Researchers at the Korea Advanced Institute of Science and Technology (KAIST), led by Chair Professor Shinhyun Choi, have developed a programmable AI semiconductor that can adjust how it responds to data changing at different speeds. The programmable dynamic memtransistor (PDM) features a dual-layer structure combining a charge storage layer that accumulates and processes data with an electron-trapping layer that controls the device’s response speed. This design allows the PDM to adjust its response characteristics according to incoming data and retain those settings. During testing, researchers adjusted the device’s current recovery time across an approximately five-fold range, and its characteristic frequency could be controlled across a range of more than 10-fold. In experiments involving data with fast and slow changes occurring together, the PDM reduced prediction errors by as much as 40 times compared with conventional semiconductor devices with fixed response characteristics. The technology also processed information accurately when the speed of handwriting or object movement varied. KAIST researchers fabricated an integrated PDM array and used it to predict complex data, achieving accuracy comparable with conventional software-based approaches while using significantly less energy. The technology could support more efficient real-time AI processing in applications including autonomous vehicles, robots, and wearable devices.