matijagrcic

Ref: Exclusive Q&A: John Carmack’s ‘Different Path’ to Artificial General Intelligence

"So I asked Ilya Sutskever, OpenAI’s chief scientist, for a reading list. He gave me a list of like 40 research papers and said, ‘If you really learn all of these, you’ll know 90% of what matters today.’ And I did. I plowed through all those things and it all started sorting out in my head."

Ref: https://x.com/ID_AA_Carmack/status/1622673143469858816

I rather expected @ilyasut to have made a public post by now after all the discussion of the AI reading list he gave me. A canonical list of references from a leading figure would be appreciated by many. I would be curious myself about what he would add from the last three years.

Papers

eenblam

Linux Networking Reading List

Currently in no particular order. Most of these are kind of ancient.

Where's all the modern documentation? So much of what I've turned up searching is other folks complaining about having few options beyond reading source code.

The OREILLY books, while dated, seem to be some of the best available. Note that these can be read with a 7-day trial. Do this! At least get through the introduction section and first chapter of each to see if it's what you're after.

https://www.netfilter.org/

RabaDabaDoba

/*
 * This is free and unencumbered software released into the public domain.
 *
 * For more information, please refer to <https://unlicense.org>
 */

//Regular text
#define BLK "\e[0;30m"
#define RED "\e[0;31m"
#define GRN "\e[0;32m"

ncmiller

This is the process I followed on my Fedora 23 host machine to build a small/minimal vanilla Linux kernel and test in Qemu (based on this blog post). This will provide a safe sandbox in which to test kernel changes, and is generally faster than developing natively on the host machine. Qemu will boot the kernel image directly in the emulated system.

Install required build tools on host machine

sudo dnf install ncurses-devel kernel-devel kernel-headers gcc gcc-c++ git qemu openssl-devel glibc-static

Prepare a working space for kernel development