PodText
Podcast transcripts you can search, summarize, and export
What it does
PodText starts with a podcast link—not a downloaded file. Paste an Apple Podcasts, Spotify, iHeart, YouTube, Xiaoyuzhou, or RSS URL, or upload audio/video, and get an accurate, timestamped transcript. AI turns it into summaries, chapters, highlights, and key quotes, while full-text search helps you find any moment fast. Export everything in SRT, VTT, TXT, or Markdown. It’s a faster path from a long episode to searchable knowledge and ready-to-publish content.
Get an accurate podcast transcript with AI — paste an Apple Podcasts, Spotify, iHeart, or RSS link, or upload audio and video. 60 minutes free, no credit card required.
Get an accurate podcast transcript by pasting an Apple Podcasts, Spotify, iHeart, or RSS link — no downloads, no uploads. Also transcribes any audio or video file. Your timestamped podcast transcript on the left, AI summary, chapters, and highlights on the right — ready to read, explore, and export. Welcome back to the show. Today we’re talking about how AI is reshaping content workflows. The biggest shift this year has been speed — turnaround that used to take days now takes minutes. Right, and that changes what a small team can ship. You’re not bottlenecked on transcription anymore. Exactly. We repurpose one episode into show notes, a newsletter, and five social clips. And search matters…from podtext.ai
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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 · 16d ago · simedw.com
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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
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Life & fun · 10d ago · louisabraham.github.io
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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.
AI · 16d ago · simedw.com