via Daily Kiran
A DGIST research team has developed a high-reliability artificial electronic synaptic device that simulates neurons and synapses.
A research team led by Director Myoung-Jae Lee from the Intelligent Devices and Systems Research Group has succeeded in developing an artificial synaptic device that mimics the function of the nerve cells (neurons) and synapses that are response for memory in human brains.
Synapses are where axons and dendrites meet so that neurons in the human brain can send and receive nerve signals; there are known to be hundreds of trillions of synapses in the human brain.
This chemical synapse information transfer system, which transfers information from the brain, can handle high-level parallel arithmetic with very little energy, so research on artificial synaptic devices, which mimic the biological function of a synapse, is under way worldwide.
Dr. Lee’s research team, through joint research with teams led by Professor Gyeong-Su Park from Seoul National University; Professor Sung Kyu Park from Chung-ang University; and Professor Hyunsang Hwang from POSTEC, developed a high-reliability artificial synaptic device with multiple values by structuring tantalum oxide a trans-metallic material into two layers of Ta2O5-x and TaO2-x and by controlling its surface.
The artificial synaptic device developed by the research team is an electrical synaptic device that simulates the function of synapses in the brain as the resistance of the tantalum oxide layer gradually increases or decreases depending on the strength of the electric signals. It has succeeded in overcoming durability limitations of current devices by allowing current control only on one layer of Ta2O5-x.
In addition, the research team successfully implemented an experiment that realized synapse plasticity, which is the process of creating, storing, and deleting memories, such as long-term strengthening of memory and long-term suppression of memory deleting by adjusting the strength of the synapse connection between neurons.
The non-volatile multiple-value data storage method applied by the research team has the technological advantage of having a small area of an artificial synaptic device system, reducing circuit connection complexity, and reducing power consumption by more than one-thousandth compared to data storage methods based on digital signals using 0 and 1 such as volatile CMOS (Complementary Metal Oxide Semiconductor).
The high-reliability artificial synaptic device developed by the research team can be used in ultra-low-power devices or circuits for processing massive amounts of big data due to its capability of low-power parallel arithmetic. It is expected to be applied to next-generation intelligent semiconductor device technologies such as development of artificial intelligence (AI) including machine learning and deep learning and brain-mimicking semiconductors.
Dr. Lee said, “This research secured the reliability of existing artificial synaptic devices and improved the areas pointed out as disadvantages. We expect to contribute to the development of AI based on the neuromorphic system that mimics the human brain by creating a circuit that imitates the function of neurons.”
Learn more: Artificial Synaptic Device Simulating the Function of Human Brain
The Latest on: Artificial synapses
via Google News
The Latest on: Artificial synapses
- "Protonic" artificial synapse runs a million times faster than human oneson August 4, 2022 at 1:24 am
Engineers at MIT have developed a new type of artificial synapse that’s extremely energy efficient and ultra-fast, processing data a million times faster than synapses in the human brain.
- New hardware offers faster computation for artificial intelligence, with much less energyon August 3, 2022 at 10:29 am
By repeating arrays of programmable resistors in complex layers, researchers can create a network of analog artificial "neurons" and "synapses" that execute computations just like a digital neural ...
- MIT has created new AI 'neurons' 1 million times faster than the brainon August 3, 2022 at 4:42 am
MIT researchers have created new artificial 'neurons' and 'synapses' to enable analog deep learning with artificial intelligence.
- MIT’s New AI Chip Is 1 million Times Faster Than The Synapses In Human Brainon August 2, 2022 at 5:36 am
A team of researchers with the Massachusetts Institute of Technology (MIT) has been working to push the speed limits of a type of a previously developed ...
- MIT Researchers Create Artificial Synapses 10,000x Faster Than Biological Oneson August 1, 2022 at 1:48 pm
By building chips whose components act more like natural neurons and synapses, we might be able to approach the efficiency of the human brain.
- MIT’s New Analog Synapse Is 1 Million Times Faster Than the Synapses in the Human Brainon July 31, 2022 at 1:21 pm
New Hardware Delivers Faster Computation for Artificial Intelligence, With Much Less Energy MIT engineers working on “analog deep learning” have found a way to propel protons through solids at ...
- ‘Artificial synapse’ could make neural networks work more like brainson July 31, 2022 at 12:01 am
This functions a bit like a synapse, a connection between two neurons, where ions flow in one direction to transmit information. But these “artificial synapses” are 1000 times smaller and ...
via Bing News