Kevin Frans @kvfrans
@berkeley_ai prev mit, read my thoughts: https://t.co/7CZsOTsiH8 kvfrans.com Cambridge, MA Joined August 2013-
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Our computer vision textbook is released! Foundations of Computer Vision with Antonio Torralba and Bill Freeman mitpress.mit.edu/9780262048972/… It’s been in the works for >10 years. Covers everything from linear filters and camera optics to diffusion models and radiance fields. 1/4
Gave a lecture on Diffusion Models yesterday with @wilson1yan and @kvfrans youtu.be/DsEDMjdxOv4?si… Thanks to it being Lecture 6 into the semester (rather than Lecture 1), we could even include Sora, Mobile Diffusion, SDXL-Lightning :)
Excited to share LAnguage Reward Modulation for Pretraining Reinforcement Learning! LAMP💡pretrains a language-conditioned agent without human supervision using VLM rewards and unsupervised reinforcement learning w/ @amberxie_ @carlo_sferrazza @younggyoseo @stepjamUK @pabbeel
I explored some simple implementations of generative models. Conclusions: VAE and Diffusion work pretty well, GANs and PixelRNN are tricky. kvfrans.com/a-brief-examin…
Presenting Powderworld at #ICLR2023 today! Check us out at 3:30 in AD10 for the oral talk, and 4:30-6:30 for poster sessions. Since the original release, we've added agent-like elements, 40+ unique RL tasks, and more! w/ @phillip_isola
Presenting Powderworld at #ICLR2023 today! Check us out at 3:30 in AD10 for the oral talk, and 4:30-6:30 for poster sessions. Since the original release, we've added agent-like elements, 40+ unique RL tasks, and more! w/ @phillip_isola https://t.co/7rA0cBtZAK
excited to share I will be starting my PhD this fall at @berkeley_ai advised by @pabbeel ! looking forward to working with some amazing people. and, a giant thanks to all of you who have been supporting me so far :)
Goal-reaching / instruction-following is a major driver of new AI advances (LLM as general task solver, controlled generation). The revolution will not be single-task. Our newest work is all about the *geometric* structure emerging in multi-task RL: tongzhouwang.info/quasimetric_rl 1/n
🧵You have a PyTorch model, an environment, and an RL framework. They should work together but don't. Today, I'm releasing PufferLib, a toolkit that makes them play nice. Initial support for CleanRL and RLlib. pufferai.github.io
AK @_akhaliq
310K Followers 3K Following AI research paper tweets, ML @Gradio (acq. by @HuggingFace 🤗) dm for promo follow on Hugging Face: https://t.co/q2Qoey80Gx
Jim Fan @DrJimFan
229K Followers 3K Following @NVIDIA Sr. Research Manager & Lead of Embodied AI (GEAR Lab). Creating foundation models for Humanoid Robots & Gaming. @Stanford Ph.D. @OpenAI's first intern.
Eric Jang @ericjang11
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Julian Togelius @togelius
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Sebastian Risi @risi1979
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Eugene Vinitsky @EugeneVinitsky
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Shane Gu @shaneguML
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Lana Sinapayen @sina_lana
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Danijar Hafner @danijarh
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Bert Chan @BertChakovsky
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Tim Rocktäschel @_rockt
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Justin Pinkney @Buntworthy
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Jack Clark @jackclarkSF
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482 Followers 3K Following Visiting Researcher @gatech_scs | Senior Undergraduate in CS at IIT Delhi | Research in PL+ML | Learning Category Theory | Sports + Music + Food (in that order)
Sai Prasanna @sai_prasanna
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35 Followers 62 Following
Cuong (Johnny) Nguyen @johnny_ckmjx
116 Followers 408 Following 🇻🇳 PhD in NLP/HCI at @ICatGT! BS in Computer Science at @GTComputing. Researcher in Social Computing, Social NLP & LLMs
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Rohit Singh @RohitSi79044113
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Charles @JamesSimon16428
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Mark @Rybchuk
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Yunshuang_Li @YunshuangL
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20 Followers 45 Following
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25 Followers 121 Following
Rakib Islam @jahin114
176 Followers 778 Following Drug Discovery @MDAndersonNews, Ex-Research Scientist @facebook, PhD from @WSUPullman, worked on Machine Learning, Anomaly detection, @escenic and @samsung
Zeng Yuwei @pluviophile16
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Andrej Karpathy @karpathy
979K Followers 905 Following 🧑🍳. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets 🧠🤖💥
Yann LeCun @ylecun
712K Followers 719 Following Professor at NYU. Chief AI Scientist at Meta. Researcher in AI, Machine Learning, Robotics, etc. ACM Turing Award Laureate.
