ASUS recently launched the new USB-form-factor AI acceleration card UGen300, breaking traditional hardware deployment barriers with a revolutionary design: no need to open the case, no PCIe slots required. With just a single USB 3.1 Gen2 cable, it can provide up to 40 TOPS of local AI inference capability for regular PCs, industrial computers, and even ARM development boards.

The core of UGen300 is a Hailo-10H neural network processor (NPU) from Israeli chip company Hailo. It achieves high performance per watt with a typical power consumption of only 2.5 watts. The device is equipped with 8 GB LPDDR4 memory, allowing direct loading and running of large pre-trained models, avoiding frequent use of host resources. Its compatibility covers mainstream computing ecosystems - supporting x86 and ARM architectures, operating systems including Windows, Linux, and Android, and development frameworks fully compatible with mainstream standards such as TensorFlow, PyTorch, and ONNX.

Notably, ASUS has pre-integrated over 100 ready-to-use pre-trained models for UGen300, focusing on advanced image recognition, object detection, semantic segmentation, and pattern analysis. It is suitable for various fields such as intelligent security, industrial quality inspection, medical image assistance, and edge AI education. Users do not need to train from scratch; they can use it immediately upon insertion, significantly reducing the complexity of AI deployment.

This product marks the arrival of the "consumer-grade plug-and-play" era in AI acceleration. Local AI inference that previously required professional servers or customized embedded solutions can now be achieved through a device the size of a USB drive. Although ASUS has not yet announced the price and release date, the technical approach represented by UGen300 - low power consumption, high compatibility, no installation required, and strong ecosystem - undoubtedly opens a new path for the popularization of edge AI. When 40 TOPS of computing power is easily accessible, every regular computer could become the starting point for the next generation of smart applications.