Memora Core @MemoraCore

Create the most lifelike humanoid AI agents with memory, feelings, emotions, and shared experiences. Git: https://t.co/Nd87kQDeW1 elzai.github.io/memora/ Joined March 2024

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Memora Core @MemoraCore

4 months ago

Memora enables you to create your own personalized AI system. with Memora, allowing your AI to do more than just respond—it learns, adapts, and evolvesalongside you.

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BetaList @BetaList

9 months ago

Memora: Replicating the Human Memory for every Personalized AI betalist.com/startups/memora

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Marc R @Seifreed

9 months ago

GitHub - ELZAI/memora: A Human Memory Agent For AI github.com/ELZAI/memora

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Memora Core @MemoraCore

5 months ago

Our GitHub github.com/ELZAI/memora/

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Synapse: Your Personal AI is Live Synapse enables you to create your own personalized AI system. with Memora, allowing your AI to do more than just respond—it learns, adapts, and evolvesalongside you. elzai.com

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Memora Core @MemoraCore

5 months ago

More info about Synapse AI elzai.com

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Memora Core @MemoraCore

5 months ago

Conversations with Personal AI (eg Character AI) should not have - delete - regenerate response - start new thread Humans don't interact like that

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Memora Core @MemoraCore

7 months ago

Emotion-Tagged Memories: Allowing AI to recall memories along with the emotions experienced at that time, such as joy 😄, sadness 😢, surprise 😲.

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Memora Core @MemoraCore

7 months ago

Currently, Memora manages text-based memories, assisting AI in maintaining context and evolving over time. However, our dream is way bigger towards the full spectrum of human memory, enabling AI to interact as naturally as a close friend.

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Memora Core @MemoraCore

7 months ago

Prompts. System prompts and input templates used by the LLM in various memory operations.

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Memora Core @MemoraCore

7 months ago

Schemas. Pydantic data models that are used for structured memory extraction, storage, and retrieval to ensure consistency and model structured output.

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Memora Core @MemoraCore

7 months ago

LLM Backends An interface for LLM providers, along with some implementations, that Memora can use in the backend for memory operations, such as understanding context, determining what to store and recall, linking memories to source messages and more.

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Memora Core @MemoraCore

7 months ago

Vector Database Enables semantic search across memories using dense vector embeddings for semantic similarity, combined with sparse text embeddings (like SPLADE) for hybrid search.

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Memora Core @MemoraCore

7 months ago

Graph Database Currently, our graph database implementation focuses on storing organizations, agents, users, their interactions with the agent (messages), and the memories derived from these interactions, all with date and time etc.