Blume Terminal
Warning compliance teams to avoid regulatory blind spots
What it does
Regulatory authorities publish hundreds of updates every month. Buried within them are changes that alter disclosure requirements, reporting obligations, and enforcement expectations. Most teams find out too late, through secondary sources, or not at all. Blume Terminal monitors primary regulatory sources continuously, classifies every publication using AI, and delivers filtered alerts directly to your inbox — matched precisely to your industry, jurisdiction, and regulatory framework footprint.
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Regulatory Intelligence TerminalJun 2026 · theriskvantage.com · ▲4Practitioner knowledge, AI synthesis, global risk fluency
- CSContinue – Source-controlled AI checks, enforceable in CIFeb 2026 · docs.continue.dev · ▲44
We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
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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 · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
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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…
AI · 27d ago · cactuscompute.com
Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
AI · Mar 2026 · claude.com
