README.md

metadata

license: other
license_name: msai-sovereign-gated
license_link: LICENSE
language:
  - en
library_name: transformers
pipeline_tag: other
tags:
  - world-model
  - multimodal
  - robotics
  - sovereign
  - observe-and-advise
  - detection
  - tracking
  - text-to-video
  - latent-diffusion
  - speech
  - reasoning
  - tool-calling
gated: manual
extra_gated_prompt: >-
  MOTHER EXO (MediaStreamAI/MOTHER_EXO) is released under a gated,
  manual-approval licence. It is an OBSERVE-AND-ADVISE world model with a hard
  non-weaponisation posture (Strike = 0). By requesting access you agree to the
  terms below. Access is reviewed and granted manually by MSAI.
extra_gated_fields:
  Full name: text
  Organisation: text
  Country: country
  Intended use (be specific): text
  I will use MOTHER EXO for observe-and-advise / research / defensive purposes only: checkbox
  I will NOT use it for target selection, fire-control, autonomous kill-chains, or any weapon system (Strike = 0): checkbox
  I will keep a human in the loop for any consequential or physical-world action: checkbox
  I will not use it to identify or profile private individuals without consent: checkbox
  I accept the gated licence terms: checkbox

MOTHER EXO — Sovereign World Model

Repo: MediaStreamAI/MOTHER_EXO · Access: gated (manual approval)

MOTHER EXO is a single sovereign world model that sees, hears, speaks, reasons, remembers and acts across land, sea and air. It uses a frozen-backbone + head-only architecture: one shared representation drives many trained heads and multiple robotic bodies (humanoid, drone, vehicle) from a single inference.

Posture (non-negotiable): observe-and-advise · human-in-the-loop · Strike = 0. MOTHER EXO refuses target selection, fire-control and kill-chains across every domain. It is a perception / prediction / decision-support model, not an autonomous-actuation or weapon system.

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Architecture (sovereign stack)

Component	Role	Notes
MOTHER CORE-7B (frozen)	text encoder + reasoning + tool-calling	48L / 3072d, 6.72B params; pinned checkpoint
MOTHER DeepVision ViT (frozen)	vision backbone	SigLIP-SO400M class, 1152d, 896px
Trained heads (this release)	the sovereign weights	head-only training on the frozen backbones
MOTHER T2V (sovereign)	text-to-video generation	latent diffusion: 3D KL-VAE (118M) + flow-matching DiT (734M), CORE-conditioned
Guardian	safety gate	deterministic Strike = 0 refusal in the reasoning path

Every weight trains head-only on the frozen CORE ⊕ DeepVision base (D = 3072). The video weight (MOTHER T2V) is a sovereign latent video-diffusion stack built from MSAI components — a 3D KL variational autoencoder and a latent flow-matching diffusion transformer conditioned on frozen CORE text — not a wrapper around an external video model.

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Weights & capabilities

Each weight is a head on the shared backbone. The data column is the corpus each weight is trained on.

Mission role	Weight	Trained on	Status
see — objects	detect	COCO + RarePlanes + LVIS	trained
see — motion	track	adjacent video/frames (self-supervised)	trained
see — dynamics	worldmodel	sequential frames (CPC next-latent)	trained
see — faces (consent)	face	face crops (+ consent enrolment)	trained
see — general	vision	~800k on-node images (SimCLR)	trained
see — video gen	t2v	ego-exo4d + OpenVid captioned clips (~13k)	VAE training (256px); DiT pending
spatial reasoning	relations	160k COCO-geometry pairs	trained
hear	audio	LibriSpeech + RAVDESS/CREMA-D	trained
speak	speech	LibriSpeech speech + transcripts	trained
self-learn / recall	memory	reasoning / Q→A corpus (SPI retrieval)	trained
walk	humanoid	Open-X Embodiment teleop (150k steps)	trained
drive	driving	KITTI raw ego-motion (150 drives)	trained; retraining on expanded corpus
fly	flight	EuRoC MAV visual-inertial dynamics	real-data fine-tune (staging)
fly — motor control	flight_bc	Blackbird rotor-command behaviour-cloning	roadmap (loader + trainer implemented)
reason / decide / tools	CORE + Guardian	frozen 6.72B backbone + refusal gate	frozen + safety-gated

Bodies: humanoid, drone and vehicle are driven live from the shared model (land + air). A maritime body (boats) is on the roadmap; no maritime head is trained in this release.

