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Source channel @githubtrending · Post #14747 · May 25

#python#deep_learning#intel#machine_learning#neural_network#pytorch#quantization Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models. https://github.com/intel/intel-extension-for-pytorch

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AI & Law

@ai_and_law · Post #256 · 03/07/2024, 08:04 AM

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Mozilla Foundation Study Raises Concerns on Watermarking AI Content Hello everyone! In a study released by the Mozilla Foundation, the challenges of identifying synthetic content online have been brought to light. Titled "In Transparency We Trust? Evaluating Watermarking and Labeling AI-Generated Content," the study delves into the effectiveness of various methods, including watermarking and labeling, in differentiating between synthetic and authentic content. The study, which conducted a comprehensive assessment of seven methods, both machine-readable and human-facing, revealed alarming findings: none of the methods were rated as "good," indicating significant hurdles in accurately identifying synthetic content. Despite efforts to implement watermarking and labeling, the study underscores the persistent difficulties faced in combatting the proliferation of AI-generated content. #MozillaFoundation#AIContent#Watermarking

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