The South Korean team used IGZO to make artificial intelligence chips

The device can train and classify hand-written data with over 98% accuracy, a research team at Pohang University of Science and Technology (POSTECH) has developed a high-performance AI semiconductor device using indium gallium zinc oxide (IGZO). The research is in the journal Advanced Electronic Materials.

Efficient AI operations, such as those of ChatGPT, need to be computed in the memory responsible for storing the information. Unfortunately, previous AI semiconductor technologies have been limited in meeting all the requirements, such as linear and symmetric programming and consistency, to improve AI accuracy.

The researchers looked for IGZO as a material for AI calculations that could be mass-produced and provide uniformity, durability, and computational accuracy. The compound has excellent electron mobility and leakage current characteristics, which makes it a key technology for OLED displays.

Using this material, a team led by Yoonyoung Chung, Seyoung Kim, and Seongmin Park developed a novel synaptic device consisting of two transistors interconnected via a storage node. The precise control of the charging and discharging speed of this node enables the AI semiconductor to meet various performance indicators required for high levels of performance, they said. In addition, the application of synaptic devices to large-scale AI systems requires minimizing the output current of synaptic devices.

Connect two oxide semiconductor transistors; One for writing and the other for reading. The researchers confirmed the possibility of using ultra-thin film insulators inside transistors to control electrical current, making it suitable for large-scale artificial intelligence. They used a newly developed synaptic device to train and classify handwritten data, achieving an accuracy of more than 98%, which validates its potential application in future high-precision AI systems.

Chung explains; "The significance of my research team's achievement is that we overcome the limitations of traditional AI semiconductor technologies, which focus solely on materials development. To do this, we use materials that are already in mass production. In addition, linear and symmetrical programming properties are obtained by using two transistors as a new structure for a synaptic device. Therefore, the successful development and application of our new AI semiconductor technology shows great potential to improve the efficiency and accuracy of AI."

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