Neural
Asymmetric Certified Robustness via Feature-Convex Neural Networks
Asymmetric Certified Robustness via Feature-Convex Neural Networks TLDR: We propose the asymmetric certified robustness problem, which requires certified robustness for only one class and reflects real-world adversarial scenarios. This focused setting allows us to introduce feature-convex classifiers, which produce closed-form and deterministic certified radii on the order of milliseconds. Figure 1. Illustration of feature-convex classifiers…
Neural Processing Units (NPUs): The Driving Force Behind Next-Generation AI and Computing
Just as GPUs once eclipsed CPUs for AI workloads, Neural Processing Units (NPUs) are set to challenge GPUs by delivering even faster, more efficient performance—especially for generative AI, where massive real-time processing must happen at lightning speed and at lower cost. The question is how do NPUs work, and why are they edging out their…