Tenshi Deepfake – Recommended

| Aspect | Guidance | |--------|----------| | | Only use data that the subject has explicitly authorized for synthetic reproduction. | | Disclosure | Every Tenshi‑generated output must carry a visible label (e.g., “Synthetic Media”) and the embedded watermark. | | Misuse Prevention | Tenshi’s license forbids distribution of non‑consensual deepfakes, political manipulation, or any content that could cause defamation or harassment. | | Data Privacy | Follow GDPR/CCPA‑type principles: store source media securely, allow subjects to request deletion of derived models. | | Bias & Representation | Evaluate models for demographic bias (skin tone, gender expression) and apply mitigation techniques (balanced training data, style‑mixing controls). | | Legal Landscape | Many jurisdictions (e.g., US states like California, Texas; EU’s Digital Services Act) criminalize non‑consensual deepfakes and require labeling. Tenshi’s compliance checklist aligns with these emerging statutes. |

| Step | Action | Resources | |------|--------|-----------| | 1 | – Tenshi is released under a non‑commercial, responsible‑use license . | Tenshi‑License.pdf (available on the official repo). | | 2 | Set Up the Environment – Docker image with GPU support; includes pretrained backbone, fine‑tuning scripts, and verification tools. | docker pull tenshi/deepfake:latest | | 3 | Collect Consent‑Based Data – Use only publicly licensed footage or obtain written consent. Store metadata (date, source, consent proof). | Consent‑Management‑Toolkit (open‑source). | | 4 | Fine‑Tune the Model – Run the tenshi_fine_tune.py script with your target data (minimum 5‑10 minutes of video). | Documentation: docs/fine_tune.md . | | 5 | Generate Content – Provide a text prompt or source video, then run tenshi_generate.py . | Example scripts in examples/ . | | 6 | Verify & Watermark – Use tenshi_verify --extract to confirm the embedded watermark. | SDK: tenshi_sdk . | | 7 | Publish with Disclosure – Add a visible caption (“Synthetic media generated using Tenshi”) and retain the provenance file. | Publishing‑Guidelines.pdf. | tenshi deepfake

Platforms must invest in automated AI detection tools trained to recognize the subtle biological artifacts left behind by deepfake software (e.g., unnatural blinking patterns or erratic pulse detection in pixels). Cryptographic Provenance: | Aspect | Guidance | |--------|----------| | |

With the release of tools like DeepFaceLab, Rope, and later, voice cloning via RVC (Retrieval-based Voice Conversion), the barrier to entry for deepfakery dropped to zero. By mid-2024, a user with a mid-range gaming GPU could generate a 60-second Tenshi deepfake video in under two hours. | | Data Privacy | Follow GDPR/CCPA‑type principles: