Chris Lu
@_chris_lu_
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Research @OpenAI Prev: DPhil Student @UniofOxford, RS Intern @SakanaAILabs @DeepMind and RS @CovariantAI
Joined November 2014
Excited to share The AI Scientist! We use LLMs to autonomously come up with research ideas, implement them, do literature search, write them up, and review them -- producing full-length papers on AI without human intervention. Co-led with @cong_ml and @RobertTLange
Introducing The AI Scientist: The world’s first AI system for automating scientific research and open-ended discovery! https://t.co/8wVqIXVpZJ From ideation, writing code, running experiments and summarizing results, to writing entire papers and conducting peer-review, The AI
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It's getting harder and harder to get signal from benchmark numbers. Rather than averages, I except in the (near) future we will also care about "argmax": what's the BEST output a model can deliver? After all, we don't need to solve PvsNP 10 out of 10 times, once is enough 😅. So
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✨ GPT-5 crossed a major threshold: over the last two months, we’ve heard repeated examples of scientists successfully directing GPT-5 to do novel research in math, physics, biology, CS, and more. If you have an example to share, please reply below! Prizes for the best ones 🧵👇
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Yet more evidence that a pretty major shift is happening, this time by Scott Aaronson https://t.co/R1kPhCWhwD
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Our general-purpose reasoning models solved all 12 problems at the 2025 International Collegiate Programming Contest (ICPC) World Finals, the world’s top university programming competition which was enough for a 1st-place human ranking.
1/n I’m really excited to share that our @OpenAI reasoning system got a perfect score of 12/12 during the 2025 ICPC World Finals, the premier collegiate programming competition where top university teams from around the world solve complex algorithmic problems. This would have
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My team forced me to post this. It's definitely the last time I organize a nice offsite for them 😤😂
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GPT-5 is what you’ve been waiting for – it defines and extends the cost-intelligence frontier across model sizes today. it’s been a long journey, and we’ve landed pivotal improvements across many axes in the whole GPT-5 family. and hey no more model picker (by default)!
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Here at @OpenAI we've cracked pretraining, then reasoning, and now we're experimenting with a new set of techniques that maximally leverage their interaction. GPT-5 is just the first step in this direction, and we're incredibly excited to see where scaling this up will lead us!
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To be clear, my academic friends never actually gave me "crap", just some good-natured teasing. This tweet was meant in the same spirit. Also, by "We" I meant "OpenAI". Many others deserve far more credit than I do for making it happen.
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To all my academic friends who gave me crap for joining OpenAI: We just open-sourced some banger models. Have fun with them!
Our open models are here. Both of them. https://t.co/9tFxefOXcg
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Our open models are here. Both of them. https://t.co/9tFxefOXcg
openai.com
Advanced open-weight reasoning models to customize for any use case and run anywhere.
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We released two open-weight reasoning models—gpt-oss-120b and gpt-oss-20b—under an Apache 2.0 license. Developed with open-source community feedback, these models deliver meaningful advancements in both reasoning capabilities & safety. https://t.co/PdKHqDqCPf
openai.com
gpt-oss-120b and gpt-oss-20b push the frontier of open-weight reasoning models
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Recently, there has been a lot of talk of LLM agents automating ML research itself. If Llama 5 can create Llama 6, then surely the singularity is just around the corner. How can we get a pulse check on whether current LLMs are capable of driving this kind of total
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One promising direction is combining ideas from AlphaEvolve and the Darwin Gödel Machine. Imagine a self-referential system improving itself even at the lowest algorithmic levels at *scale* AlphaEvolve: https://t.co/vwBkEVNZu7 Darwin Gödel Machine:
arxiv.org
Today's AI systems have human-designed, fixed architectures and cannot autonomously and continuously improve themselves. The advance of AI could itself be automated. If done safely, that would...
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Introducing The AI Scientist-v2, which produced the 1st fully AI-generated paper to pass peer review at a workshop level (at @iclr_conf 2025)! Tech Report: https://t.co/HBXB7jUv5d GitHub: https://t.co/2SEMs0OOD7 V2 adds: 🧠 Agentic Tree Search (open-ended idea exploration) 💡
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The AI Scientist Generates its First Peer-Reviewed Scientific Publication We’re proud to announce that a paper produced by The AI Scientist-v2 passed the peer-review process at a workshop in ICLR, a top AI conference. Read more about this experiment → https://t.co/LpLYLnZMCQ
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Can AI Improve Itself? In an interview with @MLStreetTalk, co-first authors of “The AI Scientist” paper, Chris Lu, Cong Lu, and Robert Lange share their views on the recent and future development of Self-Improving AI. Watch the full podcast on YouTube → https://t.co/RIAwHjCSqR
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Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬 We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. The key contributions of our work are: 🕹️ Enables the
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