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.

sebsto

# YouTube (english) : https://www.youtube.com/watch?v=FtU2_bBfSgM
# YouTube (french) : https://www.youtube.com/watch?v=VjnaVBnERDU

#
# On your laptop, connect to the Mac instance with SSH (similar to Linux instances)
#
ssh -i <your private key.pem> ec2-user@<your public ip address>

#
# On the Mac

faressoft

DOM Performance

• How the browser renders the document
  • Receives the data (bytes) from the server.
  • Parses and converts into tokens (<, TagName, Attribute, AttributeValue, >).
  • Turns tokens into nodes.
  • Turns nodes into the DOM tree.
• Builds CSSOM tree from the css rules.

gtallen1187

"Scar Tissues Make Relationships Wear Out"

04/26/2103. From a lecture by Professor John Ousterhout at Stanford, class CS142.

This is my most touchy-feely thought for the weekend. Here’s the basic idea: It’s really hard to build relationships that last for a long time. If you haven’t discovered this, you will discover this sooner or later. And it's hard both for personal relationships and for business relationships. And to me, it's pretty amazing that two people can stay married for 25 years without killing each other.

[Laughter]

> But honestly, most professional relationships don't last anywhere near that long. The best bands always seem to break up after 2 or 3 years. And business partnerships fall apart, and there's all these problems in these relationships that just don't last. So, why is that? Well, in my view, it’s relationships don't fail because there some single catastrophic event to destroy them, although often there is a single catastrophic event around the the end of the relation

djspiewak

Introduction to scalaz-stream

Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.

The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca

oakes

Contents

• Why care about Rust?
• The Toolchain
• Creating a New Project
• Modules
• Crates
• Types
• References
• Mutability

Kartones

PSQL

Magic words:

psql -U postgres

Some interesting flags (to see all, use -h or --help depending on your psql version):

• -E: will describe the underlaying queries of the \ commands (cool for learning!)
• -l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)

jestan

MAP Protocol Error Codes

Generic errors

34 System failure

35 Data Missing

36 Unexpected Data Value

21 Facility Not Supported

jestan

Mongo DB Repair

1) Remove mongod.pid file or mongod.lock file

2) Run './mongod --repair --dbpath <db-path>'

3) Run './mongo'
   
   //From Mongo Shell

jestan

#!/bin/bash 
while true; 
do { 
     echo -e "HTTP/1.1 200 OK\r\n"; cat www-doc/index.html;
} | nc -l 8080; 
done