Alex Goldie
@AlexDGoldie
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RS intern @wayve_ai 🚗 PhD student at 🤖 @whi_rl and @flair_ox 🤖 First Class MEng from Oxford 🎓
Joined February 2017
1/ 🕵️ Algorithm discovery could lead to huge AI breakthroughs! But what is the best way to learn or discover new algorithms? I'm so excited to share our brand new @rl_conference paper which takes a step towards answering this! 🧵
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A great read - and very happy to see Kinetix featured!
🪩The one and only @stateofaireport 2025 is live! 🪩 It’s been a monumental 12 months for AI. Our 8th annual report is the most comprehensive it's ever been, covering what you *need* to know about research, industry, politics, safety and our new usage data. My highlight reel:
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Reinforcement Learning (RL) has long been the dominant method for fine-tuning, powering many state-of-the-art LLMs. Methods like PPO and GRPO explore in action space. But can we instead explore directly in parameter space? YES we can. We propose a scalable framework for
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I will be presenting MLGym at @COLM_conf 2025 in Montreal 🇨🇦 Excited to talk about Agents, RL environments, enabling open-ended exploration, user simulations for proactive agents and much more. Feel free to DM me if you would like to chat 🍁
🎉 Thrilled to share MLGym and MLGym-Bench, our new framework for AI Research Agents! 🚀 Developed during my Meta internship, MLGym provides a flexible environment for benchmarking and developing new agents for AI research tasks. 🔬 MLGym-Bench consists of 13 diverse AI research
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I think RL is all about learning from experience. Now *whose* experience -- that's a different question? Even if RL folks disagree with the above view -- it'd be great if we had RL methods that can learn from *arbitrary* experiences.
Offline RL is not RL. RL is about interaction. No interaction, no RL.
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(🧵) Today, we release Meta Code World Model (CWM), a 32-billion-parameter dense LLM that enables novel research on improving code generation through agentic reasoning and planning with world models. https://t.co/BJSUCh2vtg
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Incredibly well deserved! Congrats Matt, Uljad and Jarek! 🎉🎉
Unifloral has been accepted as an Oral at NeurIPS 2025! Immensely grateful to my @FLAIR_Ox co-authors @uljadb99 and @JarekLiesen for pouring months of effort into this project. There’s a ton of low-hanging fruit in offline RL… If you’re looking for a project, check it out!
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Seeking students & open-source contributors to join some ML-for-science projects at @huggingface. If you're curious about ML × biology or ML × materials science, this could be a great way to learn + contribute. I can offer Pro subs, support, and (for longer-term work)
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AIMS is an amazing PhD course for people interested in AI and ML! 100% worth applying to! If you're thinking about applying, and want to know more, feel free to drop me a message/email🤖🤖
We are now open to receive applications for entry in October 2026. Deadline is 28th January 2026. @aims_oxford @UniofOxford
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🚨🚨Introducing the FLAIR internship program!🚨🚨 We are looking for two talented students to join us for an internship working in FLAIR for 6 months (5th January to 4th July 2026)! For details and eligibility criteria, please check:
foersterlab.com
We are looking for two talented students to join us for an internship working in FLAIR for 6 months. Students will get the chance to work on current FLAIR projects at the University of Oxford,...
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Watch our second leg of the European Road Trip – this time we’ve gone from the grassy Scottish Highlands 🏴 and for the first time crossed the channel into mainland France 🇫🇷 In this leg the Wayve AI Driver navigated: Undulating hills in the Highlands 🏞️ Swindon’s “magic
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Super excited about this event! I will give an updated version of my talk on the Simulation Hypothesis - i.e. Machine Learning in the upcoming era of extremely fast computers. How can we do science that stands the test of time when compute capacity is accelerating?
🎆Keynote Speaker Spotlight: Prof. @j_foerst | @UniofOxford We are delighted to welcome Prof. @j_foerst, Associate Professor at @UniofOxford, as a Keynote speaker at the AE Global Summit on Open Problems for AI. Jakob leads one of the biggest modern ML labs in the UK
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RLC Keynotes are now live! Covering: Wanting vs liking, Agent factories, Theoretical limit of LLMs, Pluralist value, RL teachers, Knowledge flywheels... https://t.co/8b3Kp22llI
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We just released a new version of Syllabus! We have a demo notebook to help you get started, usability improvements, an implementation of Robust PLR, new versions of learning progress, and more! Check out this thread to learn how to get started with curriculum learning (CL)! 🧵
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E71: Jake Beck, Alex Goldie, & Cornelius Braun on Sutton's OaK, Metalearning, LLMs, Squirrels @ @RL_Conference 2025 A few thoughts with @jakeABeck, @AlexDGoldie and @corbraun after @RichardSSutton's fascinating lecture on his OaK architecture at @UAlberta
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I was happy to give a more technical talk on how we might create an AI at RLC-2025 and AGI-2025 (video below). The Oak Architecture: A Vision of Super-Intelligence from Experience As AI has become a huge industry, to an extent it has lost its way. What is needed to get us back on
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Always said I wanted to make it on a podcast in my PhD! ✅ Mission Accomplished!
E69: Outstanding Paper Award Winners 1/2 @RL_Conference 2025 @AlexDGoldie : How Should We Meta-Learn Reinforcement Learning Algorithms? @RyanSullyvan : Syllabus: Portable Curricula for Reinforcement Learning Agents @jsuarez5341 : PufferLib 2.0: Reinforcement Learning at 1M
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Meta RL at its finest! Great work and a super deserved award :))
🥳 It’s an honour to have been awarded the Outstanding Paper for Scientific Understanding in RL at RLC for our work, ‘How Should We Meta-Learn RL Algorithms?’ Thank you to the organisers @RL_Conference for putting on a great conference, and congratulations to the other winners!
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Huge congratulations to @AlexDGoldie! 🎉
🥳 It’s an honour to have been awarded the Outstanding Paper for Scientific Understanding in RL at RLC for our work, ‘How Should We Meta-Learn RL Algorithms?’ Thank you to the organisers @RL_Conference for putting on a great conference, and congratulations to the other winners!
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Congratulations on the great work Alex! Really nice paper and another excellent use of questions in paper titles.
🥳 It’s an honour to have been awarded the Outstanding Paper for Scientific Understanding in RL at RLC for our work, ‘How Should We Meta-Learn RL Algorithms?’ Thank you to the organisers @RL_Conference for putting on a great conference, and congratulations to the other winners!
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