OrionReed

// 3D Dom viewer, copy-paste this into your console to visualise the DOM as a stack of solid blocks.
// You can also minify and save it as a bookmarklet (https://www.freecodecamp.org/news/what-are-bookmarklets/)
(() => {
  const SHOW_SIDES = false; // color sides of DOM nodes?
  const COLOR_SURFACE = true; // color tops of DOM nodes?
  const COLOR_RANDOM = false; // randomise color?
  const COLOR_HUE = 190; // hue in HSL (https://hslpicker.com)
  const MAX_ROTATION = 180; // set to 360 to rotate all the way round
  const THICKNESS = 20; // thickness of layers
  const DISTANCE = 10000; // ¯\\_(ツ)_/¯

rain-1

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

bendc

:root {
  --ease-in-quad: cubic-bezier(.55, .085, .68, .53);
  --ease-in-cubic: cubic-bezier(.550, .055, .675, .19);
  --ease-in-quart: cubic-bezier(.895, .03, .685, .22);
  --ease-in-quint: cubic-bezier(.755, .05, .855, .06);
  --ease-in-expo: cubic-bezier(.95, .05, .795, .035);
  --ease-in-circ: cubic-bezier(.6, .04, .98, .335);

  --ease-out-quad: cubic-bezier(.25, .46, .45, .94);
  --ease-out-cubic: cubic-bezier(.215, .61, .355, 1);

charlesroper

How to setup a practically free CDN using Backblaze B2 and Cloudflare

⚠️ Note 2023-01-21
Some things have changed since I originally wrote this in 2016. I have updated a few minor details, and the advice is still broadly the same, but there are some new Cloudflare features you can (and should) take advantage of. In particular, pay attention to Trevor Stevens' comment here from 22 January 2022, and Matt Stenson's useful caching advice. In addition, Backblaze, with whom Cloudflare are a Bandwidth Alliance partner, have published their own guide detailing how to use Cloudflare's Web Workers to cache content from B2 private buckets. That is worth reading,

rmcdongit

macOS 10.15 System Preference Panes

Below are a list of System Preference pane URLs and paths that can be accessed with scripting to assist users with enabling macOS security settings without having to walk them through launching System Preferences, finding panes, and scrolling to settings. Not all panes have an accessible anchor and some are OS specific.

To find the Pane ID of a specific pane, open the System Preferences app and select the desired Preference Pane. With the pane selected, open the ScriptEditor.app and run the following script to copy the current Pane ID to your clipboard and display any available anchors:

tell application "System Preferences"
	set CurrentPane to the id of the current pane
	set the clipboard to CurrentPane

DavidKuennen

(function (context, trackingId, options) {
    const history = context.history;
    const doc = document;
    const nav = navigator || {};
    const storage = localStorage;
    const encode = encodeURIComponent;
    const pushState = history.pushState;
    const typeException = 'exception';
    const generateId = () => Math.random().toString(36);
    const getId = () => {

SMUsamaShah

These are VMs running built with JavaScript/WASM allowing you to run an operating system within your browser, all client side.

Emulators

VMs

1. https://copy.sh/v86/
2. https://webvm.io/
3. https://bellard.org/jslinux/
4. https://jamesfriend.com.au/pce-js/ (https://github.com/jsdf/pce)

IanColdwater

Mute these words in your settings here: https://twitter.com/settings/muted_keywords

ActivityTweet
generic_activity_highlights
generic_activity_momentsbreaking
RankedOrganicTweet
suggest_activity
suggest_activity_feed
suggest_activity_highlights
suggest_activity_tweet

yoavg

Reinforcement Learning for Language Models

Yoav Goldberg, April 2023.

Why RL?

With the release of the ChatGPT model and followup large language models (LLMs), there was a lot of discussion of the importance of "RLHF training", that is, "reinforcement learning from human feedback". I was puzzled for a while as to why RL (Reinforcement Learning) is better than learning from demonstrations (a.k.a supervised learning) for training language models. Shouldn't learning from demonstrations (or, in language model terminology "instruction fine tuning", learning to immitate human written answers) be sufficient? I came up with a theoretical argument that was somewhat convincing. But I came to realize there is an additional argumment which not only supports the case of RL training, but also requires it, in particular for models like ChatGPT. This additional argument is spelled out in (the first half of) a talk by John Schulman from OpenAI. This post pretty much

shaps80

import SwiftUI

#if os(macOS)
public typealias Font = NSFont
public typealias FontDescriptor = NSFontDescriptor
#else
public typealias Font = UIFont
public typealias FontDescriptor = UIFontDescriptor
#endif