Google DeepMind @GoogleDeepMind
944K Followers 275 Following We’re a team of scientists, engineers, ethicists and more, committed to solving intelligence, to advance science and benefit humanity.
Eric Jang @ericjang11
69K Followers 3K Following physical AGI at 1X. Author of "AI is Good for You" https://t.co/eFg4WXhg0p
Julian Togelius @togelius
18K Followers 1K Following AI and games researcher. Associate professor at NYU; director of @NYUGameLab; co-founder of https://t.co/FnakJLkAXW.
Sebastian Risi @risi1979
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Eugene Vinitsky @EugeneVinitsky
13K Followers 2K Following Anti-cynic. Artificial narrow intelligence. Autonomous vehicles, multi-agent learning, and transportation. RS at Apple, Asst. Prof at @nyutandon. He/him.
Shane Gu @shaneguML
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80K Followers 122 Following Associate Professor at UC Berkeley Co-founder, Physical Intelligence
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Danijar Hafner @danijarh
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Alex Mordvintsev @zzznah
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Natasha Jaques @natashajaques
25K Followers 1K Following Senior Research Scientist at @GoogleAI and Assistant Professor @uwcse. Social Reinforcement Learning in multi-agent and human-AI interactions. PhD from @MIT.
Phillip Isola @phillip_isola
13K Followers 156 Following Associate Professor in EECS at MIT, trying to understand the science of intelligence.
Bert Chan @BertChakovsky
5K Followers 773 Following Artificial life researcher @GoogleDeepMind (formerly Brain). Hongkonger. Neurodiversity is biodiversity.
Tim Rocktäschel @_rockt
29K Followers 1K Following Open-Endedness Team Lead @GoogleDeepMind, Professor of AI @AI_UCL, PI @UCL_DARK, @ELLISforEurope Scholar. ex @MetaAI (FAIR), @CompSciOxford. Opinions my own.
Rivers Have Wings @RiversHaveWings
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Bam4d @Bam4d
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Chuan Wen @ChuanWen15
133 Followers 150 Following PhD student @Tsinghua_IIIS. Visitor @berkeley_ai w/ @pabbeel .
Karl Pertsch @KarlPertsch
1K Followers 206 Following Robot Foundation Models @ UC Berkeley & Stanford | Postdoc w/ Sergey Levine & Chelsea Finn | Prev. Intern @ Google Brain, Meta AI | PhD @ USC.
Jyothir S V @jyothir_s_v
84 Followers 231 Following Researcher at @NYU under @ylecun. FOSS Contributor, IITian. Musing on AI, Future.
Cristina Pinneri @CristinaPinneri
219 Followers 99 Following « And this gray spirit yearning in desire To follow knowledge like a sinking star, Beyond the utmost bound of human thought. »
Lerrel Pinto @LerrelPinto
5K Followers 181 Following Assistant Professor of CS @nyuniversity. I like robots!
