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🧭 About PyIntel

PyIntel is an independent open-source AI collective focused on building high-density, compute-efficient foundation models, datasets, and perception architectures for embodied robotics, edge devices, and ambient assistants.

Rather than scaling parameters blindly, PyIntel focuses on data-centric intelligence, 3D geometric grounding, and architectural efficiency—enabling sub-3B parameter models to reason like frontier systems.

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🔬 Core Research Pillars

1. 📐 Situated Spatial Reasoning & 3D Grounding

Teaching vision-language models to ground physical entities in 3D coordinate space, compute line-of-sight raycasts, and understand depth, clearances, and bounding geometries.

2. 👤 Perspective-Taking & Theory of Mind (POV of Others)

Breaking free of the "mirror reversal" bug. Training models to translate fluidly between egocentric (first-person) and allocentric (third-person/observer) reference frames, and accurately model what other agents in the environment can or cannot see.

3. 🧠 Episodic Soft Memory Projections

Developing lightweight projection bridges that compress historical video frames and sensor audio into dense soft memory tokens—giving edge models long-horizon memory without context window exhaustion.

4. ⚡ Real-Time Duplex Interaction

Architecting low-latency, streaming vision-and-voice pipelines for interactive physical assistants ("Jarvis") running on consumer edge hardware.

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📦 Flagship Artifacts & Releases

📊 Datasets

• pyintel/vantage-spatial-pov-mix
  A 7,712-pair harmonized multimodal instruction dataset featuring situated 3D spatial queries, camera perspective translations, and Theory of Mind reasoning with native <|channel>thought chains.
• pyintel/open-board-registry
  Ground-truth structured specifications for 1,700+ microcontroller boards and embedded development platforms (pinouts, voltages, RAM/ROM limits, and communication interfaces).

🤖 Models & Architectures (In Development)

• PyIntel Vantage-E2B
  A unified multimodal spatial reasoning engine combining Google DeepMind's EmbeddingGemma-2 (740M) and Gemma-4-E2B-it (2.3B) via an episodic Soft Memory Projection Bridge.

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🌐 Connect & Collaborate

• Organization Hub: huggingface.co/pyintel