PolicyWatcher
AI-assisted, digital policy and AI governance tracker
What it does
Like many of you, I was tired of receiving "We've updated our Terms of Service" emails with zero clue about what actually changed, whether my data would be used to train AI models, or how prompt retention policies were evolving. Reading 40 pages of legal jargon for every SaaS tool we use isn't scalable. That's why I built PolicyWatcher: an open civic-tech platform that monitors public policy changes across major tech and fintech companies in real time.
Track evidence-gated company policies, verified baselines and published policy changes through PolicyWatcher's public knowledge base and interactive monitor.
PolicyWatcher records public policy sources, verified baselines and published changes with direct links to their evidence. Automated screening supports review; it is not legal advice or a compliance determination. The public evidence summary and knowledge base work without JavaScript. JavaScript is only required for the interactive monitoring workspace. Current evidence counts are loading. The server-rendered knowledge base remains directly available. PolicyWatcher monitors public company policy sources and publishes evidence-gated records only after a baseline and source references are available. Yes. Public records link to the monitored company, policy, verified baseline and available…from policywatcher.online
Does the same job
all alternatives →More ai this month
the category →
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.
AI · 16d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


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…
AI · 26d ago · cactuscompute.com


Launched alongside, August 2026
the whole month →- TL
Life & fun · 9d ago · louisabraham.github.io


- SA
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.
AI · 16d ago · simedw.com