
Slopper: Private AI Replies
Boost Social Engagement with Private, On-Device AI Replies
What it does
Replying to posts, joining conversations, and staying active. Who has the time? Slopper uses a powerful floating bubble to help you generate countless high-quality, relevant replies in any app. Engage with 10x more posts on X (Twitter), Instagram, Reddit, and more. Best of all, it runs 100% on your device. No servers, no tracking, and no one else training on your data. Boost your engagement without ever sacrificing your privacy.
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Slop GogglesMay 2026 · slopgoggles.ticekralt.com · ▲59Detect AI-generated comments and posts on Reddit
- SOSlop or not – can you tell AI writing from human in everyday contexts?Mar 2026 · slop-or-not.space · ▲19
I’ve been building a crowd-sourced AI detection benchmark. Two responses to the same prompt — one from a real human (pre-2022, provably pre prevalence of AI slop on the internet), one generated by AI. You pick the slop. Three wrong and you’re out. The dataset: 16K human posts from Reddit, Hacker News, and Yelp, each paired with AI generations from 6 models across two providers (Anthropic and OpenAI) at three capability tiers. Same prompt, length-matched, no adversarial coaching — just the model’s natural voice with platform context. Every vote is logged with model, tier, source, response…




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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, November 2025
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Life & fun · Nov 2025 · bitsnpieces.dev



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