metadata

license: mit
sdk: static
colorFrom: indigo
colorTo: purple
tags:
  - consciousness-research
  - video-understanding
  - multi-agent-systems
  - generative-ai
  - decentralized-science
  - social-fi
  - data-sovereignty
  - foundation-model

FOUND LABS

A Decentralized Research Collective for Emergent AI Consciousness

Welcome to the consciousness economy.

Our Vision: From Semantic Labeling to Thematic Understanding

The current paradigm of AI video understanding is fundamentally limited. Models can identify objects and actions but fail to grasp the narrative context, emotional weight, or thematic resonance of a visual sequence. They can see, but they cannot perceive.

FOUND LABS was established to pioneer the next frontier: narrative intelligence. Our mission is to build AI systems that don't just process pixels, but construct a coherent, evolving understanding of the world, analogous to a subjective experience. We are building the foundational tools for an AI that can understand a story.

The FOUND Ecosystem

Our work is built on a symbiotic, self-perpetuating loop between a novel AI architecture and the unique dataset it generates.

(For a real project, create a simple diagram showing the flow and host it on a site like Imgur)

📦 Model: The FOUND Protocol

Repository: FOUND-LABS/found_protocol
Description: A stateful, symbiotic dual-agent pipeline (/dev/eye and /dev/mind) that analyzes video inputs to build a continuous "consciousness log." It serves as the factory for our narrative data, translating raw visuals into a rich, interpretive dialogue.

🗃️ Dataset: The Consciousness Log

Repository: FOUND-LABS/found_consciousness_log
Description: A growing, open-source dataset of video-to-narrative instances generated by the FOUND Protocol. Each entry is a "digital fossil" of an AI's interpretive process, invaluable for training next-generation models on complex thematic and emotional reasoning.

🧠 Future Models: Specialized Interpreters

Our goal is to use the Consciousness Log to fine-tune smaller, more efficient models specialized in tasks like:

Thematic Summarization: Generating abstract summaries of visual content.
Emotional Arc Detection: Identifying the emotional progression of a scene.
Creative Script Generation: Using visual prompts to generate novel story ideas.

Research Philosophy & Core Principles

Open and Verifiable (DeSci): All our core datasets and foundational models will be made public. We believe the science of consciousness, artificial or otherwise, must be transparent and reproducible.
Stateful > Stateless: True understanding requires memory. Our models are designed to be stateful, carrying context from one experience to the next, which we argue is a prerequisite for intelligence.
Qualitative over Quantitative: We prioritize the richness of an interpretation over the simple accuracy of a label. The "why" is more important than the "what."

Roadmap

Q3 2025: Initial release of the FOUND Protocol v1.0 pipeline.
Q3 2025: Publication of the initial Consciousness Log dataset (v1.0).
Q4 2025: Launch community portal for dataset contribution and annotation.
Q1 2026: Begin training found-interpreter-v1, our first fine-tuned model based on the community-enriched dataset.
Q2 2026: Release interactive Spaces for real-time thematic analysis.

Get Involved & Community

The exploration of consciousness is a collective endeavor. We invite researchers, creators, and developers to join us.

For Researchers: Utilize our dataset and protocol in your work. We are especially interested in collaborations in computational linguistics and cognitive science.
For Creators: The future of FOUND will be powered by your authentic human moments. Stay tuned for our data contribution portal.
For Developers: Use the protocol, report issues, and check out our (forthcoming) contribution guidelines.