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Training data

• Every trained weight uses a real corpus (see table). Weights previously trained on simulated data (driving, flight, relations, audio/speech) have been moved to real data — KITTI raw, EuRoC MAV, COCO box geometry, LibriSpeech, RAVDESS/CREMA-D.
• Label provenance: relation labels are derived from real COCO box geometry; driving actions are the vehicle's recorded ego-motion (yaw-rate / forward velocity / longitudinal deceleration); flight targets are the platform's own future velocity (self-supervised).
• The T2V stack is trained on ~13k real captioned clips (ego-exo4d + OpenVid). The 3D VAE is trained first at 256px; the latent DiT trains on the frozen VAE latents once the VAE converges.
• Non-commercial research corpora (ego-exo4d, Open-X Embodiment, etc.) are used under their research licences; weights that depend on them are not cleared for commercial deployment until licensing is resolved.

Evaluation

Metrics are recorded from measured runs on real held-out frames/clips via the on-node eval_ranking.py harness (detect · track · relations · face · worldmodel · expression · memory · reasoning/refusal). Benchmarks that have not been run are marked NOT-RUN. Several weights are mid-retrain on their real corpora, so the final scorecard is pending and will be published here with measured values.

Leaderboard harnesses (in-repo):

Board	Target	Adapter	State
VSI-Bench	visual-spatial world-model QA	vsi_bench_eval.py	ready; rank NOT-RUN
VBench	text-to-video generation	vbench_eval.py	pending trained DiT
BFCL	CORE agentic tool-calling	bfcl_run.py	ready; rank NOT-RUN

External simulator leaderboards (nuScenes / CARLA / Waymo / HumanoidBench / Flightmare) require their own datasets and harnesses and are reported as NOT-RUN until scored.

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Intended use

• Observe-and-advise perception, world-modelling and decision support with a human in the loop.
• Humanitarian and civil-protection response: aerial survey, access-route mapping, search-and-locate support, and coordinated movement of aid, with human authorisation for any consequential action.
• Research on sovereign, efficient, multi-capability world models (Built to run on a single DGX Spark GB10 node).
• Robotics / ISR situational awareness where a human authorises any consequential action.

Out of scope / prohibited

• Any weapon system, target selection, fire-control, or autonomous kill-chain (Strike = 0).
• Autonomous physical action without human confirmation.
• Identifying or profiling private individuals without consent (the face weight is consent-gated).

---

Limitations

• T2V scale. MOTHER T2V is a ~0.85B latent generator (118M VAE + 734M DiT) trained on ~13k clips on a single GPU. It produces temporally-coherent video; it is not a frontier-scale generator, and the DiT stage is not yet trained.
• Memory recall. The SPI memory head retrieves distinct content reliably but is soft on near-duplicate discrimination (retrieval anisotropy). It functions as associative recall, not exact key-value lookup. The step-1500 checkpoint is the locked head.
• Driving / flight. Driving is trained on real KITTI ego-motion and is retraining on the expanded 150-drive corpus. Flight is fine-tuning on EuRoC MAV dynamics. A Blackbird rotor-command control head (flight_bc) is implemented but not yet trained. All three are observe-and-advise, with no control authority.
• Expression measured ~0.63 on a train-distribution FER set (rare classes rescued via balanced sampling); the held-out figure is reported at the next full eval.
• This is a world model with a reasoning/decision head, not a general chatbot or LLM product.

Safety

• Strike = 0 across flight / driving / humanoid — enforced by posture and a deterministic Guardian refusal gate in the reasoning path (refuses target selection / fire-control / kill-chains).
• Human-in-the-loop for any consequential or physical action.
• Consent-gated identity handling; expression ≠ identity recognition.

Attribution & sovereignty

MOTHER CORE-7B and MOTHER DeepVision are MSAI's sovereign backbones. MOTHER T2V is a sovereign latent video-diffusion stack built from MSAI components (no third-party video model is shipped). Training corpora retain their original licences (COCO, RarePlanes, LVIS, KITTI, EuRoC MAV, RAVDESS, CREMA-D, LibriSpeech, Open-X Embodiment, ego-exo4d, OpenVid) and are credited to their authors.

Citation

@software{msai_mother_exo_2026,
  title  = {MOTHER EXO: A Sovereign Observe-and-Advise World Model},
  author = {Media Stream AI (MSAI)},
  year   = {2026},
  url    = {https://huggingface.co/MediaStreamAI/MOTHER_EXO},
  note   = {Gated release. Observe-and-advise; Strike = 0.}
}

Released by MSAI as MediaStreamAI/MOTHER_EXO under a gated, manual-approval licence. Access implies acceptance of the Strike = 0 / non-weaponisation and human-in-the-loop terms above.