PoV on Top Considerations for Designing AI Inference Chips
AI inference workloads are becoming more compute-intensive, with higher demands on throughput, memory access, and power…
-
-
Applying MLOps to Industrial Water Pump Anomaly Detection
In an industrial environment, readings are continuously generated by water pumps. Every minute…
-
From AI Chips to AI Systems: What Customers Really Need Today
AI hardware has developed fast. Every new product comes with promises of more power, bigger memory, or better energy use…
-
How Can Agentic AI Wearables Enable Proactive Health Monitoring and Elderly Care?
On a hot summer day in Austin, 72-year-old Arthur is working in the garden. After a while, he starts feeling uneasy as he has been..
-
Securing Medical IoT Devices with an MLOps Automated Pipeline
Medical devices like smart infusion pumps and connected heart monitors keep patients safe every day…
-
Matter Certification Checklist for OEMs
The smart home industry has made great progress with more products carrying the Matter certification…
-
Memory-Aware ASIC Design for AI Workloads
Recently, AI processors have seen significant improvements in computing power due to specialized units such as NPUs…
-
The Enterprise Blueprint for Scalable MLOps Orchestration
Getting a machine learning model to work in a Jupyter notebook is easy. The hard part and where most enterprise projects…
-
Defining Automotive Functional Safety through Hardware to AI
This includes pedestrian detection, lane keeping, over-the-air updates, cloud integration, and decision-making…
-
Accelerating AI-Powered Wearable Device Development with a Reusable Blueprint
The wearable technology industry has undergone a drastic transformation in recent times. Starting with basic…
