Anycrap - The Store of Infinite Products
Turn any absurd idea into a full product page in seconds
What it does
Anycrap instantly generates complete product pages from any text - AI-crafted description, specs, pricing, and image. Type "Quantum Toilet" and get a fully realized product concept in seconds. Nothing is for sale. Nothing is useful. That's the point. 130,000+ absurd products already created by real people, from "Melatonin Coffee" to "Barbed Wire Toilet Paper." Browse the catalog, hit random, waste your afternoon. No signup, free, zero productivity gains guaranteed.
Does the same job
all alternatives →- ASA store that generates products from anything you type in searchSep 2025 · anycrap.shop · ▲1,184
- AOAnythingLLM – Open-Source, All-in-One Desktop AI Assistant2024 · github.com · ▲368
Hey HN! This is Tim from AnythingLLM (https://github.com/Mintplex-Labs/anything-llm). AnythingLLM is an open-source desktop assistant that brings together RAG (Retrieval-Augmented Generation), agents, embeddings, vector databases, and more—all in one seamless package. We built AnythingLLM over the last year iterating and iterating from user feedback. Our primary mission is to enable people with a layperson understanding of AI to be able to use AI with little to no setup for either themselves, their jobs, or just to try out using AI as an assistant but with *privacy by…
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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, March 2026
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Switch from ChatGPT to Claude with import memory feature
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