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04 · MODULES

Plug-in Modules

Self-contained Physical AI add-ons for courses not primarily focused on AI — drop one in for 1–2 weeks of hands-on physical computing.

C++

AI-aware memory management

AI 인식 메모리 관리

Efficient C++ patterns for inference workloads — stack vs. heap, arena allocators, and avoiding dynamic memory on bare-metal targets.

C++ 3 weeks
IOT

Sensor fusion fundamentals

센서 융합 기초

Kalman filters and multi-sensor pipelines — plug into any IoT course to add a Physical AI dimension.

IoT 2 weeks
DATABASE

Time-series data for physical systems

물리 시스템 시계열 데이터

InfluxDB and real-time sensor logging — adds a physical AI data layer to any database course.

Database 2 weeks
CIRCUITS

Neural network hardware mappings

신경망 하드웨어 매핑

How circuit theory underlies Physical AI acceleration chips — MAC arrays, memory bandwidth, and power analysis.

Circuits 1 week

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PAI LAB PHYSICAL AI LAB

Open research at the intersection of machine intelligence and the physical world. Jeonju, Korea · Est. 2025

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