#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
#Policy_Brief: Coercion Over Consent: #Ethiopia’s dangerous mandatory Digital ID experiment
In this policy brief, Mohamed A. argues that Ethiopia's mandatory Digital ID (#Fayda) is a "flawed and dangerous policy," not because identification itself is problematic, but because enforcement lacks legal safeguards. He emphasizes that centralizing sensitive data risks turning governance into a tool of "surveillance, control, and exclusion."
According to him, Ethiopia is "importing the concept as if it were a proven model." In Ethiopia's fragile institutional context, this amounts to "recklessness disguised as modernization," especially with foreign funding raising unresolved questions about "who controls the data."
The author urges authorities to "pause enforcement" until trust and oversight are established, arguing that without them, mandatory ID is "not progress—it is a poorly designed and dangerous policy."
https://addisstandard.com/?p=54995
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#EthioDjiboutiRailway#ComingSoon#TravelMadeEasy#StayTuned#DigitalEthiopia#Fayda