclear magnetic resonance. The MRI research inspired many ETH professors for further studies and led them to win the Nobel Prize in Physics in 1952 for their MRI basic theory and in 1991 the Nobel Prize in Chemistry with the development of high-resolution spectroscopy. “The MRI first started 80 years ago and still applies in today’s medicine. We should focus on research which will keep such value,” President Mesot said.
Meanwhile President Shin also said that the age of the Fourth Industrial Revolution has been deemed the "winner takes all" era. At this highly competitive time, R&D activities are more meaningful if they produce the world’s best, first, and only outcomes.
“We aim to achieve excellence in research with long-term innovative research support systems. We will conduct R&D activities that will lead the megatrends of the Fourth Industrial Revolution: hyper-connectivity, super-intelligence, and meta-convergence. In addition, we will double down to conduct forward-looking flagship research that will enhance the happiness and prosperity of all humanity in the areas of global warming, infectious diseases, bio-medicine, energy and environment, smart technology, and post-AI.”
Responding to one of the student’s question about what mindsets are expected of students enrolled in government-funded national universities, President Mesot made three suggestions. First, they should remember that they are privileged, so they should give back their talents to society. They should also be patient with what they are doing even when they don’t achieve the desired results. Lastly, they should remain open to new ideas and be flexible when encountering disruptions.
Seven diplomats stationing in Korea including Rob Rapson, US Charge d’Affairs ad Interim Rob Rapson, UAE Ambassador Abdulla Saif Al Nuaimi, Kenyan Ambassador Mwende Mwinzi, Danish Ambassador Einar Jensen, Pakistani Ambassador Mumtaz Zahar Baloch, Egyptian Ambassador Haem Fahmy, and UK Ambassador Simon Smith joined the second session themed KAIST for the Global Community.
They all agreed that KAIST is one of the shining examples of successful international collaboration stemming from the international aid loan from USAID. Five decades later, KAIST now is working to help the Kenyan government to establish Kenya KAIST with a 95-million US funding from the Korea Exim Bank.
While stressing the importance of global collaboration for inclusive growth in the global community, the seven diplomats gave their insights on the newly transforming global environment intertwined with COVID-19 and the Fourth Industrial Revolution.
In the face of global changes caused by emerging technologies and carbon neutrality, the ambassadors expressed a strong desire to make collaborations between KAIST and their countries to propel new innovations in industry and education in their countries.
2021.02.17 View 7750 -
Ph.D. Candidate Seo Wins the Human Tech Paper Award
Hyun-Suk Seo, a doctoral student of KAIST’s Department of Electrical Engineering, received the grand prize of the “22nd Human Tech Paper Award” on February 3, 2016 from Samsung Electronics Co., Ltd.
Seo was the first to receive this prize ever since the Human Tech Paper Award was established 22 years ago. Until last year, the highest prize awarded for KAIST was a gold one.
The “Human Tech Paper Award” was established in 1994 by Samsung Electronics to discover and support outstanding scientists in the field of electrical engineering.
Entitled “Self-Gated Cardiac Cine MRI Using Phase Information,” Seo’s paper presented a technology that would reduce discomforts and inconveniences experienced by patients who take a magnetic resonance imaging (MRI).
This technology uses the speed changes of aorta and the abdominal movements of body to obtain the phase changes of magnetic resonance signals so that MRIs may be taken despite the organs’ movements.
Seo commented on his research, “I wanted to develop a technique that can make MRI a more comfortable experience. I will continue my research on this subject and hope to serve the needs of the society.”
In addition, the “Special Award,” which is given to schools, was awarded to KAIST. KAIST’s Department of Electrical Engineering has also been named the department that has received the second most awards (15 awards) this year.
Oh-Hyun Kwon, Vice President of Samsung Electronics, Steve Kang, President of KAIST, and Nak-In Seo, President of Seoul National University, participated in the event.
Picture: Hyun-Suk Seo (left), the recipient of the grand prize of the 2016 Human Tech Paper Award, and Oh-Hyun Kwon (right), Vice President of Samsung Electronics
2016.02.06 View 7597 -
Leon Chua, the founder of the circuit theory called "memristor," gave a talk at KAIST
Dr. Leon Ong Chua is a circuit theorist and professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He visited KAIST on April 16, 2014 and gave a talk entitled “Memristor: New Device with Intelligence.”
Dr. Chua contributed to the development of nonlinear circuit theory and cellular neural networks (CNN). He was also the first to conceive of memristor which combines the characteristics of memory and resistor. Memristor is a type of resistor, remembering the direction and charge of electrical current that has previously flowed through the resistor. In other words, memristor can retain memory without power. Today, memristor is regarded as the fourth fundamental circuit element, together with capacitors, inductors, and resistors.
In 2008, researchers at Hewlett-Packard (HP) Labs developed the first working model of memristor, which was reported in Nature (May 1st , 2008).
In addition, Dr. Chua is an IEEE fellow and has received numerous awards including the IEEE Kirchhoff Award, the IEEE Neural Network Pioneer Award, the IEEE Third Millennium Medal, and the Top 15 Most Cited Author in Engineering Award.
2014.04.21 View 9274 -
KAIST Wins First Prize at Recon Challenge of Int"l Magnetic Resonance Society
Professor Jong-chul Ye of the Department of Bio and Brain Engineering and Hong Jeong, a doctorate student, won the first prize at the Recon Challenge held as part of a workshop sponsored by the International Society for Magnetic Resonance in Medicine (ISMRM) held in Sedona, the United States.
The workshop took place under the theme of “data sampling and image reconstruction” on Jan. 25-28 in Sedona, Arizona, the United States. The KAIST team beat out major magnetic resonance imaging groups from the U.S. and Europe.
The Recon Challenge is a biennial competition highlighting different reconstruction strategies and metrics to compare them. ISMRM is an international, nonprofit, scientific association which promotes communication, research, development, and applications in the field of magnetic resonance in medicine and biology and other related topics.
At the competition, the KAIST team presented a new dynamic MRI algorithm called k-t FOCUSS that is optimal from a compressed sensing perspective. The main contribution of the method is extension of k-t FOCUSS to a more general framework with prediction and residual encoding. The prediction provides an initial estimate while the residual encoding takes care of the remaining residual signals.
2009.02.06 View 12832