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| // ==UserScript== | |
| // @name Hcaptcha Solver with Browser Trainer(Automatically solves Hcaptcha in browser) | |
| // @namespace Hcaptcha Solver | |
| // @version 10.0 | |
| // @description Hcaptcha Solver in Browser | Automatically solves Hcaptcha in browser | |
| // @author Md ubeadulla | |
| // @match https://*.hcaptcha.com/*hcaptcha-challenge* | |
| // @match https://*.hcaptcha.com/*checkbox* | |
| // @grant GM_xmlhttpRequest | |
| // @grant GM_setValue |
Build a polished, interactive 3D pop-up book called “A Day in the Forest” as a single self-contained HTML file. It should feel like a handcrafted paper theatre, not a flat web page with pictures pasted on it.
The book follows one forest day from dawn to night. It has six two-page spreads plus a front and back cover:
- Dawn — a doe and her fawn in a misty clearing.
- Morning — a red squirrel and a great spotted woodpecker in a big oak; the tree unfolds upward and becomes the tall centerpiece.
I liked the way Grokking the coding interview organized problems into learnable patterns. However, the course is expensive and the majority of the time the problems are copy-pasted from leetcode. As the explanations on leetcode are usually just as good, the course really boils down to being a glorified curated list of leetcode problems.
So below I made a list of leetcode problems that are as close to grokking problems as possible.
by Flamerix AI · MIT License
Platforms: Linux and Windows 11 tested by us; macOS reported by others. Tested on Claude Code 2.1.257–2.1.317. The binary is not modified (
BUN_OPTIONS=--preload). An update can silently undo it, so see Verify.
Every ~30 seconds, Claude Code re-sends each background agent's full transcript to the model to
Можно взять сервер у любого зарубежного хостинг-провайдера:
Across six instrumented PHP-backed web personas, a 26-hour, 43-minute capture recorded 30 pre-script out-of-memory errors and 11 worker crashes. The traffic included repeated leak-stage payloads, distributed fixed-length probes, serializer-oriented requests, and large chunked uploads. No remote code execution or usable memory disclosure was confirmed.
The observation window runs from 22 October 22:45 to 24 October 01:28 UTC. All times below are UTC; application names such as WordPress and Drupal refer to the presented web personas, not findings against those CMS products.
Jump to: Campaign overview · Source outcomes · Crash timeline · IP and reverse-DNS appendix · Request aggregates · Fingerprints · Request excerpts
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
Since the Edgerunners 2 update (2.5, October 22, 2026), the game crashes during startup on GTX 16xx cards under Proton. The Proton log shows:
Unsupported: %.i0134.cast.i0 = extractelement <8 x i4> %.i0134.cast, i64 0
Exception 0xc000001d at ... libnvidia-gpucomp.so.615.78.08 + 0x39b07e
err:vulkan:vkCreateComputePipelines Exception 0xc000001d in Unix call.
