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Source channel @githubtrending · Post #15401 · Jan 8

#python#agent#agentic_ai#agentic_framework#agentic_workflow#ai#ai_agents#ai_companion#ai_roleplay#benchmark#framework#llm#mcp#memory#open_source#python#sandbox MemU lets AI systems take in conversations, documents, and media, turn them into structured memories, and store them in a clear three-layer file system. It offers both fast embedding search and deeper LLM-based retrieval, works with many data types, and supports cloud or self-hosted setups with simple APIs. This helps you build AI agents that truly remember past interactions, retrieve the right context when needed, and improve over time, making your applications more accurate, personal, and efficient. https://github.com/NevaMind-AI/memU

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@kejiqu · Post #3614 · 07/05/2025, 06:44 AM

Character.AI 突破性技术:实时 AI 角色视频互动 Character.AI 发布名为 TalkingMachines 的自回归扩散模型,旨在增强 AI 角色互动真实感。该模型基于 Diffusion Transformer(DiT)技术,通过流匹配扩散、音频驱动的交叉注意力、稀疏因果注意力和不对称蒸馏等技术,实现类似 FaceTime 的实时通话视觉互动。用户仅需输入图片和声音信号,即可生成逼真的 AI 角色动作,支持多种风格。TalkingMachines 强调其为实时音频视觉 AI 角色发展的重要一步。IT之家 🏷#TalkingMachines#Character#AI#Diffusion 📢频道👥群组📝投稿