Scott Cory
505 posts
Scott Cory
@slessans
robot intelligence @openai
San Francisco, CA انضم Mayıs 2010
1.1K يتبع1.8K المتابعون
if ruud comes back and wins he’ll be the first player in history to win 4-1 in a 5 setter
Tennis Updates@TennisUpdates26
Jim Courier "I'm not saying electronic line calling is perfect but it makes far fewer mistakes than humans. Matches should be decided by the players not by people, not in 2026." Every other tournament uses Hawkeye except Roland Garros.
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@slessans nvm just saw who the VP of robotics is ! Excited for what you guys ship now!
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this is the most ambitious, challenging and rewarding thing we are doing right now and if robotics is exciting to you, you should come join us. the team is incredible.
Sam Altman@sama
OpenAI Robotics is hiring, looking for exceptional full-stack hardware, ops, systems, and ML engineers to help us program and manufacture robots that are useful for society. AI should be able to help people in the physical world. In the short term, we are focused on robots to support skilled workers to build our future infrastructure; in the long term, we imagine everyone having a personal robot doing anything they need. Our world simulation research program, led by Aditya Ramesh (@model_mechanic), has evolved over the past year into OpenAI Robotics. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research. If you love working hands-on across the robotics stack and want to build the future, please consider joining us. Send an email with your background and evidence of exceptional accomplishment to: robotics-recruiting@openai.com
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Era of robots is nearing…
Sam Altman@sama
OpenAI Robotics is hiring, looking for exceptional full-stack hardware, ops, systems, and ML engineers to help us program and manufacture robots that are useful for society. AI should be able to help people in the physical world. In the short term, we are focused on robots to support skilled workers to build our future infrastructure; in the long term, we imagine everyone having a personal robot doing anything they need. Our world simulation research program, led by Aditya Ramesh (@model_mechanic), has evolved over the past year into OpenAI Robotics. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research. If you love working hands-on across the robotics stack and want to build the future, please consider joining us. Send an email with your background and evidence of exceptional accomplishment to: robotics-recruiting@openai.com
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@slessans Idk if it’s relevant…
But I use AI to pick up ducks 🤷♂️
KuphDev@KuphDev
No better way to celebrate Memorial Day than with robots! 🦾🇺🇸 GPUs were spinning thru the night and now I’ve got ACT policy chaining at 100% success after ~50 trials. Watch this: one policy places the orange duck, the next removes it. Clean handoff every time. TLDR: Instead of one giant combined policy, I train small atomic ones (place specific color, remove it, etc.) and stitch them together. The technique: capture an image from the overhead cam, feed it to a multimodal LLM (OpenAI) alongside a few labeled workspace examples + a good prompt. The AI then selects the right policy or flags any error states. Has anyone tried this atomic + LLM-selector approach with VLA models? I'm curious how the performance compares vs using a larger generalized model.
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OpenAI Robotics is hiring, looking for exceptional full-stack hardware, ops, systems, and ML engineers to help us program and manufacture robots that are useful for society.
AI should be able to help people in the physical world. In the short term, we are focused on robots to support skilled workers to build our future infrastructure; in the long term, we imagine everyone having a personal robot doing anything they need.
Our world simulation research program, led by Aditya Ramesh (@model_mechanic), has evolved over the past year into OpenAI Robotics. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research.
If you love working hands-on across the robotics stack and want to build the future, please consider joining us. Send an email with your background and evidence of exceptional accomplishment to: robotics-recruiting@openai.com
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robot intelligence is going to be interesting in a world that is increasingly inference flops pilled because you have a time constraint that naturally sets a hard limit on scaling on that axis
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Nobody actually buys new Aeron chairs in SF.
Every Aeron chair was created in a one-time Big Bang event during the first dotcom boom in 1999, and has been passed along from failed to new startup in an uninterrupted 30 year chain.
It’s the Law of Conservation of Aeron.
Marc Randolph@marcrandolph
One of my reliable signs that an early-stage company is in trouble: I walk in a few weeks after their seed round closes, and every employee is sitting in a $1,000 Aeron chair behind an automatic standing desk.
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medvedev is an agent of pure chaos and the atp tour is so much better because of him
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people be like “ai leads to brain fry” and then doom scroll for 5 hours
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@parmita tech employees don’t want you to find out this one simple trick
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this cheat code is also known as founding a startup
Forbes@Forbes
Greg Brockman Testifies Stake In OpenAI Worth Nearly $30 Billion—Despite Investing Nothing go.forbes.com/RN1F1T
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Never did I imagine a feature I worked on would lead to goblin amplification, but here I am. Happy reading to those of you who are goblin-curious.
OpenAI@OpenAI
We’re talking about Goblins. openai.com/index/where-th…
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The robotics thesis is being built on an analogy to LLMs that doesn't hold.
1/ Tokens compound. Manipulation data does not. Folding laundry teaches a robot nothing about stacking groceries.
2/ LLMs fail gracefully. Robots ... do not. The last 5% of reliability costs 10x the first 95% (just ask Waymo)
3/ LLMs got the internet for free. Every hour of robot data has to be bought.
4/ Software aggregates through an API. Physical deployments never have.
Bessemer@BessemerVP
𝐁𝐞𝐬𝐬𝐞𝐦𝐞𝐫 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐬: 𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐩𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐀𝐈 🤖 1. We're in the GPT-2.5 moment for robotics. Capabilities are real, but the gap between lab performance and field deployment remains wide. 2. Scaling laws are emerging. Data is expensive, capital is the moat. World models may be the shortcut. 3. Talent concentration will crown winners quickly. This is not a market where 50 companies win. 4. Near-term value will accrue to full-stack, vertically integrated players, not pure-play foundation model companies. 5. Defense robotics will produce the first $50B+ IPOs in the category. 6. There will be no robotics bubble. In fact, not enough capital is flowing into the industry. Dive in 🦾 bvp.com/atlas/bessemer…
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