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Roberta Raileanu
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Roberta Raileanu

@robertarail
Open-Endedness Team Lead and Senior Staff Research Scientist @GoogleDeepMind. Adjunct Faculty @bold_lab_ai. ex @Meta | @NYU | @Princeton | IPhO | IOAA.
London, UK
Joined April 2013
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  • Pinned
    user avatar
    Roberta Raileanu
    @robertarail
    Jul 24, 2025
    I’m building a new team at @GoogleDeepMind to work on Open-Ended Discovery! We’re looking for strong Research Scientists and Research Engineers to help us push the frontier of autonomously discovering novel artifacts such as new knowledge, capabilities, or algorithms, in an
    job-boards.greenhouse.io
    DeepMind
  • user avatar
    Roberta Raileanu
    @robertarail
    Aug 26
    Amazing to see all the excitement around RSI, which finally feels within reach.  I pitched RSI back when I was at FAIR in 2023, right after we did Toolformer, which was arguably too early. But we got to see the first signs it may be possible while working on MLGym with
    user avatar
    Nathan Benaich
    @nathanbenaich
    Jul 9
    Replying to @raais @robertarail and @GoogleDeepMind
    and full talk here! youtu.be/Tek-FwtEwTk?si…
  • user avatar
    Roberta Raileanu
    @robertarail
    Aug 21
    Unique opportunity to do groundbreaking AI research in a vibrant academic lab with tons of freedom, compute, and ambition. Be BOLD and apply! 🦋
    user avatar
    Jakob Foerster
    @j_foerst
    Aug 21
    TL;DR: This is one of the most important and exciting opportunities in AI on the planet - please read on. The British Open-ended Learning & Discovery Lab is creating the perfect place for paradigm breaking AI research in the name of open-source and open-science. We have agency,
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  • user avatar
    Roberta Raileanu
    @robertarail
    Aug 17
    Combining LLMs with Bayesian methods could provide a path towards more efficient and principled automation of scientific discovery. Nice to see these explorations.
    user avatar
    Kevin Patrick Murphy
    @sirbayes
    Aug 12
    Predicting the answer to interventional "what if?" questions — the outcome of an action you never took — need a *mechanistic* model, not a curve fit. And you can only learn one by *experimenting*. Experiments are costly, so the real game is **data efficiency**. Meet the Model
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  • user avatar
    Roberta Raileanu
    @robertarail
    Aug 14
    Great to see more work on improving models at replicating research.
    user avatar
    Inherent
    @inherent_labs
    Aug 14
    1/ Today, we introduce Faraday, a 27B-parameter AI Scientist that extends the capabilities of coding agents with a layer of scientific intuition. Trained via long-horizon RL, Faraday outperforms Claude Opus 4.8 and GPT-5.5 on the task of replicating research papers. 🧵
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