MediaSFU
Video, Voice, AI Agents & Translation
What it does
MediaSFU is a developer-first communication platform with 6 embeddable widgets, AI voice & vision agents, HD video meetings, cloud phone (SIP/PSTN), and live translation in 20+ languages. Drop one script tag on any website — WordPress, Shopify, React, plain HTML — and add a call button, AI agent, or meeting portal in minutes. No backend changes. SDKs for React, React Native, Flutter, Angular, Kotlin, Vue, and more. $0.10 per 1,000 minutes. Everything included. No per-seat fees.
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Chat Skills for AI AgentsApr 2026 · cometchat.com · ▲84One file. Any agent. Working chat in under 10 minutes.
- ARA React and Next.js UI Toolkit for LLMs2024 · github.com · ▲24
Hey HN, I wanted to share a UI toolkit project I’ve been working on recently, born out of how difficult I found it to build a great UX on top of LLMs, and keep application state in sync. I’ve built: - A React/JS front-end library for conversational interfaces, which makes it super easy to bootstrap AI assistants and ChatGPT style UX: https://github.com/nlkitai/nlux - A set of adapters that simplify integration with AI backends such as LangServe and HuggingFace The library is highly configurable, easy to theme, supports markdown streaming (that was tough to get…
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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.
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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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Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
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