Enabling Physical AI and Robotics: Platform for the Intelligent Edge


Physical AI has emerged as an essential technology driving the future of robotics — it closes the loop between perception, reasoning, and action in the real world using powerfully trained AI models. But for robots and autonomous machines, that loop only works well if it runs where the world is actually sensed: at the Edge. Instead of streaming raw sensor data to a data center for interpretati... » read more

25G Ethernet: Scaling Data Movement For ADAS, Industry 4.0, And 5G Systems


The automotive and industrial markets are undergoing rapid transformation, driven by Advanced Driver Assistance Systems (ADAS) adoption, Industry 4.0 automation, and the rollout of 5G infrastructure. These trends are driving an unprecedented demand for edge AI capabilities and connectivity, with the global Edge AI IC market projected to grow at a 34.7% CAGR and reach $340B by 2034 [1]. Traditio... » read more

Power, Not Area: Why Edge GPU Design Is Entering A New Era


For decades, semiconductor progress followed a familiar playbook: shrink the node, pack in more logic, raise the clock, and performance would follow. That model held remarkably well, and possibly much longer than it should have. As the industry moves below 2nm, GPU design is running into a hard physical reality. The limiting factor is no longer how much logic we can fit on a die. It’s how ... » read more

Edge And Micro Data Centers: Powering The Real-Time Digital World


The modern world no longer runs on delayed responses. It runs on immediacy. When a self-driving vehicle identifies a pedestrian, when a factory robot adjusts production in milliseconds, or when an augmented reality overlay appears instantly during remote surgery, there is no tolerance for latency. These applications demand data processing that happens almost at the speed of human reflexes. B... » read more

AI Moves Out Of The Cloud And Onto The Edge


The impact of AI to date, in the cloud, is undisputed, but the question we must answer going forward is whether we can only expect more of the same or whether there is a fundamental shift looming that will change everything. Today, we will explore historical data to find patterns repeated through the ages to help us see what I will attempt to prove is imminent. A brief history of time… keepi... » read more

Next Generation AI: Transitioning Inference From The Cloud To The Edge


AI inference deployments are increasingly focused on the edge as manufacturers seek the consistent latency, enhanced privacy, and reduced operational costs they can’t achieve in cloud-based deployments. While cloud-based platforms provide incredible computational power and enable widely adopted services, the dependence on network connectivity inherently creates variability, cost and security ... » read more

Why Openness Matters For AI At The Edge


AI continues to migrate towards the edge and is no longer confined to the data center. Edge AI brings several key advantages, delivering intelligence closer to where data is generated, improving latency for critical functions, ensuring privacy by limiting transmitted data, and reducing energy consumption for AI. Edge AI encompasses systems performing AI inferencing directly where data is cre... » read more

Breaking The Compromise: Low Power And High Performance For The Intelligent Edge


By 2030, over 75 billion devices will be connected worldwide, each expected to think, learn, and respond instantly (Statista, IoT Connected Devices Forecast). The world is connecting faster than ever. With tens of billions of smart devices coming online, intelligence can no longer live in the cloud alone. Edge AI is emerging as the new frontier, bringing smarter, safer, and more res... » read more

Co-Optimizing GPU Architecture And SW To Enhance Edge Inference Performance (NVIDIA)


A new technical paper titled "EdgeReasoning: Characterizing Reasoning LLM Deployment on Edge GPUs" was published by researchers at NVIDIA. Abstract "Edge intelligence paradigm is increasingly demanded by the emerging autonomous systems, such as robotics. Beyond ensuring privacy-preserving operation and resilience in connectivity-limited environments, edge deployment offers significant energ... » read more

Enabling The Future: Heterogeneous Integration From Connected Devices To Data Centers


The digital landscape is evolving at an unprecedented pace. From smartphones and wearables to autonomous vehicles and hyperscale data centers, the demand for faster, smarter, and more efficient electronics is reshaping the semiconductor industry. At the core of this transformation is heterogeneous integration—the convergence of multiple technologies, functions, and components into unified sys... » read more

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