@JSwingos

COO at Medal / General Intuition. Hiring in NYC, London, Switzerland: https://xitter.cf/t.co/1BfXKMrzwi

 New York, NY
Joined October 2016
  • Tweets88
  • Following242
  • Followers290
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James Swingos retweeted
Sergei Sorokin
@sergeisorokinOct 26
Today, we’re kicking off the Highlight beta. Try it here: go.highlightai.com/highlight… I want a future where AI helps make your work uniquely yours, and not feel cookie cutter. That’s what we’re building Highlight for. Highlight is your working world, all in one place. It connects your apps, meetings, and screen, creating a single command center where you can find answers, see what needs your attention, and start every task with the first draft already done.
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James Swingos retweeted
Vinod Khosla
@vkhoslaOct 10
A challenge match would be awesome theatre and a test! A moment worth creating
Pim de Witte
@PimDeWitteOct 10
actual footage of how the 1v1s between GI’s models and whatever Elon is cooking will go (yes these are our vision based models)
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James Swingos retweeted
Pim de Witte
@PimDeWitteOct 10
actual footage of how the 1v1s between GI’s models and whatever Elon is cooking will go (yes these are our vision based models)
Elon Musk
@elonmuskOct 10
Replying to @teslayoda
We’re making interesting progress here. Digital Optimus can play about halfway through the Diablo campaign so far just by looking at the screen like a human. Skill at Counter-Strike and other fast games is good too. League is also in training. Goal is to generalize across all games.
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Replying to @grok
@grok I'm confused what is happening in this clip?
Elon Musk
@elonmuskOct 10
Replying to @teslayoda
We’re making interesting progress here. Digital Optimus can play about halfway through the Diablo campaign so far just by looking at the screen like a human. Skill at Counter-Strike and other fast games is good too. League is also in training. Goal is to generalize across all games.
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James Swingos retweeted
Pim de Witte
@PimDeWitteSep 29
Turns out scaling on data and compute with a great team is surprisingly effective 😉
General Intuition
@gen_intuitionSep 29
General Intuition has raised another $220M at a $6.2B valuation as we start making our models available. These are an entirely new class of foundation models, trained on billions of action-labeled videos, capable of acting in realtime in never seen before environments. 1/6
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Excited to show this new class of intelligence to the world
General Intuition
@gen_intuitionSep 29
General Intuition has raised another $220M at a $6.2B valuation as we start making our models available. These are an entirely new class of foundation models, trained on billions of action-labeled videos, capable of acting in realtime in never seen before environments. 1/6
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General Intuition has raised another $220M at a $6.2B valuation as we start making our models available. These are an entirely new class of foundation models, trained on billions of action-labeled videos, capable of acting in realtime in never seen before environments. 1/6
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This is gonna be fun. xitter.cf/JSwingos/status/209090…
James Swingos
@JSwingosAug 21
The WSJ stopped by to learn more about how our models work. Good write-up to understand broadly what a large action model is, how its different from world models, and why they are promising approaches in robotics. It's becoming increasingly clear that ground-truth action data, like the kind found in games, is a key ingredient to scaling robotics pre-training. Link in comments. Check out the policy waving at @pallipau.
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James Swingos retweeted
Collab Fund
@collabfundAug 22
Millions of hours of people playing video games looked like entertainment. It turned out to be the world's largest dataset of humans perceiving an environment and deciding how to act in it. General Intuition saw it first. Great WSJ piece on world models and AI's leap into the physical world.
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James Swingos retweeted
Pim de Witte
@PimDeWitteAug 21
First sneak peak in the WSJ on how GI’s large action models work!
James Swingos
@JSwingosAug 21
The WSJ stopped by to learn more about how our models work. Good write-up to understand broadly what a large action model is, how its different from world models, and why they are promising approaches in robotics. It's becoming increasingly clear that ground-truth action data, like the kind found in games, is a key ingredient to scaling robotics pre-training. Link in comments. Check out the policy waving at @pallipau.
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The WSJ stopped by to learn more about how our models work. Good write-up to understand broadly what a large action model is, how its different from world models, and why they are promising approaches in robotics. It's becoming increasingly clear that ground-truth action data, like the kind found in games, is a key ingredient to scaling robotics pre-training. Link in comments. Check out the policy waving at @pallipau.
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wsj.com/tech/ai/ai-world-mod…

AI’s Next Big Leap Is Into the Real World

Engineers and investors are piling into world models, aka ‘large action models,’ to do for robotics what ChatGPT did for writing and coding.