Oier Mees @oier_mees
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Ellis Brown @_ellisbrown
357 Followers 939 Following CS PhD Student @NYU_Courant | Prev: @CarnegieMellon, https://t.co/EkTzprGc4i, @VanderbiltU
Zhao-Heng Yin @zhaohengyin
90 Followers 223 Following Computer Science PhD student @UCBerkeley BAIR @Berkeley_AI. Make Robots Work.
Younggyo Seo @younggyoseo
588 Followers 584 Following Research Scientist @Dyson Robot Learning Lab / Prev: Ph.D @ KAIST w/@jinwoos0417, Visitor @ UC Berkeley w/@pabbeel
Stephen James @stepjamUK
4K Followers 177 Following Leading the @Dyson Robot Learning Lab. Postdoc @UCBerkeley w/ @pabbeel. PhD Imperial College London w/ @ajdDavison. AI, Robotics, Machine Learning 🤖
Kuan Fang @KuanFang
2K Followers 663 Following Incoming Assistant Professor at Cornell CS (Fall 2024) | Postdoc at UC Berkeley & Researcher at Boston Dynamics AI Institute | Previously PhD at Stanford
Amy Lu @amyxlu
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8K Followers 389 Following Code, AI, and 3D printing. Opinions are my own, not my computer's...for now. Husband of @thesamnichol. Co-creator of DALL-E 2. Researcher @openai.
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2K Followers 277 Following PhD student @MIT_CSAIL @MITEECS, Ex @GoogleDeepMind, @berkeley_ai; Doing AI & Robotics. Foundational model for decision making. World models and robotics.
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Angjoo Kanazawa @akanazawa
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Aviral Kumar @aviral_kumar2
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Seyone Chithrananda @SeyoneC
2K Followers 3K Following 🇨🇦 in SF | cs/bioe @ucberkeley, sidequesting @BerkeleyML | learning @doudna_lab | prev: @MSFTResearch, @dyno_tx
John So @johnrso_
363 Followers 380 Following robots @1x_tech, @stanford | prev @berkeley_ai, prez @BerkeleyML, @accel scholars
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Huazhe Harry Xu @HarryXu12
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Kevin Black @kvablack
373 Followers 73 Following phd @berkeley_ai, deep reinforcement learning + robotics
Ademi Adeniji @AdemiAdeniji
385 Followers 180 Following PhD @UCBerkeley. Prev @NVIDIAAI, @Stanford '21. Reinforcement Learning, Robot Learning, Behavior Foundation Models.
Haoyu Xiong @Haoyu_Xiong_
2K Followers 2K Following Grad student researcher @CMU_Robotics/ I work on robotic agents in the real world #robotlearning
Alejandro Escontrela @alescontrela
841 Followers 344 Following PhD Student @ UC Berkeley | Formerly Google DeepMind
Harry Zhang @HarryZhangOG
422 Followers 298 Following PhD student @MIT Quant Researcher. Prev. @CMU_Robotics @berkeley_ai
Nicklas Hansen @ncklashansen
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Alon Albalak @AlbalakAlon
887 Followers 465 Following CS PhD candidate at @ucsbNLP. Research: Data-centric AI, Efficiency in ML, NLP.
Kimin @kimin_le2
1K Followers 330 Following Assistant professor at KAIST. Prev: Research scientist @GoogleAI, Postdoc @berkeley_ai & Ph.D at KAIST.
Dibya Ghosh @its_dibya
1K Followers 392 Following I do RL research @UCBerkeley | Previously @ Google Brain Montreal
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350 Followers 260 Following PhD student at UC Berkeley @berkeley_ai
Michael Nielsen @michael_nielsen
96K Followers 6K Following Searching for the numinous 🇦🇺 🇨🇦, home in 🇺🇸 Research @AsteraInstitute https://t.co/maezekzRUb
Eva Yi Xie @EvaYiXie
161 Followers 162 Following ug @MIT ‘24 @MIT_CBMM. 🔜 Incoming PhD student in Neuroscience @PrincetonNeuro. Incoming summer intern @AllenInstitute
Stephanie Fu @xkungfu
438 Followers 185 Following PhD student @berkeley_ai | studying computer vision and intelligence | Previous: B.S. M.Eng, CS + Music @MIT
a new blog post, because it is Saturday. <Fixing DPO but I have a dinner reservation …> kyunghyuncho.me/a-proper-prefe…
A fun short lecture on parallelization for training large models: youtu.be/Hr2FWHBuNXs by @wilson1yan and @haoliuhl
Our computer vision textbook is released! Foundations of Computer Vision with Antonio Torralba and Bill Freeman mitpress.mit.edu/9780262048972/… It’s been in the works for >10 years. Covers everything from linear filters and camera optics to diffusion models and radiance fields. 1/4
My time visiting Berkeley is coming to an end. Many thanks to Prof. Pieter Abbeel @pabbeel and Xingyu @Xingyu2017 for your guidance. Grateful to every member of RLL; your companionship and friendship are my most precious memories. Wishing you all the best for the future!
