> now reading: Issue #001, coming soon
Deep dives you can actually finish, projects with real code, and resources worth bookmarking. No hype, no fluff, just the good stuff, explained properly.
> choose --level
Every post is tagged by difficulty, so you always know what you're getting into.
New to AI. Start with intuition and pictures. No math degree needed.
Rookie postsYou've run a notebook or two. Now learn how the internals actually work.
Hero postsPapers, math and production war stories. Bring coffee.
Legend posts> ls ./blog --latest
No issues published yet. The next panel is still being drawn.
> git log --projects
Real projects, real repos. Every one comes with a write-up of what worked and what didn't.
$ paperpal ask 2310.06825 "what is sliding window attention?"
→ answer + 3 citations (p.2, p.4, p.7)Chat with any arXiv paper. Every answer cites the page it came from.
$ python train.py --params 10M
step 4200 · loss 1.93 · "POW! said the robot"A 10M-parameter GPT trained from scratch on comic book dialogue.
$ arena vote --blind
model A vs model B · you picked BCompare two models side by side and vote blind. Results feed a live leaderboard.
> open ./resources
Hand-picked papers, courses, tools and datasets, bundled by topic. Each pick comes with a note on why it's worth your time.
One email every Friday: the new issue, one project update and three links worth your time.