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.

jawj

# using AWS Lightsail, Ubuntu 20.04
# in dashboard, allow TCP on port 5901


sudo apt update && sudo apt upgrade -y && sudo apt install -y \
  tigervnc-standalone-server tigervnc-xorg-extension \
  xfce4 wireshark node  # pick any window mgr, say yes to non-root packet capture


# set up VNC

ilyapuchka

// The issue with sectionHeadersPinToVisibleBounds and sectionFootersPinToVisibleBounds is that they do not pin 
// first header and last footer when bouncing. This layout subclass fixes that.

class StickyLayout: UICollectionViewFlowLayout {
    
    override init() {
        super.init()
        self.sectionFootersPinToVisibleBounds = true
        self.sectionHeadersPinToVisibleBounds = true
    }

hwayne

EXTENDS Integers, TLC, Sequences
CONSTANTS Devices

(* --algorithm BatchInstall
variables
  AppScope \in [Devices -> {0, 1}];
  Installs \in [Devices -> BOOLEAN];
  batch_pool = {};
  lock = FALSE;

yossorion

What I Wish I'd Known About Equity Before Joining A Unicorn

Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.

This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would

b1naryth1ef

Pillow

(64, 64)
        0.217446804047 total time
        217446.804047 ns / op
(128, 128)
        0.085732460022 total time
 85732.460022 ns / op

blainerothrock

#!/usr/bin/env xcrun swift -O

/*
gen.swift is a direct port of cfdrake's helloevolve.py from Python 2.7 to Swift 3
-------------------- https://gist.github.com/cfdrake/973505 ---------------------
gen.swift implements a genetic algorithm that starts with a base
population of randomly generated strings, iterates over a certain number of
generations while implementing 'natural selection', and prints out the most fit
string.
The parameters of the simulation can be changed by modifying one of the many

andymatuschak

A composable pattern for pure state machines with effects

State machines are everywhere in interactive systems, but they're rarely defined clearly and explicitly. Given some big blob of code including implicit state machines, which transitions are possible and under what conditions? What effects take place on what transitions?

There are existing design patterns for state machines, but all the patterns I've seen complect side effects with the structure of the state machine itself. Instances of these patterns are difficult to test without mocking, and they end up with more dependencies. Worse, the classic patterns compose poorly: hierarchical state machines are typically not straightforward extensions. The functional programming world has solutions, but they don't transpose neatly enough to be broadly usable in mainstream languages.

Here I present a composable pattern for pure state machiness with effects,

olih

Processing JSON using jq

jq is useful to slice, filter, map and transform structured json data.

Installing jq

On Mac OS

brew install jq

Avaq

const I  = x => x
const K  = x => y => x
const A  = f => x => f (x)
const T  = x => f => f (x)
const W  = f => x => f (x) (x)
const C  = f => y => x => f (x) (y)
const B  = f => g => x => f (g (x))
const S  = f => g => x => f (x) (g (x))
const S_ = f => g => x => f (g (x)) (x)
const S2 = f => g => h => x => f (g (x)) (h (x))