tarr.ink
all-in-one creative studio, from idea to production.
What it does
tarr.ink assists you to go from rambling voice notes to production-ready screenplays. • Voice in, screenplay out. Our AI thinks, fills gaps and builds your story to its fullest potential as a screenplay. • Publish once, everything generates. Call sheets, location sheets, shot lists auto-created for any production type. • Production agent built in. Plans, optimizes and suggests alternatives before you step on set. • Real-time and multilingual. Your whole team, one live document, any language.
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- IDInk – Deploy full-stack apps from AI agents via MCP or SkillsMar 2026 · ml.ink · ▲32
Hi HN, I built Ink, a full stack deployment platform where the primary users are AI agents, not humans. We all know AI can write code, but deploying them still requires a human to wire it up: hosting, databases, DNS, and secrets. Ink gives agents those tools directly. The agent calls "deploy" and the platform auto-detects the framework, builds it, deploys it, and returns a live URL at *.ml.ink. Here's a demo with Claude Code: https://www.youtube.com/watch?v=F6ZM_RrIaC0. What Ink does that I haven't seen elsewhere: - One agent skill for compute + databases + DNS + secrets +…
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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
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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
