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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 #99 · 08/30/2023, 07:04 AM

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Zoom Addresses EU Privacy Concerns and Updates Terms of Service Greetings! In response to discussions about potential EU privacy law implications, Zoom issues a statement and revises its Terms of Service. The focus? Ensuring customer data isn't utilized to train AI models. Zoom's statement and Terms affirm that user-generated content, including audio, video, chat, and more, isn't employed for training Zoom's or any third-party AI models. This step aims to dispel any concerns. Zoom initially shared its statement on August 7 and later updated it on August 11, aligned with the revised Terms. The shared stance now unequivocally states, "Zoom does not use any of your customer content to train AI models." Earlier, a Stack Diary article flagged changes to Zoom's March Terms, raising potential concerns about broad data utilization for AI model training. Zoom's quick response aims to address these concerns and reaffirm privacy commitments. #Zoom#PrivacyMatters#TermsOfService#AIModels#DataProtection#PrivacyLaw#TechUpdates

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