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Source channel @githubtrending · Post #14659 · May 1

#cplusplus#arm#convolution#deep_learning#embedded_devices#llm#machine_learning#ml#mnn#transformer#vulkan#winograd_algorithm MNN is a lightweight and efficient deep learning framework that helps run AI models on mobile devices and other small devices. It supports many types of AI models and can handle tasks like image recognition and language processing quickly and locally on your device. This means you can use AI features without needing to send data to the cloud, which improves privacy and speed. MNN is used in many apps, including those from Alibaba, and supports various platforms like Android and iOS. It also helps reduce the size of AI models, making them faster and more efficient. https://github.com/alibaba/MNN

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@venturevillagewall · Post #4339 · 03/08/2025, 01:00 PM

Top 5 Insights from Trendoscope Lab 1️⃣ a16z's new report reveals top B2C AI apps by traffic differ from revenue leaders like photo and video editors. Read more 2️⃣ Google launches AI Mode with Gemini, initially for Google One subscribers, enhancing AI SEO relevance. Details here 3️⃣ Short drama apps surge with 221% annual growth in downloads, affecting traditional streamers like Netflix and Disney+ that declined by 35%. Insight found here 4️⃣ Google and Meta enable developers to access cameras on XR devices, easing previous privacy restrictions. More info and here 5️⃣ Google enhances Android widget visibility with new filters and dedicated pages. Learn more #AI#Google#Tech#Streaming#XR#Investments#B2C#Apps#VideoEditing#Photos#Dramas#SEO#Privacy#Android#Widgets#Investing#VC#a16z#Trends#Innovation