Are We Underestimating Small Edge AI Models?
A developer has created an Android feature that recognizes Morse code from images and live camera feeds using a small, on-device AI module. This module, weighing under 5 MB, operates entirely offline and utilizes LiteRT for inference. The project involved building the entire ML pipeline from scratch, including data collection, model training on a personal GPU with TensorFlow/Keras, and mobile optimization. This work highlights the potential of small, specialized AI models for practical, local applications, questioning whether the focus on large foundation models overlooks these efficient solutions. AI
IMPACT Highlights the potential of small, specialized AI models for practical, offline applications on mobile devices.