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
Altitude-V1-2B-Base	Balanced Multimodal Model	High-Capacity Multimodal Audio/Video/Text Architecture	Model
Altitude-V1-1B-R	Extended Knowledge Model	Refined Knowledge Distillation & Attractor Memory Alignment	Model
Altitude-V1-2B-R	Extended Knowledge Model	Deep Context & High-Reasoning Variant	Model

🤝 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.
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