Nvidia Jetson Gives Generative AI It's Own Platform

 

Now here’s a switch: Nvidia hobbyist AI computers, supporting generative artificial intelligence apps (chatbots, for example) created using the Nvidia Jetson platform. 

The new machines are designed for hobbyists, commercial AI developers, and students to create AI applications, including chatbots and robotics, for example. 

Jetson modules are optimized for running AI models directly on embedded systems, reducing the need for sending data back and forth to the cloud, crucial for real-time decision-making in applications such as robotics, drones, autonomous vehicles, smart cameras, and industrial Internet of Things, for example. 

The developer kit features an NVIDIA Ampere architecture GPU and a 6-core Arm CPU, supporting multiple edge AI applications and high-resolution camera inputs and sells for about $250. 

 The Jetson modules are designed to enable edge AI applications that require real-time, high-performance processing at the edge rather than in a centralized cloud environment. Use cases might include autonomous vehicle real-time image and sensor data processing to enable navigation and decision-making. 

Robotics use cases include object recognition, motion planning, and human-robot interaction. The modules also can support smart cameras for security applications that require object detection, face recognition, and anomaly detection. 

Industrial Internet of Things use cases include the monitoring of machinery and systems used for real-time analysis. Unmanned aerial vehicles use cases include visual navigation, obstacle avoidance, and image-based inspection. 

At least in one respect, the Jetson is a sort of upside-down case of computer development. Personal computers started out as hobbyist machines entirely for edge computing (though we did not use the term at the time). 

Connected computing at remote locations (cloud computing) developed later. For AI, sophisticated remote processing in the cloud or enterprise-style data centers happened first, and now we get development of platforms aimed strictly at edge, “autonomous” computing without the requirement for connection to remote processing.