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PLPercy Liang, Professor, Stanford

Top 100 AI · United States

Percy Liang

Stanford United States

Score
7,4710 today
Rank
62/198 ↑7
over 90 days
+607+8.3%

Percy Liang is a professor of computer science at Stanford University, specializing in artificial intelligence and natural language processing. He co-founded TogetherCompute and Simile AI, and created the Marin community. His content focuses on AI model scaling, dataset composition, and technical insights into machine learning, often sharing detailed analyses and predictions related to large-scale AI training.

Data as of Oct 25, 2026.

The raw numbers · last 90 days

Median views
56K
per post
Median engagements
629
per post
Posts
15
over 90 days
Followers
127.4K
all scored platforms

What drives the score

Percentiles 0–100 against all tracked creators.

  • Reach · 30%88

    Average views per post over 90 days

  • Engagement · 30%76

    Average reactions per post

  • Audience · 30%75

    Total followers, relative to population

  • Consistency · 10%77

    Posting frequency (25 posts / 90 days = 100)

Platforms

127.4K total followers

PlatformFollowersScore
X@percyliang127.4K8,662t1

Last 30 days

Liang's top posts

  1. 🚢Marin 535B-A23B training has crossed the halfway mark! Some observations and learnings so far: https://t.co/tNhEWle6Mp
    X · 20 days ago#1
    PLPercy Liang, Professor, StanfordPercy Liang

    🚢Marin 535B-A23B training has crossed the halfway mark! Some observations and learnings so far: https://t.co/tNhEWle6Mp

    71.7K views1.1K engagements

  2. X · 13 days ago#2
    Most classes teaching the algorithms, but a lot of ML is about the empirical intuitions that develop from experience. This class systemizes this process. Assessment is next experiment prediction.
    PLPercy Liang, Professor, StanfordPercy Liang

    56.1K views1.1K engagements

  3. X · 28 days ago#3
    Given how many people have tried their hand at NanoGPT, I really didn't expect a 40% reduction in a single go!
    PLPercy Liang, Professor, StanfordPercy Liang

    74.1K views629 engagements

  4. X · 20 days ago#4
    What is the probability that Astra today can generate/forecast a particular new paper past its cutoff date? Naive sampling is intractable (tail probability is astronomically small). The key idea of priced guidance is …
    PLPercy Liang, Professor, StanfordPercy Liang

    28K views303 engagements

  5. X · 3 days ago#5
    The final stretch...
    PLPercy Liang, Professor, StanfordPercy Liang

    16.2K views229 engagements

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