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---
title: README
emoji: 🔥
colorFrom: purple
colorTo: yellow
sdk: static
pinned: false
---

# United Lab

> **Reinventing AI based on human anatomy with 1-bit self-organizing substrates and open-weights for the global community.**

---

### 🌟 About Us
We are a non-profit research and engineering collective dedicated to the research, development, and democratization of next-generation artificial intelligence. We focus on moving beyond standard dense floating-point transformers by building **1-bit self-organizing attractor engines**, zero-float SIMD runtimes, and accessible open-source models.

By combining continuous local plasticity (STDP), homeostatic density regulation, and time-multiplexed silicon execution, we aim to deliver high-capacity, low-latency, and unrestricted AI substrates that run efficiently on standard consumer hardware.

---

### 🛠️ Technical Focus & Core Research

Our research centers on replacing brute-force matrix multiplication with biologically inspired, hardware-native bitwise graph dynamics:

*   **1-Bit Self-Organizing Attractor Substrates:** Replacing standard floating-point backpropagation with binary directed graphs updated dynamically via Spike-Timing-Dependent Plasticity (STDP) and bitwise `XNOR` + `POPCNT` SIMD evaluation kernels.
*   **Homeostatic Density Regulation:** Engineering adaptive thresholding mechanisms that lock active node firing density within optimal sparse regimes, preventing network seizure (activity saturation) and activity collapse.
*   **Time-Multiplexed Clock Scaling:** Leveraging high CPU/GPU clock frequencies (MHz/GHz) to scale execution throughput on compact, L3-cache-resident graphs (100M to 32B 1-bit edges) to achieve human-level state transition capacity without hitches from DRAM bandwidth bottlenecks.
*   **Frequency-Thresholded Subword Readouts:** Implementing multi-step state history concatenation mapped onto subword BPE vocabularies via frequency-thresholded linear decoding trees.
*   **Zero-Copy Rust Subsystems:** Developing high-performance, memory-aligned Rust runtimes featuring zero-heap allocation hot loops, strict `cargo clippy` standards, and atomic `.1bit` binary state persistence.
*   **Uncensored & Open Foundations:** Committing to raw model capabilities, transparent binary state checkpoints, and unconstrained open-weight foundations free of arbitrary alignment restrictions.

---

### 🚀 Featured Repositories & Substrates

| Repository / Model | Type / Focus | Core Architecture | Links |
| :--- | :--- | :--- | :--- |
| **Engine-1Bit-Core** | Rust Substrate Runtime | Zero-Float SIMD Bitwise Attractor Core (`.1bit`) | [Code](#) |
| **Altitude-V1-1B-Base** | Multimodal Audio/Video/Text | Edge-Adopted Multimodal Transformer / Hybrid Substrate | [Model](https://huggingface.co/T-E-A/Altitude-V1-2B-Base) |
| **Altitude-V1-2B-Base** | Balanced Multimodal Model | High-Capacity Multimodal Audio/Video/Text Architecture | [Model](https://huggingface.co/T-E-A/Altitude-V1-6B-Base) |
| **Altitude-V1-1B-R** | Extended Knowledge Model | Refined Knowledge Distillation & Attractor Memory Alignment | [Model](https://huggingface.co/T-E-A/Altitude-V1-2B-R) |
| **Altitude-V1-2B-R** | Extended Knowledge Model | Deep Context & High-Reasoning Variant | [Model](https://huggingface.co/T-E-A/Altitude-V1-6B-R) |

---

### 🤝 How to Support & Collaborate

As an open non-profit research team, our progress is driven by community collaboration and distributed engineering effort. Here is how you can get involved:

*   **Code & Algorithmic Contributions:** Help optimize our Rust bitwise kernels, design scale-free graph wiring routines, or refine readout decoding layers. Join our team on [Discord](https://discord.gg/MdvFfe69).
*   **Compute & Hardware Testing:** Help benchmark baseline training passes, run continuous dataset streaming experiments, or donate portable CPU/GPU compute time for our next open substrate release.

---

### 📬 Connect With Us
*   **Discord / Community:** [Join the United Lab](https://discord.gg/MdvFfe69)

---
<p align="center">
  <sub>© 2026 United Lab. Distributed under the Apache 2.0 Open Source License.</sub>
</p>