Sumeet Singh

66 posts

Sumeet Singh

Sumeet Singh

@Sumeet_Robotics

Research scientist at Google Brain Robotics in NYC. All views are my own.

New York, NY Katılım Ağustos 2018
176 Takip Edilen493 Takipçiler
Sumeet Singh retweetledi
Google DeepMind
Google DeepMind@GoogleDeepMind·
We’re making robots more capable than ever in the physical world. 🤖 Gemini Robotics 1.5 is a levelled up agentic system that can reason better, plan ahead, use digital tools such as @Google Search, interact with humans and much more. Here’s how it works 🧵
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Google DeepMind
Google DeepMind@GoogleDeepMind·
Meet Gemini Robotics: our latest AI models designed for a new generation of helpful robots. 🤖 Based on Gemini 2.0, they bring capabilities such as better reasoning, interactivity, dexterity and generalization into the physical world. 🧵 goo.gle/gemini2-roboti…
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Thomas Lew
Thomas Lew@thomas__lew·
Presenting our robotic table wiping work today at 3pm, Pod 15 at #ICRA2023 ➡️ Come have a chat about reinforcement learning, trajectory optimization, and stochastic dynamics modeling
Thomas Lew@thomas__lew

📢Excited to share our #ICRA2023 work on robotic table wiping via RL + optimal control! 📖 arxiv.org/abs/2210.10865 🎥 youtu.be/inORKP4F3EI 💡RL (for high-level planning) + trajectory optimization (for precise control) can solve complex tasks without on-robot data collection ⬇️

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Sumeet Singh
Sumeet Singh@Sumeet_Robotics·
A summary of Google Robotics in 2022, including our work on novel trajectory optimizers and applications!
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Kevin Patrick Murphy
Kevin Patrick Murphy@sirbayes·
Great article on LLMs - MLE training is exactly lossy data compression! I know RLHF is changing the loss to maximize predicted human ratings, but it still feels like a bit like lipstick on a pig to me (although who doesnt like bbq now and then? ;) newyorker.com/tech/annals-of…
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Sumeet Singh
Sumeet Singh@Sumeet_Robotics·
Check out the table-wiping robot from Thomas' internship! Great example of combining the strengths of RL and classical trajectory optimization for modularity, generalization, and efficient learning. Disclaimer: surface cleaner sold separately 🙃
Thomas Lew@thomas__lew

📢Excited to share our #ICRA2023 work on robotic table wiping via RL + optimal control! 📖 arxiv.org/abs/2210.10865 🎥 youtu.be/inORKP4F3EI 💡RL (for high-level planning) + trajectory optimization (for precise control) can solve complex tasks without on-robot data collection ⬇️

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Sumeet Singh
Sumeet Singh@Sumeet_Robotics·
@lucacarlone1 Congrats, Luca! Can you find my 2019 paper hidden somewhere in the review abyss? 😬
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Luca Carlone
Luca Carlone@lucacarlone1·
I've joined the editorial board of the International Journal of Robotics Research (IJRR) as a Senior Editor. I'm excited and honored to help reshape the future of IJRR, with a renewed commitment to providing informative and timely reviews. Send your best papers! #IJRR #robotics
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Sundar Pichai
Sundar Pichai@sundarpichai·
Work from our @GoogleAI team - training robots to play table tennis to better understand how they learn in dynamic + high-speed settings. One project achieved a 300+ hit rally, while another is focused on matching the precision of amateur human players 🏓 ai.googleblog.com/2022/10/table-…
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Sumeet Singh
Sumeet Singh@Sumeet_Robotics·
Come check out this workshop on Monday at #RSS2022! I'll be presenting (poster + spotlight) our latest work on multiscale sensor fusion architectures for continuous-time control using Neural CDEs.
Ajay Mandlekar@AjayMandlekar

Our #RSS2022 workshop on "Overlooked Aspects of Imitation Learning" is this Monday June 27 - join us virtual or in-person! We have a wonderful lineup of speakers (@ancadianadragan @ankurhandos @chelseabfinn @LerrelPinto Mohi Khansari @shimon8282) See: tinyurl.com/2pjt86uk

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Sumeet Singh
Sumeet Singh@Sumeet_Robotics·
Results show significant stability and convergence benefits on difficult planning problems. Official code-release as part of the google/trajax library (github.com/google/trajax) is on the way!
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