# dzyim/ilya-sutskever-recommended-reading

It is said that, Ilya Sutskever gave John Carmack this reading list of ~ 30 research papers on deep learning.

Repository: https://github.com/dzyim/ilya-sutskever-recommended-reading
Canonical: https://ross.abutalabs.com/products/ilya-sutskever-recommended-reading
License Family: other
Last push: 2024-06-04T10:16:59+00:00

## Health v2 (maintenance only)
Score: 24/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 60
- inputs: {"age_days": 842, "days_push": 820, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1798, forks 195 (observed 2026-08-28T04:05:37.715344+00:00)

## What it is
A curated list of roughly 30 deep learning research papers and blog posts reportedly recommended by Ilya Sutskever to John Carmack. It is a link collection with no code, organizing foundational papers on transformers, RNNs, CNNs, and related topics.

## Use cases
- find a deep learning reading list recommended by Ilya Sutskever
- learn the fundamentals of transformers and neural networks from classic papers
- get a structured path into deep learning research literature
- find links to papers like Attention Is All You Need and AlexNet
- study what an AI research leader considers essential reading

## When to choose
- you want a curated, opinionated path through foundational deep learning papers
- you prefer learning from primary research literature and annotated blogs
- you want a quick reference of canonical paper links in one place

## When to avoid
- you need runnable code, tutorials, or exercises rather than paper links
- you want a comprehensive textbook-style curriculum with guidance
- you need up-to-date papers beyond the ~2020 era covered by the list

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: deep-learning, machine-learning, tutorials, artificial-intelligence
- platform: -
- tags: reading-list, research-papers, curated-links, transformers, neural-networks, web

## Member repositories
- dzyim/ilya-sutskever-recommended-reading (main) score 24

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:37.715344+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:22:26.025237+00:00, confidence not recorded.
  - readme: https://github.com/dzyim/ilya-sutskever-recommended-reading (fetched 2026-08-28T04:05:37.715344+00:00, sha d1204bbadbce)
- Data as of 2026-08-30T08:39:29.467469+00:00.