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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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@abmedia_news · Post #23709 · 04/07/2026, 01:34 PM
【🚀AI 人工智慧｜Agent Harness 才是關鍵：為什麼同一個 AI 模型在不同產品表現天差地遠 】 #Agent#Harness#AI 📍請見報導： https://abmedia.io/agent-harness-engineering-why-same-model-different-performance 📍訂閱鏈新聞頻道：https://linktr.ee/abmedia.io
@abmedia_news · Post #23801 · 04/11/2026, 09:30 AM
【🚀AI 人工智慧｜Harness Engineering 是什麼？AI 的下一個戰場不是模型，而是模型外面的那層架構 】 #Harness#Engineering#AI 📍請見報導： https://abmedia.io/harness-engineering-ai-agent-framework-explained 📍訂閱鏈新聞頻道：https://linktr.ee/abmedia.io
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@githubtrending · Post #15523 · 02/25/2026, 12:30 PM
#typescript#agent#agentic#agentic_framework#agentic_workflow#ai#ai_agents#bytedance#deep_research#harness#langchain#langgraph#langmanus#llm#multi_agent#nodejs#podcast#python#superagent#typescript DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge. https://github.com/bytedance/deer-flow
@desi_memes_funny_jokes · Post #5101 · 07/31/2024, 08:22 AM
#TransformAnger#FuelForSuccess#Harness TheEnergy #PassionDriven#Success Mindset #RiseAboveChallenges #HappinessJourney#PracticeMakesPerfect#Mindfulness#Gratitude#KindnessMatters#JoyfulMoments#PersonalGrowth#HappinessIsAChoice#SpreadLove#LiveFully#MotivationalStudio#AashiqShekhMotivational#FitnessFuelHub#RemixedRhymes#LaughingStudio
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