Changes In Chip Architectures At The Edge


Edge computing is all about low latency, within a tight power budget, and with sufficient performance. This is very different from an AI data center, where the real focus is on data throughput between processor and memory. Achieving those goals requires a focus on what different processing elements bring to the table. Nigel Drego, co-founder and CTO of Quadric, talks about how these different c... » read more

AI Workloads at the Edge: Ensuring Performance, Privacy, and Security


Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss why some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president a... » read more

Next Generation AI: Transitioning Inference from the Cloud to the Edge


Deploying AI inference at the edge—on smartphones, appliances, industrial devices, and vehicles—promises faster, private, and energy-efficient intelligence. Expedera’s packet-based NPU architecture delivers up to 90% utilization and dramatic reductions in memory movement compared to conventional approaches, enabling next-generation real-time AI capabilities. This white paper examines tech... » read more

Optimizing AI Workloads For Edge Computing


Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss how some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president an... » read more

Edge AI Safety: Agentic AI Architecture That Leverages 3D To Integrate A Dedicated Safety Layer (Princeton, HKUST, NC State Univ.)


A new technical paper titled "3D Guard-Layer: An Integrated Agentic AI Safety System for Edge Artificial Intelligence" was published by researchers at Princeton University, Hong Kong University of Science and Technology, and North Carolina State University. Abstract "AI systems have found a wide range of real-world applications in recent years. The adoption of edge artificial intelligence, ... » read more

Moving AI Workloads To The Edge


Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss how some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president an... » read more

Cloud vs. Edge Gaming: Performance Gap Is Shrinking


Chip designers and gaming companies are scrambling to figure out whether the gaming market will tilt toward the cloud, the edge, or some combination of both. Multi-gigabit internet allows more people to play high-end games in the cloud, but edge-based gaming consoles and devices remain well-rooted, more secure, and private. Which one wins? So far, there are more questions than answers. Handh... » read more

Re-Architecting AI For Power


The industry is becoming increasingly concerned about the amount of power being consumed by AI, but there is no simple solution to the problem. It requires a deep understanding of the application, the software and hardware architectures at both the semiconductor and system levels, and how all of this is designed and implemented. Each piece plays a role in the total power consumed and the utilit... » read more

Edge AI: Enabling Smart IoT Applications


As industries race to unlock the next wave of innovation, edge AI is emerging as a game-changer—bringing intelligent, real-time data processing directly to the device level across industries. ‘Edge AI: Enabling Smart IoT Applications’ is your in-depth guide to the transformative potential of artificial intelligence at the edge. This insightful eBook explores 15 powerful use cases that ... » read more

Report: The AI Efficiency Boom


Artificial Intelligence (AI) is undergoing a fundamental transformation. While early AI models were large, compute-heavy, and dependent on cloud processing, a new wave of efficiency-driven innovations is moving AI inference—the generation of model results—to the edge. Smaller models, improved memory and compute performance, and the need for privacy, low latency, and energy efficiency are dr... » read more

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