Lots of fun discussions about CS, research and life here and back home ❤️
Roamed around SF with @Cinnabar233 today!
Can LLMs ace LeetCode? 😱 Can LLMs repair, execute, and predict test outputs? 😲 🏖️🤖🏋️Introducing LiveCodeBench - holistic - contamination-free - four code tasks - easy, med, hard splits ❌LLMs CANNOT do LeetCode! The best model gets ~6% on LCB-hard 💻livecodebench.github.io
📢📢Excited to introduce our new work LiveCodeBench! 📈 Live evaluations to ensure fairness and reliability 🔍 Holistic evaluations using 4 code-related scenarios 💡Insights from comparing 20+ code models 🚨🚨We use problem release dates to detect and prevent contamination
Very excited to share what our research team at Covariant has been working on: RFM-1, our latest Robotics Foundation Model. Built on top of high-quality multimodal data the Covariant robotics fleet has collected over the years, this project embodies our commitment to pushing the…
Excited to share my recent research, SELFI about RL in UC Berkeley and Toyota Motor North America. Our self-improving RL, SELFI fine-tunes the pre-trained model-based control policy by model-free RL. @shahdhruv_ @KyleStachowicz @ajaysridhar0 and @svlevine
Functional reward encodings (FRE) provide a general way to train universal policies: the policy is conditioned on an embedding of functions and trained on a large randomized distribution of rewards. It can then generalize to new reward functions! kvfrans.com/fre/ Thread👇
FRE is perhaps the most flexible and general way to pre-train diverse policies from unlabeled data. The key idea is very simple: encode the reward *function* itself 🙂 Check out Kevin’s thread!
Functional Reward Encodings (FRE) provide a simple, unsupervised approach to offline zero-shot RL: 1. Learn a robust latent space of reward functions, then 2. Train a generalist agent on *random functions*, such that new tasks naturally map to solutions. kvfrans.com/fre/
How can we train LLM Agents, to learn from their own experience autonomously? Introducing ArCHer, a simple (i.e., small change on top of standard RLHF) and effective way of doing so with multi-turn RL 🧵⬇️ Paper: arxiv.org/abs/2402.19446 Website: yifeizhou02.github.io/archer.io/
Hilbert foundation policies (HILPs) provide a way to train general-purpose policies in an unsupervised way from offline data: analyze a dataset of trajectories, learn a metric space of behaviors, and then solve new tasks in zero- or few-shot! seohong.me/projects/hilp/ A thread 👇
Are game engines world simulators? Given a mesh+texture, a game can render a beautiful depiction of tree bark. But, typically, it doesn't model how the bark came to be in the first place, how the mesh+texture were created. Gen models, in a sense, do. 1/3
Excited to share "Hilbert Representations for Foundation Policies", our new method to pre-train a generalist policy from unlabeled data! Website: seohong.me/projects/hilp/ A thread ↓:
Gave a lecture on Diffusion Models yesterday with @wilson1yan and @kvfrans youtu.be/DsEDMjdxOv4?si… Thanks to it being Lecture 6 into the semester (rather than Lecture 1), we could even include Sora, Mobile Diffusion, SDXL-Lightning :)
Latent space planning. Took me a while to understand why each maze path has two latent paths.
Super honored to have been shortlisted for the George Girault PhD award, the most prestigious recognition for a robotics dissertation in Europe! Congrats to the other finalists too!
HNY! Excited to share SynCLR, that rivals CLIP and Dino v2 but uses pure synthetic data. The interesting part - it can outperform models (e.g. CLIP) directly trained on LAION-2B, which was the dataset used to train SD 1.5 that we used to generate images. arxiv.org/abs/2312.17742
Emergent intelligence from scratch
went home after #NeurIPS2023 and entered year 4 of "can stephanie eat 52 pomegranates before going back to school"
year 3: flew back home for winter break today and was met with my annual antioxidant boost of 52 pomegranates for $13
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