How to Kill the Dead Internet
Ok, so maybe "how to revive the internet" would be more accurate, but if you're reading this, I got your attention, right? Here's why I want you to read on: I built a free extension, D-slop, to disincentivize anyone from posting AI writing, and eventually images and video as well, on the internet. For writing, it checks known vocab and punctuation tells, as well as subtler tells related to cadence, and assigns it a score subject to an adjustable threshold. If the text fails, users have the option to flag offending text, hide it, or block the page entirely (with the option to see anyway). For…
In plain words
D-slop is a free browser extension that detects AI-generated text on websites by analyzing vocabulary, punctuation, and cadence patterns, then assigns a detection score. Users can flag, hide, or block content that exceeds an adjustable threshold. The tool is designed to reduce AI-generated content online and help users avoid misinformation. A version for detecting AI-generated images and video is in development, though image detection currently relies on C2PA metadata that is often stripped from social media platforms.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Ok, so maybe "how to revive the internet" would be more accurate, but if you're reading this, I got your attention, right? Here's why I want you to read on: I built a free extension, D-slop, to disincentivize anyone from posting AI writing, and eventually images and video as well, on the internet. For writing, it checks known vocab and punctuation tells, as well as subtler tells related to cadence, and assigns it a score subject to an adjustable threshold. If the text fails, users have the option to flag offending text, hide it, or block the page entirely (with the option to see anyway). For media, it's admittedly fairly weak, as it relies on C2PA metadata which is stripped from all of the social media sites where it would be most helpful. (Anyone else have chronically online boomer parents continually gobbling up slop like it's real information?) I have a D-slop+ version in the works that should be able to handle the media itself, but it's going to have to make API calls to have real teeth, which means I can't offer it for free. If this extension validates the concept, I'm happy to build it for y'all. Yes, I vibe-coded it, but an ancillary bonus to the project accrued when it inspired me to cook dinner listening to Metallica's "Fight Fire with Fire," which in turn brought my 5 y/o running into the kitchen with every musical instrument in the house for an impromptu karaoke speed metal session. It's MIT license open-source, full brief at https://github.com/jared-the-automator/d-slop; This forum is full of people smarter than me, so I'm open to suggestions.
More ai this month
the category →
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 · 26d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com