Mem Agent
The AI that refuses to let you drop the ball
What it does
An important deliverable, or a pizza place saved for that someday trip to Italy—Mem Agent keeps track of what you tell it, plus the todos living inside your notes and meetings, sharply following up so it actually happens. And with Push-to-Remember, seamlessly capture a thought into Mem or recall something you saved with a single button—all without leaving your work.
Use Push-to-Remember or save notes, meetings, and ideas in Mem. Your Agent learns what matters and checks in when something needs you.
Throw your notes, meetings, and braindumps into Mem. It'll make sure you follow through. Mem Workspace is where your notes, meetings, and ideas live. Push-to-Remember lets you speak a thought from anywhere on desktop; every capture gives your Agent context. Your notes, messages, and calendar show what’s unfinished, what’s coming up, and when you have time to act. Choose where Mem Agent reaches you during setup. It checks in with the relevant note or a useful first step. Capture and organize normally in Mem. Your notes stay visible and editable; your Agent uses them to understand what matters and help you follow through. Hold your desktop shortcut, speak, and release to send with…from get.mem.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.
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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, August 2026
the whole month →- TL
Life & fun · 10d 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 · 17d ago · simedw.com