Cloud-based AI dominates the headlines, but responsive and private interaction lies at the edge. This blog post shows how to build a fully offline, real-time voice assistant using the Arm-based NVIDIA ...
Memory bit cells — tiny storage elements within a chip — are typically unreliable at 0.5 volts or less. To solve this problem ...
A new technical paper, “Protonic nickelate device networks for spatiotemporal neuromorphic computing,” was published by researcher at UCSD and Rutgers University. Abstract “Computation in biological ...
The advantage of using CPO is that it positions optical connections much closer to the ASIC, GPU, or CPU, reducing the need for long and inefficient electrical traces. And while it’s not inherently ...
A compact, two-pin interface provides efficient access to debug and trace features while minimizing pin count.
The pace of AI innovation continues to expose a painful reality. Compute keeps scaling, but memory bandwidth remains one of the hardest bottlenecks to remove. As AI models grow larger and more complex ...
Three AI data center scaling strategies are scale-up, scale-out, and scale-across. Scale-up is within a rack; scale-out is between racks; scale-across is between data centers. Each of the three uses a ...
AI data centers are the engines of the new data revolution, transforming data lakes and extracting meaningful insights guided by user queries. In this white paper, we revisit the security problem and ...
D imaging radar enhances automotive sensing by adding elevation to traditional range, velocity, and azimuth measurements. This enables better target detection and classification, enabling safer ...
The high power density in turn produces large thermal gradients, with the low to max temperature changes increasing ...
Yield loss is increasingly driven by molecular variability in thin films, interfaces, and contamination rather than visible defects. Reliability issues often appear first as parametric drift or margin ...
The case for sharing test, manufacturing, and design data.
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