Geoffrey Hinton from the University of Toronto gave this talk at the Vector Institute. “What is Wrong with ‘standard’ Convolutional Neural Nets? They have too few levels of structure: Neurons, Layers, and Whole Nets. We need to group neurons in each layer in ‘capsules’ that do a lot of internal computation and then output a compact result.”
[SPONSORED GUEST ARTICLE] Hammerspace, the company orchestrating the Next Data Cycle, unveiled the high-performance NAS architecture needed to address the requirements of broad-based enterprise AI….
The high-performance computing (HPC) market is witnessing a notable shift towards the cloud, partially driven by the benefits of enhanced energy efficiency. According to Hyperion Research nearly every organization running HPC workloads is either already using or investigating the cloud to accelerate application performance, with the cloud market for HPC workloads forecast to reach $11.5 […]
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