This will remain open for another week: join us!

DeepMind's RL team is hiring a research scientist: if you're passionate about RL, come work with us!

And if you know people who might be interested, please share:
job-boards.greenhouse.io/deepmind/job...

RLC2026 Call for Workshops!

We’re already live: openreview.net/group?id=rl-...
Here's the opportunity to help shape the conference & spotlight your own RL focus areas.

Call: rl-conference.cc/call_for_wor...
Deadline: Mar 12 (AoE)

And don't forget the awesome banquet :) www.cirquedusoleil.com/ludo

Only ~7 days to go until the full paper deadline (Mar 5, AOE)! Wishing everyone a strong close to the submission cycle.

Hi RL Enthusiasts!

RLC is coming to Montreal, Quebec, in the summer: Aug 16–19, 2026!

Call for Papers is up now:
Abstract: Mar 1 (AOE)
Submission: Mar 5 (AOE)

Excited to see what you’ve been up to - Submit your best work!
rl-conference.cc/callforpaper...

Please share widely!

Could we meta-learn which data to train on? Yes!
Does this make LLM training more efficient? Yes!
Would you like to know exactly how? arxiv.org/pdf/2505.17895

(come see us at NeurIPS too!)

@rl-conference.bsky.social

Where do some of Reinforcement Learning's great thinkers stand today?

Find out! Keynotes of the RL Conference are online:
www.youtube.com/playlist?lis...

Wanting vs liking, Agent factories, Theoretical limit of LLMs, Pluralist value, RL teachers, Knowledge flywheels
(guess who talked about which!)

On my way to #ICML2025 to present our algorithm that strongly scales with inference compute, in both performance and sample diversity! 🚀

Reach out if you’d like to chat more!

Deadline to apply is this Wednesday!

The RL team is a small team led by David Silver. We build RL algorithms and solve ambitious research challenges. As one of DeepMind's oldest teams, it has been instrumental in building DQN, AlphaGo, Rainbow, AlphaZero, MuZero, AlphaStar, AlphaProof, Gemini, etc. Help us build the next big thing!

Ever thought of joining DeepMind's RL team? We're recruiting for a research engineering role in London:
job-boards.greenhouse.io/deepmind/job...
Please spread the word!

When faced with a challenge (like debugging) it helps to think back to examples of how you've overcome challenges in the past. Same for LLMs!

The method we introduce in this paper is efficient because examples are chosen for their complementarity, leading to much steeper inference-time scaling! 🧪

RLC Keynote speakers: Leslie Kaelbling, Peter Dayan, Rich Sutton, Dale Schuurmans, Joelle Pineau, Michael Littman

Some extra motivation for those of you in RLC deadline mode: our line-up of keynote speakers -- as all accepted papers get a talk, they may attend yours!

@rl-conference.bsky.social

200 great visualisations: 200 facets and nuances of 1 planetary story.

The sound of two users joining per second: "tik", "tok"...

David Silver - Towards Superhuman Intelligence - RLC 2024 YouTube video by Reinforcement Learning Conference

Reposting David Silver's talk about how RL is the way to intelligence. No particular reason
www.youtube.com/watch?v=pkpJ...

Announcement of Richard S. Sutton as RLC 2025 keynote speaker

Excited to announce the first RLC 2025 keynote speaker, a researcher who needs little introduction, whose textbook we've all read, and who keeps pushing the frontier on RL with human-level sample efficiency

Could language games (and playing many of them) be the renewable energy that Ilya was hinting at yesterday? They do address two core challenges of self-improvement -- let's discuss!

My talk is today at 11:40am, West Meeting Room 220-222, #NeurIPS2024
language-gamification.github.io/schedule/

Don't get to talk enough about RL during #neurips2024? Then join us for more, tomorrow night at The Pearl!

Dynamic programming has a fun origin story. In 1950, Bellman wanted to coin a term that "was something not even a Congressman could object to".
See here:
pubsonline.informs.org/doi/pdf/10.1...

This year's (first-ever) RL conference was a breath of fresh air! And now that it's established, the next edition is likely to be even better: Consider sending your best and most original RL work there, and then join us in Edmonton next summer!

Ohh... good morning to you too!

Clearly this got off on the wrong foot: do you want to try again, maybe more constructively (in the spirit of bluesky not being the other place)? This is a preprint, so I'd be happy to hear your suggestions for making it less "ignorant"...

Either one or many players. For "improvement" to be well-defined, one agent must be special (see footnote 6), but the multi-agent setting has many benefits.

Open-Endedness is Essential for Artificial Superhuman Intelligence In recent years there has been a tremendous surge in the general capabilities of AI systems, mainly fuelled by training foundation models on internetscale data. Nevertheless, the creation of openended...

1: open-ended means that it will keep producing novel and learnable artifacts (see the definition here: arxiv.org/abs/2406.04268), on the timescale of interest for the observer.

2: I think as a thought experiment it is valid, as it could work in principle, but of course it hasn't been built?

In section 5 (second paragraph), there's about a dozen references to language games people are already using (one per paper), some with ingenious ways to provide feedback.

Also, I suspect the workshop will ultimately have the poster abstracts online with plenty of additional material!

Language Gamification Workshop 2024 Join us for the Language Gamification Workshop 2024, featuring keynote speeches, panel discussions, and poster sessions.

I'll also be giving a talk about this at the @neuripsconf.bsky.social workshop on "Language Gamification" in two weeks. Pop by if you're around!

language-gamification.github.io

Boundless Socratic Learning with Language Games An agent trained within a closed system can master any desired capability, as long as the following three conditions hold: (a) it receives sufficiently informative and aligned feedback, (b) its covera...

Are there limits to what you can learn in a closed system? Do we need human feedback in training? Is scale all we need? Should we play language games? What even is "recursive self-improvement"?

Thoughts about this and more here:
arxiv.org/abs/2411.16905

@colah.bsky.social: with a few years' hindsight, how do you see the Distill space now? Is there a chance for a reboot or a rebirth in another form?

Distill — Latest articles about machine learning Articles about Machine Learning

I think the Distill journal was really valuable in this space, but unfortunately is no longer around to help...

distill.pub