NVIDIA released the Jetson Nano Development Kit at the 2019 NVIDIA GPU Technology Conference (GTC), a microcomputer now available to embedded designers, researchers, and DIY makers, delivering the power of modern AI in a compact, easy-to-use platform with full software programmability. Jetson Nano features a quad-core 64-bit ARM CPU and a 128-core integrated NVIDIA GPU, delivering 472 GFLOPS of computing performance. It also includes 4GB of LPDDR4 memory in an efficient, low-power package with 5W/10W power modes and 5V DC input
The newly released JetPack 4.2 SDK provides a complete desktop Linux environment for Jetson Nano based on Ubuntu 18.04 with accelerated graphics, support for NVIDIA CUDA Toolkit 10.0, and libraries such as cuDNN 7.3 and TensorRT. The SDK also includes the ability to natively install popular open source machine learning (ML) frameworks such as TensorFlow, PyTorch, Caffe, Keras, and MXNet, as well as frameworks for computer vision and robotics development such as OpenCV and ROS.
Full compatibility with these frameworks and NVIDIA's leading AI platform makes it easier than ever to deploy AI-based inference workloads to Jetson. Jetson Nano provides real-time computer vision and inference for a wide range of complex deep neural network (DNN) models. These capabilities support multi-sensor autonomous robots, IoT devices with intelligent edge analytics, and advanced AI systems. Even transfer learning enables retraining of networks locally on Jetson Nano using ML frameworks.
