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OSS featured in the Aerospace & Defense Review magazine

OSS featured in the Aerospace & Defense Review magazine

AEROSPACE & DEFENSE REVIEW - The Business and Technology Magazine for A&D industry featured One Stop Systems in their latest Q&A industry review. Read the Full Article HERE.

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How the Scarcity of Truckers Hurts Manufacturing (And How to Fix the Problem)

How the Scarcity of Truckers Hurts Manufacturing (And How to Fix the Problem)

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.

To read the full article click here.

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Designing Transportable, High-Performance AI Systems for the Rugged Edge

Designing Transportable, High-Performance AI Systems for the Rugged Edge

System design requirements are well understood for high-performance artificial intelligence applications destined to reside in enterprise or cloud data centers. Data centers are specifically designed to provide a clean, cool environment with stable and standard power with no need to worry about vibration or shock loads.

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Scalable Inferencing for Autonomous Trucking

Scalable Inferencing for Autonomous Trucking

Most AI inferencing requirements are outside the datacenter at the edge where data is being sourced and inferencing queries are being generated. AI inferencing effectiveness is measured by the speed and accuracy with which answers are provided, and, in many applications, real-time response is required.  To meet the objectives of many AI applications, a very large number of inferencing queries need to be serviced simultaneously.  Often many different inferencing models answering different types of queries need to be coordinating in parallel.

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Deploying Artificial Intelligence where the ‘Rubber meets the Road’

Deploying Artificial Intelligence where the ‘Rubber meets the Road’

A long-haul truck cruises by you on Interstate 10 in west Texas. You get a brief wave from the driver who seems unfocused on the road ahead.  It’s hot and the road is bumpy. You didn’t realize it but you just encountered an autonomous driving truck in development, testing out the latest version of its Artificial Intelligence algorithms.  The truck is loaded with unseen video cameras, lidar, radar and infer-red sensors.  As it travels along it is seeing its environment and its on-board computers are making the thousands of little decisions that keep it moving safely to its prescribed destination.  The driver is a safety layer that will be removed in future iterations of the design.

 

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Edge NVMe Storage for Autonomous Vehicles

Edge NVMe Storage for Autonomous Vehicles

Adoption of the latest HPC and AI technologies in autonomous vehicles is creating a surge in vehicle real-time data processing capabilities.  The growth in number, speed and resolution of vehicle sensors and related compute performance in autonomous vehicles has in turn led to increased demand for high-capacity, high-throughput storage.  Effective storage within autonomous vehicles must meet three primary criteria: throughput to match the capture and processing rates, a rapid data transfer workflow for offloading the captured data, and a rugged environmental design to operate in any autonomous vehicle conditions.

To read the full article click here.

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