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Latest AI research, explained simply

New AI, tech and chip research in plain words, with a link to every source, plus the people worth following.

  • 8 top papers
  • 4 lab posts
  • 44 sources
  • Updated 18 Oct 2026

Today's top papers

Titles as the authors wrote them. A short plain line shows only when our research run explained the paper.

Most upvoted papers

Hugging Face Daily Papers, pulled 18 Oct. Number = community upvotes.

  1. 1FDE-Gym: The Last Mile of AI DeliveryNew studynot peer reviewed yetHugging Face Daily PapersRead more 281
  2. 2Behavioral Compositionality of Sparse Autoencoder RepresentationsNew studynot peer reviewed yetHugging Face Daily PapersRead more 104
  3. 3Can World and Action Modeling Benefit Each Other under Unified Causal Training?New studynot peer reviewed yetHugging Face Daily PapersRead more 40
  4. 4OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World ModelingNew studynot peer reviewed yetHugging Face Daily PapersRead more 32
  5. 5Data World: Scaling Data Environments from ScratchNew studynot peer reviewed yetHugging Face Daily PapersRead more 27
  6. 6Virtual Head AttentionNew studynot peer reviewed yetHugging Face Daily PapersRead more 9
  7. 7Beyond Policy Rollouts: Embedding-Space Directional Exploration with Anchored Noise for LLM RLVRNew studynot peer reviewed yetHugging Face Daily PapersRead more 8
  8. 8FlashMask-3: Efficient and Expressive Mask-Aware Distributed AttentionNew studynot peer reviewed yetHugging Face Daily PapersRead more 8

New from the labs

The newest post from each research lab blog we follow.

  • Google Research

    Grounding AI agents in biological reality: Building blocks for autonomous wet labsRead more

  • Google DeepMind

    Accelerating the search for antimicrobial peptides with Google AntigravityRead more

  • Microsoft Research

    Proof-based general-purpose computing with MagnetarRead more

  • Apple Machine Learning Research

    Local and Distributed Large LLM Inference with MLX and RDMA on Mac StudioRead more

Who to follow

30 people worth following for new research, each with links to their own posts.

Researchers 17

People doing the research, many with their own blogs.

  • Geoffrey Hinton

    'Godfather of AI', 2024 Nobel Prize in Physics, now warns about AI risks

    X profile

  • Yoshua Bengio

    Turing Award winner, leads Mila and the International AI Safety Report

    Website

  • Yann LeCun

    Turing Award winner, deep learning pioneer, ex-Meta chief AI scientist

    X profile

  • Fei-Fei Li

    Stanford professor who built ImageNet, co-founded World Labs

    X profile

  • Demis Hassabis

    Google DeepMind CEO, 2024 Nobel Prize in Chemistry for AlphaFold

    X profile

  • Ilya Sutskever

    OpenAI co-founder, now runs Safe Superintelligence (SSI)

    X profile

  • Jeff Dean

    Google's chief scientist, Gemini

    X profile

  • Andrew Ng

    Coursera and DeepLearning.AI founder, weekly newsletter The Batch

    X profileWebsite

  • Percy Liang

    Stanford, leads model testing (HELM) and open-model research

    X profile

  • François Chollet

    Made Keras, created the ARC-AGI test

    X profile

  • Jim Fan

    NVIDIA, robots and AI agents

    X profile

  • Noam Brown

    OpenAI, AI that reasons (o1), poker AI

    X profile

  • Melanie Mitchell

    Santa Fe Institute, clear-eyed takes on what AI can't do

    Blog feed

Explainers and influencers 10

People who read new papers and explain what they mean.

  • AK (Ahsen Khaliq)

    Posts new AI papers all day; runs Hugging Face Daily Papers

    X profile

  • Ethan Mollick

    Wharton professor, how AI changes work, blog One Useful Thing

    X profileBlog feed

  • Two Minute Papers (Karoly Zsolnai-Feher)

    YouTube: new papers explained in minutes

    YouTube feed

  • Yannic Kilcher

    YouTube: walks through papers line by line

    X profile

Hardware and chip voices 3

People who follow AI chips, data centers and computer design.

  • Ian Cutress

    Chip analyst, TechTechPotato on YouTube

    X profile

  • Jim Keller

    Legendary chip designer (AMD, Apple, Tesla), runs Tenstorrent

How we pick and check research
  • We pull 44 free sources every day: 9 paper feeds (Hugging Face Daily Papers and arXiv), 5 peer-reviewed journals, 9 lab blogs, 8 explainer sites, 13 researchers' own feeds.
  • Preprints (mostly from arXiv) are labeled New study and not peer reviewed yet: a new study says something, it is not proven.
  • Peer-reviewed means other scientists checked the paper before a journal printed it.
  • We never write a finding we can't source. Every item links to where it came from, and numbers come only from the paper itself.
  • The plain explanations come from our daily research run, which reads each pick. Top papers from the raw pull show only their title and source.
  • Top papers are ranked by Hugging Face community upvotes on the day we pulled them.
  • People are listed only as sources to follow, with links to their own posts. We never quote them.
  • Skipped: hacking tools, deepfakes and voice cloning, NSFW and the rest of our skip list.
All 44 sources
  • Hugging Face Daily Papers
  • arXiv: AI
  • arXiv: machine learning
  • arXiv: language (LLMs)
  • arXiv: vision
  • arXiv: robotics
  • arXiv: chips and hardware
  • arXiv: security
  • arXiv: quantum
  • Nature
  • Nature Machine Intelligence
  • Nature Electronics
  • Science
  • PNAS
  • Google Research
  • Google DeepMind
  • Microsoft Research
  • Apple Machine Learning Research
  • OpenAI
  • NVIDIA Technical Blog
  • Allen Institute for AI (Ai2)
  • Berkeley AI Research (BAIR)
  • MIT News: AI
  • Epoch AI
  • IEEE Spectrum
  • Quanta Magazine
  • ScienceDaily: AI
  • Chips and Cheese
  • ServeTheHome
  • Import AI (Jack Clark)
  • The Gradient
  • Andrej Karpathy
  • Lilian Weng
  • Sebastian Raschka
  • Nathan Lambert
  • Melanie Mitchell
  • Ethan Mollick
  • Simon Willison
  • swyx (Shawn Wang)
  • Dwarkesh Patel
  • Lex Fridman
  • Two Minute Papers (Karoly Zsolnai-Feher)
  • Gary Marcus
  • Dylan Patel