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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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Venture Village Wall 🦄

@venturevillagewall · Post #3606 · 12/20/2024, 06:41 PM

O3 and O3-Mini Benchmark Breakthroughs The O3 and O3-Mini models showcase state-of-the-art (SOTA) performance with significant leaps in various benchmarks. Results on Frontier Math have jumped from 2% to 25%. The SWE-Bench model achieved a score of 71.7%, while a startup has raised $200 million following results of 13.86%. ELO on Codeforces reached 2727, surpassing most peers globally. Notably, the ARC-AGI model scored 87.5%, breaking a five-year benchmark. Access for security researchers to O3-Mini starts today, with general access available in late January. #O3#O3Mini#SOTA#Benchmarks#AI#ML#Funding#Codeforces#ARC-AGI #FrontierMath#SWE-Bench #ELO#GPQA#AIME#SecurityResearch#TechUpdates#Innovations#Startups#Performance#AIModels