veekaybee

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models

veekaybee

How are search and recommendations the same, and how are they different?

• Question on Mastodon
• Question on Twitter

TL;DR:

• The design of both search and recommendations is to find and filter information
• Search is a "recommendation with a null query"
• Search is "I want this", recommendations is "you might like this"

andrewp-as-is

#!/usr/bin/env bash
{ set +x; } 2>/dev/null

IFS=$'\n'
set "$@" $(find ~ -name ".*" ! -name ".CFUserTextEncoding" ! -type l -mindepth 1 -maxdepth 1) # dotfiles
set "$@" $(find ~ -name "Google *" -mindepth 1 -maxdepth 1) # Google Drive
set "$@" ~/git # store on github/etc :)
set "$@" ~/node_modules

set "$@" ~/Applications # install apps with brew cask

johnmyleswhite

Papers

Benchmarking seems not to be a main focus of any specific academic field, although the problem has been addressed by many different groups in CS.

Some papers I found interesting:

• http://research.microsoft.com/en-us/um/people/nswamy/papers/bottlenecks-ecoop04.pdf
• http://www.sigmod.org/publications/sigmod-record/0806/p45.dewitt.pdf
• http://daniel-wilkerson.appspot.com/trend-prof.pdf
• http://sape.inf.usi.ch/sites/default/files/publication/EvaluateCollaboratoryTR1.pdf