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.

countercept

import time
import etw
import etw.evntrace
import sys
import argparse
import threading


class RundownDotNetETW(etw.ETW):
    def __init__(self, verbose, high_risk_only):

ibraheem4

Installing Postgres via Brew

Pre-Reqs

Brew Package Manager

In your command-line run the following commands:

1. brew doctor
2. brew update

jFransham

Achieving warp speed with Rust

Contents:

• Number one optimization tip: don't
• Never optimize blindly
• Don't bother optimizing one-time costs
• Improve your algorithms
• CPU architecture primer
• Keep as much as possible in cache
• Keep as much as possible in registers

so0k

Kubectl output options

Let's look at some basic kubectl output options.

Our intention is to list nodes (with their AWS InstanceId) and Pods (sorted by node).

We can start with:

kubectl get no

mdwhatcott

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"strconv"
)

func main() {

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

hellerbarde

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs