# AnyBody

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Oscar Kinnala](https://cerebralvalley.ai/u/Kinnala)
- **GitHub:** https://github.com/tr8tmnvny9-lab/AnyBody
- **Demo video:** https://www.youtube.com/watch?v=vE_KLrKh_GU
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2674

AnyBody (A://) — Body & Task-Agnostic Humanoid Control

AnyBody (A://) is a universal, body- and task-agnostic neuromorphic motor brain built from first principles in pure Rust (zero external ML framework dependencies). Instead of brittle joint-space PID loops, keyframe policies, or body-specific trajectory optimizers, AnyBody runs a 4-layer, 4,134,584-neuron, 25,107,740-synapse (25.11M) spiking motor connectome at 1,000 Hz coupled to 88 antagonistic Hill-type muscles (44 whole-body & 5-finger hand DoFs), verified across Unitree H1 (19 DOF), Unitree G1 with 5-finger hands (43 DOF), Unitree Go2 / Spot (12 DOF), and Franka Panda (7 DOF).

THE PROBLEM IT SOLVES:
1. Morphology Lock-In: Controllers tuned for a 19-DOF biped cannot transfer to a 44-DOF dexterous humanoid or 12-DOF quadruped without weeks of reward re-engineering.
2. Stiff Actuator Power Waste: Conventional 1,000 Hz PD servos fight gravity with rigid co-contraction, burning ~1,221 W during locomotion.
3. Open-Loop Perception: VLM planners output static waypoints without closed-loop retinal feedback or spinal reflex stability.

HOW ANYBODY SOLVES IT FROM FIRST PRINCIPLES:
• Layer 1 — Prefrontal Cortex & Retinal Stream (Meta Muse + SAM-3.1): Natural-language/voice commands (Muse-Spark-1.3, Muse-Open, Muse-Wonder-Full) and first-person camera frames (ego_head_cam, 116°×86° FOV segmented by Meta SAM-3.1) compile open-ended goals—including negations and sorting—into 14-D cortical attractors and Basal Ganglia D1/D2/STN gating channels (meta_prefrontal.rs).
• Layer 2 — Self-Organizing Somatotopic Neocortex (neuro_core & cortex.rs): 2,500 minicolumns (15,000 neurons, 390,036 synapses) built from 3-compartment Layer-5 pyramidal neurons (Vs, basal NMDA Vb, apical Ca2+ tuft Va with Larkum BAC burst multiplexing), PV/SST/VIP disinhibition, and a 4-timescale synapse bank (STP, 1,000 ms BTSP, Oja/STDP, Fusi cascade). In 1,500 prenatal twitches, it self-organizes a topological homunculus (-53.8% disorder, 6.78 -> 3.13, 2.17x gain) with zero kinematic labels.
• Layer 3 — Cerebellar mGluR1 Predictive Delay Cancellation (cerebellum.rs): 4,118,752 neurons and 24.71M synapses across 88 microzones. Intracellular mGluR1 -> IP3 -> Ca2+ eligibility traces (tau = 45 ms, peak at 44 ms) bridge the 30 ms sensory delay via Kawato Feedback-Error Learning, cutting postural error by -16.9% and spinal reflex effort by -58.9%.
• Layer 4 — Spinal Half-Center CPG & 88 Hill-Type Muscles (spinal.rs & body_physics): Persistent-sodium (INaP) rhythm generators, alpha-gamma co-activation, Ia/Ib reflexes, and 25 ms palmar slip locks drive locomotion and grasping with zero PID loops.

FALSIFIABLE PROOFS (verify_all):
• Zero-Weight Collapse: Zeroing weights (Audit 4A) causes unpinned collapse in 0.179 s—proving zero hidden PD loops.
• 2.89x Performance-per-Watt: 84.2% spike sparsity (26.6 mW compute vs. 42.84 W dense) and 422.0 W total power vs. 1,220.7 W stiff-PD (saving 798.7 W) at 1.76 m/s 3D walking (99.6/100).

## More from Meta Global AI Developer Hackathon

- [Triton Kernel Harness](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2671)
- [Sensora AI](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2672)
- [BacktestAI](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2673)
- [OmniInspect AI](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2675)
- [Glenox Team](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2676)
- [BugBuster](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2677)

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