Tim Miller of One Stop Systems highlights a new approach - AI on the Fly - where specialized high-performance accelerated computing resources for deep learning training move to the field near the data source. One Stop Systems asserts moving AI compute to the data is another important step in realizing the full potential of AI.
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The impact of artificial intelligence is starting to be realized across a broad spectrum of industries. Typically, deep learning (DL) training is a centralized datacenter process and inferencing occurs in the field. To build an AI system, data is collected, run through data scientist training models based on deep learning (DL) frameworks - on the fastest accelerated computers in the world - with the output sent to the field for an "AI at the Edge" system to inference from this model in day-to-day decision making.
OSS released its flagship artificial intelligence (AI) transportable compute server, the Rigel Edge Supercomputer, according to the company this month.
With a dense form factor, the Rigel is designed for deployments in "tight spaces" at the edge, such as an equipment bay of autonomous vehicles, within mobile command centers, under seats of helicopters, or in an aircraft equipment bay.
Bridging the gap between sensors and high-performance compute power is a growing challenge, especially in systems where quick, complex decisions are vital.
The concept of "the edge" in embedded systems has taken on new urgency in the federal space. "The edge" can be defined as "where it's happening" and in government systems, that's the field.