Generative, Inferencing and Natural Language Processing (NLP) AI applications have all seen explosive growth (NVIDIA market cap growth 3200%) and rapid proliferation in the last two years across commercial market segments such as Automotive, Aerospace, Manufacturing, Transportation, Banking, and Entertainment. The commercial consumption of AI has quite directly driven the need for High Performance Compute (HPC) solutions, and, specifically HPC solutions that operate in some of the most extreme environments on earth. By comparison, DOD compute systems for air/ground platforms, while significantly ruggedized for austere environments, lack the compute power to employ such technological advancements in AI…or worse, lack the capability to counter AI threats employed by adversaries using commercially available SW/HW.
The rapid onset of AI is managing its ways into every facet of our lives. It is unlikely you can go a day, or even hour, without in some way connecting with, using, or hearing about AI. This is especially true in Edge Processing markets where AI is integrated in vehicles and platforms in the environments we work and play in.
HPC systems are characterized by their high-speed processing power, high-performance networks, and large-memory capacity, generating the capability to perform massive amounts of parallel processing. When a standard desktop with a 3 GHz processor can perform around 3 billion calculations per second, an average HPC system can perform quadrillions of calculations per second. This means HPC systems perform extreme amounts of calculations in seconds, whereas a regular processor would take weeks or even months to complete the same task, thanks to their technology.
In my last blog post, What is the Workhorse Advancing HPC at the Edge?, I highlightedhowenterprise applications requiring the highest endcomputefor theirAIworkloads at the Edge areleveragingdata-center grade NVIDIA GPUs to get even greater performance.Processing and storing datacloser to where the action takes place means a decision can be made more quickly,producing reduced latency, improved security, greater reliability, andmuchhigherperformance.In this blog,I’llbe covering the transitionfromusingbigpower-hungryGPUs to smaller form factorelectronic control units, better known as ECUs, at the very edge.
In the ever-evolving landscape of modern warfare, the United States Department of Defense (DoD) is at the forefront of developing advanced capabilities to maintain superiority on the battlefield. The Joint All-Domain Command and Control (JADC2) initiative has emerged as a critical framework for enabling real-time data sharing, decision-making, and operational coordination across all military branches and domains. One Stop Systems (OSS), a leading provider of high-performance computing solutions, has positioned itself as a key player in supporting JADC2 applications with their innovative and powerful hardware offerings.
The integration of Artificial Intelligence (AI) into warfare has revolutionized the technological landscape of modern military operations. AI-driven systems are capable of autonomously processing data, making intelligent decisions, and executing complex tasks with precision. In this blog article, we provide a comprehensive overview of the current capabilities of AI in warfare, explore future possibilities, and examine the challenges faced by the underlying hardware.
