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.
According to the American Trucking Associations (ATA), at current trends the driver shortage could surpass 160,000 by 2030. ATA estimates that, in the next decade, the industry will have to recruit nearly a million new drivers into the industry to replace drivers exiting the field due to retirements, driver burn-out, compensation and poor benefits. These are the challenges facing transportation executives in securing a robust driver pool.
However, the challenge of driver shortages does not end with the trucking industry. Rather, the scarcity of drivers directly affects the larger manufacturing sector.
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