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Source channel @githubtrending · Post #14659 · May 1

#cplusplus#arm#convolution#deep_learning#embedded_devices#llm#machine_learning#ml#mnn#transformer#vulkan#winograd_algorithm MNN is a lightweight and efficient deep learning framework that helps run AI models on mobile devices and other small devices. It supports many types of AI models and can handle tasks like image recognition and language processing quickly and locally on your device. This means you can use AI features without needing to send data to the cloud, which improves privacy and speed. MNN is used in many apps, including those from Alibaba, and supports various platforms like Android and iOS. It also helps reduce the size of AI models, making them faster and more efficient. https://github.com/alibaba/MNN

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DOFH - DevOps from hell

@dofh_ru · Post #3570 · 02/05/2025, 05:54 PM

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Here we go again! SEV-SNP is vulnerable, again. New AMD SEV-SNP vulnerability: https://github.com/google/security-research/security/advisories/GHSA-4xq7-4mgh-gp6w Exploit: https://github.com/google/security-research/tree/master/pocs/cpus/entrysign Reports about two recent vulnerabilities in SEV-SNP memory encryption and isolation mechanism, on CPU pipeline, cache and branch prediction level: https://www.amd.com/en/resources/product-security/bulletin/amd-sb-3019.html https://www.amd.com/en/resources/product-security/bulletin/amd-sb-3010.html AMD reported that previous approaches to Spectre class attacks will work to fix new vulnerabilities: https://www.amd.com/content/dam/amd/en/documents/epyc-technical-docs/tuning-guides/software-techniques-for-managing-speculation.pdf #cVM #TEE #SEV #SNP #SEV_SNP #AMD

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