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Running on Zero
| # Simam AI Lab case studies | |
| This collection is written for public communication, LinkedIn articles, and | |
| technical project pages. It distinguishes verified implementation evidence from | |
| research hypotheses and unfinished work. | |
| ## Case studies | |
| 1. [Simam3D Evidence Lab](01-simam3d-evidence-lab.md) — a depth and 3D export | |
| pipeline designed to show its evidence, provenance, and uncertainty. | |
| 2. [Direct Gaussian Export with DA3](02-da3-direct-gaussian-export.md) — a | |
| hosted experiment exporting native Depth Anything 3 Gaussian parameters. | |
| 3. [Multi-View Fusion Without Overclaiming](03-multiview-fusion-evidence.md) — | |
| how duplicate, near-duplicate, synthetic-prior, and native-camera inputs are | |
| separated. | |
| 4. [What's Behind the Image?](04-whats-behind-the-image.md) — a user-guided | |
| hidden-scene hypothesis interface with explicit uncertainty boundaries. | |
| 5. [SimamAnything2GS](05-anything2gs-ingest.md) — an image/video-to-3D ingest | |
| prototype and its path toward true learned Gaussian reconstruction. | |
| 6. [SimamTwin3D](06-samamtwin3d-consent-first-capture.md) — a consent-first | |
| reference-capture and digital-presence research direction. | |
| ## How to use these | |
| Each case study contains: | |
| - a short public summary; | |
| - a LinkedIn-ready article draft; | |
| - verified evidence and limitations; | |
| - a suggested call to action and hashtags. | |
| The canonical implementation and verification record are linked from the | |
| [Simam3D GPU Space](https://huggingface.co/spaces/junaid-simamdigital/Simam3D-GPU), | |
| including [hosted verification](../HOSTED_VERIFICATION.md), the | |
| [paper outline](../PAPER_OUTLINE.md), and the | |
| [research backlog](../RESEARCH_BACKLOG.md). | |
| Do not describe a case study as a benchmark result unless it includes a named | |
| dataset split, a baseline, a metric, and a reproducible manifest. | |