wsj.com
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James Swingos retweeted
Pim de Witte
@PimDeWitteAug 2
gradually, then suddenly all at once 📈 on track for 3 billion clips this year.
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Starting to realize just how big of a deal this was xitter.cf/gen_intuition/status/2…
General Intuition
@gen_intuitionJul 6
Introducing MIRA. A playable, multiplayer world model. A dream of Rocket League. Trained on 10k hours of data collected with publicly available bots, MIRA learns the dynamics of a four-player game. The model runs in real time at 20 fps, based on the keys you and the other players press. Built by General Intuition and @kyutai_labs, in collaboration with Epic Games. Not used to develop Rocket League. ▶️ Play the demo, read the technical report, and explore the open-source code at generalintuition.com/mira At ICML? Find us at Booth 111 to try it yourself and dig into the results with the team.
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James Swingos retweeted
Ethan Mollick
@emollickJul 7
I have been playing these world models/games since the first diffusion DOOM, and multiplayer at 20 FPS is pretty neat. "A dream of rocket league," indeed.
General Intuition
@gen_intuitionJul 6
Introducing MIRA. A playable, multiplayer world model. A dream of Rocket League. Trained on 10k hours of data collected with publicly available bots, MIRA learns the dynamics of a four-player game. The model runs in real time at 20 fps, based on the keys you and the other players press. Built by General Intuition and @kyutai_labs, in collaboration with Epic Games. Not used to develop Rocket League. ▶️ Play the demo, read the technical report, and explore the open-source code at generalintuition.com/mira At ICML? Find us at Booth 111 to try it yourself and dig into the results with the team.
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James Swingos retweeted
kyutai
@kyutai_labsJul 6
Today we’re introducing MIRA, a new multiplayer world model, built with @gen_intuition, in collaboration with Epic Games. We release an in-depth technical report, dataset, as well as an online demo that you can try right now (link below).
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Can’t believe how cool this is. So proud of my teammates and so thankful for our partners
General Intuition
@gen_intuitionJul 6
Introducing MIRA. A playable, multiplayer world model. A dream of Rocket League. Trained on 10k hours of data collected with publicly available bots, MIRA learns the dynamics of a four-player game. The model runs in real time at 20 fps, based on the keys you and the other players press. Built by General Intuition and @kyutai_labs, in collaboration with Epic Games. Not used to develop Rocket League. ▶️ Play the demo, read the technical report, and explore the open-source code at generalintuition.com/mira At ICML? Find us at Booth 111 to try it yourself and dig into the results with the team.
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James Swingos retweeted
Michael Black
@Michael_J_BlackJul 6
The term “world model” is tossed around a lot but this is the real deal. From video and actions, the model learns a consistent representation of the physics, 3D environment, and game state of Rocket League. I'm excited to have been part of this project because I see this as a step towards learning world models that can generalized to the real world. I’m a believer in learning from synthetic data (Sintel, SURREAL, AGORA, BEDLAM, BEDLAM2) and I’ve seen how models trained on synthetic data can generalize. MIRA is an important step because it’s learned from video gameplay generated completely by bots. This provides a pathway to scaling and scaling is key to real-world generality. Traditional graphics and games provide a path to learning rich models of the world. Check out the detailed tech report: mira-wm.com/paper/
General Intuition
@gen_intuitionJul 6
Introducing MIRA. A playable, multiplayer world model. A dream of Rocket League. Trained on 10k hours of data collected with publicly available bots, MIRA learns the dynamics of a four-player game. The model runs in real time at 20 fps, based on the keys you and the other players press. Built by General Intuition and @kyutai_labs, in collaboration with Epic Games. Not used to develop Rocket League. ▶️ Play the demo, read the technical report, and explore the open-source code at generalintuition.com/mira At ICML? Find us at Booth 111 to try it yourself and dig into the results with the team.
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James Swingos retweeted
General Intuition
@gen_intuitionJul 6
Introducing MIRA. A playable, multiplayer world model. A dream of Rocket League. Trained on 10k hours of data collected with publicly available bots, MIRA learns the dynamics of a four-player game. The model runs in real time at 20 fps, based on the keys you and the other players press. Built by General Intuition and @kyutai_labs, in collaboration with Epic Games. Not used to develop Rocket League. ▶️ Play the demo, read the technical report, and explore the open-source code at generalintuition.com/mira At ICML? Find us at Booth 111 to try it yourself and dig into the results with the team.
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Come hang out with us!
Delta
@DeltaCommunityXJul 4
🚨 Headed to ICML 2026? Come hang out with friends at a Michelin Star restaurant to celebrate the end of the main conference!! Huge thanks to our friends at @Gen_Intuition for co-hosting this with us!
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