Ask HN: AI Reading List

13•TheAlchemist•8mo ago

In the thread about John Carmack presentation, somebody mentioned the reading list he got from Ilya which were crucial to understand what matters and the current state of the knowledge (at the time).

After some googling, it seems like this list is plausible, although not confirmed: https://github.com/dzyim/ilya-sutskever-recommended-reading?tab=readme-ov-file

What would an actualized list look today ?

I'm asking since I'm taking a similar direction to Carmack (with maybe 1% of his talent and skills, but hey it's all about the journey !) in that I don't intend to work on improvement existing models, which I also believe are a road to nowhere, but rather understand things from the ground up, and maybe figure out 'something different' at the end.

Comments

MrCoffee7•8mo ago

I think a good approximation to getting a good current optimal list would be finding a syllabus online for a recent course offering in your AI area of interest. Most lists like that would combine some hands-on work with readings.

nextos•8mo ago

Kevin Murphy's book, particularly volume 2, is really well organized and summarizes the state of the art: https://probml.github.io/pml-book/book2.html

It's a really good entry point to current ML, written by an expert who has been in the field of generative models before they incorporated deep features.

tuyguntn•8mo ago

How do you find time to read 1300 page technical book? I admire people who do it for fun.

By the time I finish this book, probably SOTA will look totally different

nextos•8mo ago

I don't think his book is meant to be read from cover to cover. It's useful in many ways, as an outline, as a reference, or as an entry point to your niche of interest.

Let's say you are interested in diffusion models. You read the corresponding chapter (and play with the companion code).

If you are missing some background, you can also backtrack and skim through the initial chapters.

Show HN: WeaveMind – AI Workflows with human-in-the-loop

Show HN: Seedream 5.0: free AI image generator that claims strong text rendering

A contributor trust management system based on explicit vouches

Show HN: Analyzing 9 years of HN side projects that reached $500/month

The Floating Dock for Developers

Arcan Explained – A browser for different webs

We are not scared of AI, we are scared of irrelevance

Quartz Crystals

Show HN: I built a free dictionary API to avoid API keys

Show HN: Kybera – Agentic Smart Wallet with AI Osint and Reputation Tracking

Show HN: brew changelog – find upstream changelogs for Homebrew packages

Any chess position with 8 pieces on board and one pair of pawns has been solved

LLMs as Language Compilers: Lessons from Fortran for the Future of Coding

Projecting high-dimensional tensor/matrix/vect GPT–>ML

Show HN: Free Bank Statement Analyzer to Find Spending Leaks and Save Money

Our Stolen Light

Matchlock: Linux-based sandboxing for AI agents

Show HN: A2A Protocol – Infrastructure for an Agent-to-Agent Economy

Drinking More Water Can Boost Your Energy

Proving Laderman's 3x3 Matrix Multiplication Is Locally Optimal via SMT Solvers

Fire may have altered human DNA

"Compiled" Specs

The Next Big Language (2007) by Steve Yegge

Open-Weight Models Are Getting Serious: GLM 4.7 vs. MiniMax M2.1

Using AI for Code Reviews: What Works, What Doesn't, and Why

Show HN: Solnix – an early-stage experimental programming language

DoNotNotify is now Open Source

The British Empire's Brothels

What rare disease AI teaches us about longitudinal health

The Brand Savior Complex and the New Age of Self Censorship