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Source channel @githubtrending · Post #15141 · Sep 13

#python#large_language_models#machine_learning_systems#natural_language_processing Flash Linear Attention (FLA) is a fast, memory-efficient library for advanced linear attention models used in transformers, written in PyTorch and Triton, and compatible with NVIDIA, AMD, and Intel GPUs. It offers many state-of-the-art linear attention models and fused modules that speed up training and reduce memory use. You can easily replace standard attention layers in your models with FLA’s efficient versions, improving training and inference speed, especially for long sequences. FLA supports hybrid models mixing linear and standard attention, and integrates with Hugging Face Transformers for easy use and evaluation. This helps you train and run large language models faster and with less memory, making your AI projects more efficient and scalable. https://github.com/fla-org/flash-linear-attention

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Crypto M - Crypto News

@CryptoM · Post #65185 · 04/11/2026, 05:11 PM

🚀 Solana's Drift Protocol Suffers $285 Million Loss in Security Breach Drift Protocol experienced a significant security breach on April 1, 2026, resulting in a loss of $285 million. According to NS3.AI, attackers managed to drain Solana's largest perpetual futures exchange within approximately 12 minutes. The exploit was facilitated by a governance setup that utilized a two-of-five multisig and a zero-delay path for privileged actions. The attackers spent six months cultivating trust with insiders, leading to two Security Council members pre-signing transactions with hidden authorizations. In response to the breach, the Solana Foundation launched STRIDE, a foundation-backed continuous security program, just days after the incident. #Solana#DriftProtocol#SecurityBreach#285MillionLoss#PerpetualFutures#NS3AI#MultisigExploit#GovernanceSetup#STRIDE#SolanaFoundation#CryptoSecurity#InsiderAttack#BlockchainSecurity#SOL