Medical AI - Diagnosing in Real-Time at the Edge

By:  Jaan Mannik – Director of Commercial Sales The term AI, or Artificial Intelligence, is everywhere nowadays and has quietly woven itself into the fabric of our daily lives. It powers the recommendations we see on streaming platforms, the navigation apps that guide us through traffic, and even the virtual assistants that answer our questions in seconds. From optimizing energy use in smart homes to predicting market shifts in finance, AI has become the invisible engine driving convenience, efficiency, and insight across industries. In manufacturing, AI-driven robots collaborate with humans to streamline production. In agriculture, machine learning models monitor crops, forecast yields, and conserve resources. Retailers use predictive analytics to anticipate consumer needs before customers even express them. The reach of AI is no longer confined to futuristic labs, it’s in our phones, vehicles, and cities, constantly learning and adapting to serve us better.

High Speed Performance for Sensors

OSS PCIe-based products deliver critical advantages for modern military sensor systems by enabling real-time data acquisition, processing, and transmission in rugged, mission-critical environments. These benefits stem from their ability to support high-bandwidth, low-latency interconnects, modular scalability, and environmental resilience, all of which are essential for today’s advanced military platforms.

Agile Infrastructure: Scaling More Efficiently

Companies today are being asked to do more with data than ever before. Bigger AI models, faster insights, and workloads that don’t stay in one place, it’s a lot to keep up with. Traditional infrastructure just isn’t built for this kind of speed and flexibility. The answer isn’t about throwing more hardware at the problem. It’s about building smarter, more agile infrastructure that adapts as demands change. And that’s where scale-out and increasingly, a blend of scale-out and scale-up come into play.

Ponto PCIe Accelerator Infographic

Leveraging NVIDIA MGX to Accelerate Rugged Edge System Design

The rugged edge computing landscape is becoming increasingly complex with new generations of technologies, such as the latest AI focused GPUs, releasing annually rather than every 2-3 years. Whether the end application is commercial or defense, rugged edge servers must not only deliver cutting-edge compute performance but also withstand extreme environmental conditions.

Tackling the Thermal Challenge of 600W+ Devices in High-Density Computing Systems

  When the PCI-SIG formally added support for 675W add-in card devices in the PCI Express Card Electromechanical (CEM) specification in August 2023, NVIDIA’s most powerful CEM GPU, the NVIDIA H100 80GB had a maximum power consumption of 350W.  While some devices were starting to push the limits of datacenter thermodynamics – high density systems of many 675W devices seemed like a distant reality.  However, with power constraints uncapped and the need for higher performing GPUs skyrocketing, the industry quickly came out with devices taking full advantage of the new specification capability.  NVIDIA quickly replaced the H100 80GB with the H100 NVL, increasing power density to 400W.  While this small jump was manageable for existing installations, NVIDIA then dove all-in with the H200 NVL released in late 2024 at 600W.  The rapid transition from 350W to 600W has put power and cooling technologies in the spotlight in a race to solve this next generation challenge.

The Future of Transportation: Will Autonomous Trucks Ever Make the Driver Obsolete?

The advent of technology has always brought about significant changes to various industries, and the transportation sector is no exception. Among the most transformative innovations in recent years is the development of autonomous vehicles, particularly trucks. The potential for autonomous trucks to revolutionize freight transport is immense, raising the fundamental question: will these technological advancements make human drivers obsolete? To explore this question, we must consider the current state of autonomous driving technology, the economic implications, and the societal impact of removing human drivers from the equation.

Advantages and Disadvantages of Implementing AI Inference Nodes on Soldiers

The integration of artificial intelligence (AI) into military operations has revolutionized battlefield strategies, decision-making, and operational efficiency. Among these advancements, AI inference nodes deployed directly on soldiers represents a cutting-edge innovation. These nodes, compact computational devices, enable real-time AI processing and analytics, empowering soldiers with enhanced situational awareness, decision support, and operational effectiveness. However, such technology also brings challenges, particularly in power management, size, and weight constraints. This blog delves into the advantages and disadvantages of implementing AI inference nodes on soldiers, focusing on these critical aspects.

Composable Infrastructure: Dynamically Changing IT Infrastructure

The evolution of IT infrastructure spans several decades and is marked by significant advancements in computing technology, networking, storage, and management practices. Data Centers have historically relied on Converged or Hyper-Converged infrastructures when deploying their hardware which proved to limited in flexibility, efficiency, scalability, and support for the Artificial Intelligence / Machine Learning (AI/ML) modern workloads of today.