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Source channel @githubtrending · Post #15428 · Jan 22

#cplusplus FlashMLA is DeepSeek's optimized attention library that makes AI models run faster and use less memory. It works with advanced NVIDIA GPUs to speed up how language models process information, achieving up to 660 trillion floating-point operations per second. The library supports both dense and sparse attention modes, meaning it can focus on important tokens while skipping less relevant ones, reducing computational waste. For you, this means faster AI responses, lower costs for running large language models, and better performance on tasks like chatbots and code generation. The technology is open-source and integrates with popular AI frameworks like PyTorch and Hugging Face, making it accessible for developers building next-generation AI applications. https://github.com/deepseek-ai/FlashMLA

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Venture Village Wall 🦄

@venturevillagewall · Post #3607 · 12/20/2024, 07:00 PM

o3 & o3-mini Break Benchmark Records The performance of o3 and o3-mini showcases state-of-the-art (SOTA) results across various benchmarks. Key insights include: - Frontier Math scores increased from 2% to 25%. - SWE-Bench achieved 71.7%, a significant leap for a startup that recently raised $200 million with 13.86% earlier this year. - ELO on Codeforces reached 2727, held by only 150 individuals globally. - ARC-AGI model scored 87.5%, breaking a five-year deadlock. - Noteworthy progress on GPQA and AIME benchmarks. Access to o3-mini is currently available to security researchers, while general public access is set for late January. Full access to o3 will follow later. #AI#SOTA#Benchmarks#o3#o3-mini #FrontierMath#SWE-Bench #Codeforces#ELO#ARC-AGI #GPQA#AIME#Funding#Progress#Research#Technology#Innovation

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