Dhi Labs, Blog

Technical writing from Dhi Labs on honest edge vision AI. Hugging Face has no public API for Posts or Articles, so these are published here as versioned markdown, and linked from the org card, every product's demo Space, every dataset card, and the Dhi Labs collection.

Posts

1. AI that refuses to guess (2026-07-10 update, ~17 min read): the thesis. A full taxonomy of the four honesty mechanisms (calibrated intervals, refusal gates, provenance, falsification ledgers) with a worked, real numbered micro example of each; why the industry default is overclaiming and what it costs operators; and the measurement philosophy: synthetic ground truth first, real data second, negative results published.
2. Precision first cross camera linking (E1) (2026-07-10 update, ~19 min read): the full method walkthrough (episodes versus events, three gates with their actual thresholds, transit priors learned only from ref confirmed links), the 0.918 to 1.0 uniqueness guard story with the failure case that motivated it, the 24 site grid, the under 2 MB month test, the Frigate bridge's confidence gated identity mapping, and the first real data campaign: WILDTRACK two ways (ground truth replay and a real YOLO11n + ByteTrack pipeline), precision 1.0 with zero wrong links in every condition, recall 0.4087 and 0.3502 at 40% reference coverage, and an honest recall 0.0 without references, diagnosed rather than hidden.
3. When the error bar is the product (A4) (2026-07-10 update, ~14 min read): the flagship honesty story, told in four acts from the committed evidence log. Synthetic wins first (analytic interval 0.50 to 0.63 actual coverage against a 0.90 claim, conformal multiplier 6.7x to 14.5x); then the first real CrowdHuman test fails (flat detectability curve, one directional correction against two sided error, 28.204 versus naive 14.08); a richer curve fails better; a detector fix improves naive to 11.767 and the correction still loses; and the two sided estimator finally wins (11.031, 90.67% coverage), with the dense scene boundary where naive still wins disclosed.
4. Six products, one honesty thesis (2026-07-10 update, ~14 min read): the portfolio tour. Each product in a full paragraph with its headline number and its stated limitation in the same breath (A4, E1, A3, E4, A5, B1), the combined 340 test count with its arithmetic shown, and a new section on how the pieces are designed to compose on a single edge box, CPU only decision layers over GPU perception, stated as design properties rather than deployment claims.
5. Prompt2Model v0.1.0 (2026-07-10 update, ~12 min read): the program's public release exception, MIT licensed and tagged. The refusal gate mechanics (conformal threshold with the finite sample correction, the 0.98 relative accuracy floor), the three bug engineering case study behind a published 0.0 accuracy artifact (unseeded RNGs, class dropping splits, from scratch BatchNorm collapse), the healthy re measured result (36 of 36 correct, zero abstentions in distribution, both OOD probes abstained), the corrections that fix forced to earlier published numbers, and all eight numbered known limitation issues.

License

This blog is released under CC BY-NC 4.0 (non-commercial). It stays public and freely readable: this dataset is prose meant to be read, and gating it would hide the posts from everyone. Reading and citing individual posts is welcome; do not redistribute or re-host the text elsewhere without permission. Any use in a publication or downstream work should cite Dhi Technologies. Commercial use requires a separate agreement; contact dhi-tech.com.

Honesty note

Numbers in these posts are measured on synthetic benchmarks with exact ground truth, except where a post explicitly attributes a number to a real data evidence log (CrowdHuman for A4, WILDTRACK for E1), a fresh reproduction run described in the post, or a public release note, and says so inline. Remaining real world validation is in progress and marked as such throughout. No state of the art claims, no customer or deployment claims.

• Org: https://huggingface.co/Dhi-Technologies
• Collection: https://huggingface.co/collections/Dhi-Technologies/dhi-labs-honest-edge-vision-ai-6a4eb297cbd60f5f673cc2d7
• Company site: https://dhi-tech.com/labs
• Code: proprietary, closed source; the open surface is the evidence these posts quote and link. Prompt2Model shipped one public, MIT licensed release (post 5) as a deliberate exception; the other five products are not public and have no release planned. Partnership or access inquiries: dhi-tech.com.