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Source channel @githubtrending · Post #14974 · Jul 19

#cplusplus ik_llama.cpp is an improved version of llama.cpp that runs faster on CPUs and hybrid GPU/CPU setups. It supports many new advanced quantization methods, which help models use less memory and run more efficiently. It also offers better performance for special models like DeepSeek and MoE, with faster prompt processing and token generation. You can run it on various hardware, including Android, and it has features to control where model data is stored (CPU or GPU). This means you get quicker AI responses and can handle bigger or more complex models smoothly on your computer or device[2][1][4]. https://github.com/ikawrakow/ik_llama.cpp

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@venturevillagewall · Post #4266 · 02/28/2025, 07:00 AM

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AI Predictions: From Vacuums to Real Impact AI-powered prediction platforms are gaining traction, with a focus on forecasting reactions based on content and audience. Initial predictions using tools like ChatGPT yield 17% accuracy, but considering audience interactions can boost accuracy to 83%. This innovative approach helped a startup refine its pitch to enter Y Combinator. Discover more insights on enhancing prediction accuracy in various fields here. #AI#Startup#Prediction#YCombinator#Marketing#Innovation#Tech#Growth#Entrepreneurship#Forecasting#AudienceAnalysis#DataScience#MachineLearning#Success#Business#Trends#Platforms#Metrics#Investment#VC