Abstract: Quantization of local model updates before uploading to the parameter server is a primary solution to reduce the communication overhead in federated learning. However, prior literature ...

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Abstract: Modern datasets often exhibit heavy-tailed behavior, while quantization is inevitable in digital signal processing and many machine learning problems. This paper studies the quantization of ...

This article has been edited and created by AI. Memory Optimization for Vulkan Backend (contiguous buffer fast path) and Progress in KvN KV Cache Quantization — Latest llama.cpp Vulkan News llama.cpp ...

SEOUL, South Korea, June 11, 2026 /PRNewswire/ -- Nota AI, a company specializing in AI model compression and optimization, announced that two of its papers on MoE-specific quantization algorithms ...

Two papers on MoE-specific quantization algorithms accepted at a workshop held in conjunction with ICML 2026 Recognition follows Nota AI's overall win at the NVIDIA Nemotron Hackathon Strengthening ...

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Tesla FSD Hardware 3 owners received FSD v14 Lite on June 29, ending a 16-month freeze for roughly 4 million vehicles. The ...

Vienna startup Ora Computing raised €3.5M and proved a 70-billion-parameter large language model can be compressed for under ...

Daisy-chaining two of Dell's Nvidia GB10 DGX Spark systems didn't just pump up my home AI lab—it fundamentally changed how I ...