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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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AI & Law

@ai_and_law · Post #602 · 06/27/2025, 07:04 AM

🇺🇸Microsoft Faces Watchdog Pushback on AI Advertising Microsoft’s ambitious marketing of its Copilot AI features has come under scrutiny. The National Advertising Division (NAD) has recommended that the company revise or discontinue certain productivity claims tied to Microsoft 365 Copilot, citing a lack of objective evidence. While Microsoft cited impressive user perception stats—like 70% reporting increased productivity—the NAD found the study insufficient to support hard ROI claims. More than just numbers, the watchdog also flagged the branding itself. With "Copilot" used across multiple tools, including Business Chat, users may not understand what the product can, and cannot, do. NAD advised Microsoft to make material limitations clear and avoid conflating distinct features under a single name. As AI tools enter mainstream business settings, regulatory clarity around marketing promises is becoming non-negotiable. #AI#MicrosoftCopilot#AIAdvertising#AITransparency