Total Robots
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Deployed
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Provisioned
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Online (1h)
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Draft
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Recent Robots
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🤖 Identity
✨ Soul
🧠 Brain
⚙️ Hardware
🌐 Network
🔒 Security
When triggered, permanently destroys on-board storage. Only for classified deployments.
Deployed Robots
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📋 Activity Log — All Robots
📡 Push to Single Robot
🌐 Fleet Broadcast
All deployed + provisioned robots
⚠️ This pushes to ALL active robots. Use carefully.
📋 OTA Update History
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🧬 ATAVUS Genesis-1 — Live · Port 8008 · 4.7GB Q4_K_M
ATAVUS Neural Core A1 | Runtime: atavus.cpp v1.0.0 | Fine-tuned for ATAVUS humanoid robotics
Model
ATAVUS Genesis-1 (R4)
File
/data/models/genesis-1-gguf/genesis-1-q4_k_m.gguf
Size
4.7 GB (Q4_K_M quantized)
Serve Port
8008 (atavus.cpp, OpenAI-compat)
Training Rounds
4 rounds complete ✅
Final Loss / Acc
0.0397 / 98.5%
Training Samples
215 (115 language + 100 embodiment)
Context
8,192 tokens (deployed) / 40,960 (model max)
ATAVUS Genesis-1 R4: 4 rounds of QLoRA fine-tuning (rank 64) on 215 samples. 98.5% accuracy. Embodiment-aware: proprioception, manipulation, navigation, safety. Runs via atavus.cpp on port 8008.
💬 Live Chat
🏋️ Fine-Tune
📦 Create Update
📊 Dataset
📋 Job Status
🧬 Genesis-1 Live Test
Talk directly to the deployed Genesis-1 model running on port 8008.
Ready — type a message to test Genesis-1...
Quick tests:
Latency:
● Port 8008
1 epoch ≈ 45min CPU. 3 epochs recommended for first run.
What happens when you train:
1. Loads ATAVUS Neural Core A1 base weights
2. Applies QLoRA (rank 64, alpha 128) — precision fine-tuning
3. Fine-tunes on your dataset (215+ samples: language + embodiment)
4. Saves LoRA adapter to
5. Push adapter via OTA to all robots
2. Applies QLoRA (rank 64, alpha 128) — precision fine-tuning
3. Fine-tunes on your dataset (215+ samples: language + embodiment)
4. Saves LoRA adapter to
/data/models/genesis-1/adapter/ (R4 complete ✅)5. Push adapter via OTA to all robots
⏱️ Est. time per round: ~9 hrs on AMD EPYC (no GPU).
R4 complete. Next run = R5 incremental fine-tune.
R4 complete. Next run = R5 incremental fine-tune.
Build an OTA update package from your current Genesis-1 model config. Deploy to individual robots or broadcast to fleet.
R4 Dataset: 215 samples (115 language + 100 embodiment) · LoRA rank 64 · loss 0.0397 · acc 98.5%
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