Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...

This article is based on findings from a kernel-level GPU trace investigation performed on a real PyTorch issue (#154318) using eBPF uprobes. Trace databases are published in the Ingero open-source ...

A new hybrid AI approach may drastically cut energy use while improving reliability. Artificial intelligence is not just changing software. It is also driving a sharp rise in electricity use. In the ...

This is why your phone never lasts all day anymore ...

Sparse tensors are the most used representation of sparse multidimensional data. Operations that decompose them, selecting their most important features while reducing their dimension, have become ...

Abstract: Functional tensor decomposition can analyze multidimensional data with real-valued indices, paving the path for applications in machine learning and signal processing. A limitation of ...

For more than a decade, Nvidia’s GPUs have underpinned nearly every major advance in modern AI. That position is now being challenged. Frontier models such as Google’s Gemini 3 and Anthropic’s Claude ...

Google has introduced multiple TPU generations, each optimized for specific workloads, from cost-efficient training to high-performance inference. The new Ironwood TPU is designed explicitly for ...

Google’s system leverages optical circuit switching (OCS) to create direct, low-latency optical paths between TPU chips, minimizing signal conversion losses. They avoid repeated ...

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