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Lechao Xiao
211 posts
@Locchiu

Lechao Xiao

@Locchiu
Training @OpenAI & BK. Prev @GoogleDeepMind @GoogleBrain. Tackle scaling, along the path to AGI.
New York, NY
sites.google.com/site/lechaoxia…
Joined September 2009
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  • @Locchiu
    Lechao Xiao
    @Locchiu
    Sep 4
    I would expect a move 37 would look like Dvir’s proof of finite field Kakeya conjecture
    @jdlichtman
    Jared Duker Lichtman
    @jdlichtman
    Sep 4
    For a Move 37 impact in math, one would have to e.g. construct an original method or definition which reinvents the problem (or an entire field...) So far AI results have found (very clever) combinations of pre-existing techniques (to amazing effect, to be clear)
    2
  • @Locchiu
    Lechao Xiao
    @Locchiu
    Sep 3
    From rotating needles to gradient spikes
    Image
    @7homaslin
    Thomas Lin
    @7homaslin
    Sep 2
    Terence Tao wrote a clear, nontechnical explanation of the Kakeya Conjecture (for which Hong Wang won the Fields Medal in July), why it matters, how it was solved, and future directions, and posted it on the arXiv: arxiv.org/abs/2608.22209
  • @Locchiu
    Lechao Xiao
    @Locchiu
    May 10
    It was a record (still now?) arxiv.org/abs/1806.05393
    @_arohan_
    rohan anil
    Core Automation
    @_arohan_
    May 10
    Who has the deepest network of them all?
    1
  • @Locchiu
    Lechao Xiao
    @Locchiu
    May 7
    This is going to be a super fun workshop on scaling & learning dynamics & optimization! Please consider submitting your best work there!
    @poseypaquet
    Elliot Paquette
    @poseypaquet
    May 7
    The High-Dimensional Learning Dynamics Workshop @ ICML 2026 🇰🇷, with a special focus on scaling laws, is coming up, July 10! Submission Deadline: May 11 AoE (extended). @Locchiu @albertobietti @JustinLin610 @inbarser @BachFrancis @ShamKakade6 @andrewgwils @blake__bordelon
    Image
    Image
  • @Locchiu
    Lechao Xiao
    @Locchiu
    Feb 20
    The originality and the depth of science are really impressive. High thinking, signal to flop ratio. Congrats Damien, Elliot, Courtney et al.
    @damien_ferbach
    Damien Ferbach
    @damien_ferbach
    Feb 19
    1/10 We built ADANA, an optimizer that gets better as you scale. It extends AdamW with log-time schedules for momentum and weight decay — same hyperparameter count, no extra engineering. Scaled from 45M to 2.6B, it saves ~40% compute vs tuned AdamW, and the gap keeps growing.🧵
    Image
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