I built an open-source Grokipedia because Elon Musk forgot to
I built an open-source client version of Grokipedia. It transforms raw Grokipedia pages into a structured, navigable wiki experience with AI chat, mindmaps, and intelligent citations, while maintaining near-instant load times through aggressive caching (it currently only supports the ~800,000 articles that Grokipedia has indexed). Live at: https://deepgrokipedia.com Repo Link: https://lnkd.in/eywUy9i3
Does the same job
all alternatives →- LALurnby, a tool for better learning, is now open source2022 · github.com · ▲162
I've been working on Lurnby for 2 years. It's kind of like a mix of pocket + kindle + anki. It lets you => add add epubs, pdfs, and web articles to the app => highlight and add comments => tag and organize highlights => review them with a spaced repetition system Today I made the decision to open source the project. I'm passionate about helping other people learn to learn better and hope that this will allow a lot more innovation in the tool and the space. I'm very new to open source and development in general really, but looking forward to receiving the guidance of the community.
- GAGrok, a modern wiki for useful, concise, trustworthy content2018 · grok.how · ▲29
- RTReal-time Wiki2013 · document.ly · ▲76
- IOI Open Sourced Deepwiki2025 · github.com · ▲5
- TTTorchpad – The simplest way to make a wiki2014 · torchpad.com · ▲28
- DRDeep Research – Open-Source Customizable Reasoning Framework for Devs2025 · github.com · ▲7
The first ever AI peer reviewed research article just got approved. It’s kinda crazy how advanced AI have come to replace researchers. I've just been using Deep Research on ChatGPT and Perplexity a lot to write and research complex technical reports for my boss. He loves the reports and it has decreased my workload a ton but I still have some frustrations with it. None of them provide an API that gets me the same quality of output you would with the applications. I wanted something with more control on the LLMs, swappable with the reasoning new models that came out. Not just prompt →…
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
Astute▲585Automate your B2B brand going viral, with new media creators
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 · 27d ago · cactuscompute.com
Launched alongside, October 2025
the whole month →
- SA
I went down the rabbit hole on a side project and ended up building this: Strange Attractors(https://blog.shashanktomar.com/posts/strange-attractors). It’s built with three.js. Working on it reminded me of the little "maths for fun" exercises I used to do while learning programming in early days. Just trying things out, getting fascinated and geeky, and being surprised by the results. I spent way too much time on this, but it was extreme fun. My favorite part: someone pointed me to the Simone Attractor on Threads. It is a 2D attractor and I asked GPT to extrapolate it to…
AI · Oct 2025 · blog.shashanktomar.com
- ASAutism Simulator▲779
Hey all, I built this. It’s not trying to capture every autistic experience (that’d be impossible). It’s based on my own lived experience as well as that of friends on the spectrum. I'm trying to give people a feel for what masking, decision fatigue, and burnout can look like day-to-day. That’s hard to explain in words, but easier to show through choices and stats. I'm not trying to "define autism". I’ve gotten good feedback here about resilience, meds, and difficulty tuning. I’ll keep tweaking it. If even a few people walk away thinking, "ah, maybe that’s why my coworker struggles in those…
Life & fun · Oct 2025 · autism-simulator.vercel.app
