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Source channel @githubtrending · Post #15271 · Nov 5

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite

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Crypto M - Crypto News

@CryptoM · Post #64625 · 04/09/2026, 11:54 AM

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🚀 Independent Miner Achieves Rare Bitcoin Block Discovery An independent Bitcoin miner achieved a rare feat by successfully mining a Bitcoin block with a very low probability. According to BlockBeats, the miner used CKpool's solo mining software to mine block number 944,306, earning a total of 3.128 Bitcoin. Data from block explorer Mempool indicates that the miner received a block subsidy of 3.125 Bitcoin and transaction fees amounting to 0.003 Bitcoin. CKpool developer Con Kolivas noted on the X platform that the miner accomplished this with just 70TH of computing power. The probability of a miner of this scale discovering a block daily is approximately one in 100,000, with an average occurrence of once every 300 years. #Bitcoin#mining#CKpool#blockchain#rarefeat#blockdiscovery#cryptocurrency#soloMining#Mempool#transactionfees#ConKolivas#BTC

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