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Brain-Inspired Neuromorphic Cybersecurity System Detects ”Bad Apples” 100X Faster

Cybersecurity is critical—for national security, corporations and private individuals. Sophisticated cybersecurity systems excel at finding “bad apples” in computer networks, but they lack the computing power to identify the threats directly. Instead, they look for general indicators of an attack; call them “apples.” Or the system flags very specific patterns, such as “bad Granny Smith

Memory at the Core of New Deep Learning Research Chip

Over the last two years, there has been a push for novel architectures to feed the needs of machine learning and more specifically, deep neural networks. We have covered the many architectural options for both the training and inference sides of that workload here at The Next Platform, and in doing so, started to notice

FPGA Based Deep Learning Accelerators Take on ASICs

Over the last couple of years, the idea that the most efficient and high performance way to accelerate deep learning training and inference is with a custom ASIC—something designed to fit the specific needs of modern frameworks. While this idea has racked up major mileage, especially recently with the acquisition of Nervana Systems by Intel