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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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AI & Law

@ai_and_law · Post #341 · 06/28/2024, 07:04 AM

Implementing Transparency in AI: A Step Forward Zuzanna Warso and Paul Keller from Open Future, alongside Maximilian Gahntz from Mozilla, have published a proposal to implement the EU AI Act’s training data transparency requirement for general-purpose AI (GPAI). Article 53 1(d) of the Act mandates GPAI model providers to publish detailed summaries of their training content, covering data sources and sets with narrative explanations. The proposed template emphasizes a comprehensive scope and sufficient technical detail to benefit both experts and laypeople. These summaries should list primary data collections, provide narrative explanations of other data sources, and clearly distinguish between 'data sources' (origins) and 'datasets' (processed data points). This transparency requirement aims to enhance accountability, enable research and scrutiny, and strengthen individuals' and organizations' ability to exercise their rights in the AI development process. #AI#Transparency#AIAct#DataGovernance#OpenFuture#Mozilla