arinze19

Having worked remotely for the majority of my career, I've come to settle on this way of working and gathered a few resources that have helped me stay productive. Below I've shared some resources for people looking to transition into remote work or existing workers looking to improve their productivity. Please feel free to open up a PR and add more resources of your own.

Focusing

For the most part, focusing was something I struggled with since I was working out of my bedroom and any time I felt tired I could easily retire to my bed and spend a large chunk of time being unproductive. I counter-acted these habitts with some of the following tools

1. FocusMate - Productivity web application to enable you do deep work by pairing you with an accountability partner over video for a session of deep and focused work.
   • Free Plan: Limited to 3 sessions per week

• Paid Plan: Unlimited number of sessions a week

yinkakun

import Axios from "axios";
import Router from "next/router";

const API_URL = process.env.NEXT_PUBLIC_API_URL;

export const axios = Axios.create({
  baseURL: API_URL,
  headers: {
    "Content-Type": "application/json",
  },

biast12

// ==UserScript==
// @name Replaces the X logo with the old Twitter logo
// @description Replaces the X logo with the old Twitter logo by Biast12
// @icon https://abs.twimg.com/favicons/twitter.ico
// @version 1.0.6
// @author Biast12
// @namespace https://twitter.com/Biast12
// @homepageURL https://gist.github.com/biast12/04f66af3297b9395ec489f7eb16a9286
// @supportURL https://gist.github.com/biast12/04f66af3297b9395ec489f7eb16a9286
// @updateURL https://gist.github.com/biast12/04f66af3297b9395ec489f7eb16a9286/raw/Replace-twitter-logo.user.js

t3dotgg

// Types for the result object with discriminated union
type Success<T> = {
  data: T;
  error: null;
};

type Failure<E> = {
  data: null;
  error: E;
};

rain-1

How large are large language models? (2025)

This aims to be factual information about the size of large language models. None of this document was written by AI. I do not include any information from leaks or rumors. The focus of this document is on base models (the raw text continuation engines, not 'helpful chatbot/assistants'). This is a view from a few years ago to today of one very tiny fraction of the larger LLM story that's happening.

History

• GPT-2,-medium,-large,-xl (2019): 137M, 380M, 812M, 1.61B. Source: openai-community/gpt2. Trained on the unreleased WebText dataset said to 40GB of Internet text - I estimate that to be roughly 10B tokens. You can see a list of the websites that went into that data set here domains.txt.
• GPT-3 aka davinci, davinci-002 (2020): 175B parameters. There is a good breakdown of how those parameters are 'spent' here [How d

jbreckmckye

The Cloudflare outage was a good thing

Cloudflare, the CDN provider, suffered a massive outage today. Some of the world's most popular apps and web services were left inaccessible for serveral hours whilst the Cloudflare team scrambled to fix a whole swathe of the internet.

And that might be a good thing.

The proximate cause of the outage was pretty mundane: a bad config file triggered a latent bug in one of Cloudflare's services. The file was too large (details still hazy) and this led to a cascading failure across Cloudflare operations. Probably there is some useful post-morteming about canary releases and staged rollouts.