#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
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
#Scikit_learn is an open source Python library that implements a range of #machine_learning , preprocessing, cross-#validation and #visualization algorithms using a unified interface...
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Telegram Takes Over Blockchain Control
Telegram is ramping up its control over the TON blockchain by increasing the number of million-TON validators it operates. The minimum amount required to participate in validation has risen from 414K to 500K TON since December. This consolidation suggests a shift towards centralized management. Telegram has added 25 new validators in January, boosting its share of validators to over 66%. This move may simplify blockchain upgrades but raises concerns over decentralization. Telegram appears to be monetizing TON more directly, potentially selling it at discounts while maintaining income from accumulated TON investments.
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