Contradish tests AI policy consistency
Contradish verifies your AI follows its own stated policies
What it does
The EU AI Act, NIST AI RMF, and responsible AI frameworks require evidence that your model behaves consistently with its stated policies. contradish provides it.
contradish tests your AI 2,160 ways across 20 real-world domains: semantic invariance testing (paraphrase robustness) to find where your policy breaks.
Does the same job
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Hi all, Gorkem here. I started VerifyWise [1] to make AI governance less painful. Today, we’re launching our open-source platform to help teams take control of their AI compliance process. VerifyWise helps organizations navigate AI governance by providing audit readiness, risk registers, model fairness checks, and compliance documentation. Those are all built into a single platform you can self-host. We’ve been quietly building VerifyWise for a while, and we’re now at a place where it’s ready for more teams to try. Since we started, we've: - Released our core platform on GitHub:…

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Been working on data sovereignty recently and started this list. Hope you can contribute too.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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