Xiaolong Wang retweeted
1/ muse spark open is the most capable US open-weight model to date.
816B total params, 42B active. 1M-token context. natively multimodal. built for coding and agentic work like long-horizon tasks, hard software engineering, multi-step reasoning.
america! 🇺🇲
816B total params, 42B active. 1M-token context. natively multimodal. built for coding and agentic work like long-horizon tasks, hard software engineering, multi-step reasoning.
america! 🇺🇲
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Xiaolong Wang retweeted
We're open-sourcing Muse Spark Open!
This is an important release which is the most capable US open-weight model yet. 🇺🇸
- 816B parameters (42B active)
- 1M token context window
- Built for coding and long-horizon agents
- Runs locally on two Apple M5 Ultra Mac Studios
More z7BNg0
This is an important release which is the most capable US open-weight model yet. 🇺🇸
- 816B parameters (42B active)
- 1M token context window
- Built for coding and long-horizon agents
- Runs locally on two Apple M5 Ultra Mac Studios
More z7BNg0
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Robots writing their own skills, and getting better and cheaper at it the more they practice.
Our G1 robot found its way to the pantry, picked up a Pringles can, and handed it over. No pre-built map. No training for this task.
Behind it is a coding agent, writing, running, and fixing the robot's programs as it goes. And it self-evolves: what works is saved as code for ining needed. This is ASENA.
Joint work with @Isabella__Liu, @edmund_bu, Johan Bjorck, @yin_hongxu, @zhengyiluo, @jankautz, @DrJimFan, @yukez, and @Sifei30488L. 🧵👇
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Xiaolong Wang retweeted
Our G1 robot found its way to the pantry, picked up a Pringles can, and handed it over. No pre-built map. No training for this task.
Behind it is a coding agent, writing, running, and fixing the robot's programs as it goes. And it self-evolves: what works is saved as code for ining needed. This is ASENA.
Joint work with @Isabella__Liu, @edmund_bu, Johan Bjorck, @yin_hongxu, @zhengyiluo, @jankautz, @DrJimFan, @yukez, and @Sifei30488L. 🧵👇
Behind it is a coding agent, writing, running, and fixing the robot's programs as it goes. And it self-evolves: what works is saved as code for ining needed. This is ASENA.
Joint work with @Isabella__Liu, @edmund_bu, Johan Bjorck, @yin_hongxu, @zhengyiluo, @jankautz, @DrJimFan, @yukez, and @Sifei30488L. 🧵👇
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Automatic scaling on how to play majiang?🤑
Can we scale robot learning without scaling human labor? 📈
Demonstrations, resets, failure recovery, constant supervision—collecting robot data still takes substantial human effort.
🔑 Three keys let agents take on more of the work:
1. Real2Sim2Real: Agents explore and learn trial and error is safer and cheaper.
2. Autonomous Recovery: Robots learn to recover from unexpected failures instead of waiting for human resets.
3. Human-on-Demand Learning: Multiple robots run in parallel, and humans step in only when autonomous recovery falls short.
🥑 Recova brings these together to get more robot learning out of every hour of human effort.
research.nvidia.com/labs/gear/reco…
Joint work with @anjjei, Johan Bjorck, @ZhidingYu, @yin_hongxu, @jankautz, @DrJimFan, @yukez, and @Sifei30488L.
👇 Here's how it works 🧵
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Xiaolong Wang retweeted
introducing muse wonder
our new frontier model. state-of-the-art at personal agents and professional agents.
our largest and most capable model yet—rivals the big bois
our new frontier model. state-of-the-art at personal agents and professional agents.
our largest and most capable model yet—rivals the big bois
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Xiaolong Wang retweeted
🚨 side project alert 🚨
Announcing Muse Gadgets, an open source ESP32 firmware and Linux sdk so that you can make hardware devices that work with Muse.
Grab an API token from gadgets.muse.ai and point your favorite coding agent at the github repo to build your own peripherals for Muse.
Announcing Muse Gadgets, an open source ESP32 firmware and Linux sdk so that you can make hardware devices that work with Muse.
Grab an API token from gadgets.muse.ai and point your favorite coding agent at the github repo to build your own peripherals for Muse.
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Looks solid.
Today we give Atlas dexterous hands, with the strength to take on real work, and the simplicity for mass manufacturing. Like the body, the hands are designed with high fidelity simulation in mind, to enable sim-to-real RL. If you give dexterous hands to a robot, make them do thoughts here
Blog: bostondynamics.com/blog/robot-han…
Video: youtube.com/watch?v=4whgw2…
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Xiaolong Wang retweeted
Meet FINGR: a dexterous hand that solves a 2×2 Rubik’s Cube with continuous finger tricks.
Here’s how we got the fingers to work together. 🧵
Here’s how we got the fingers to work together. 🧵
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Xiaolong Wang retweeted
1/ muse for small businesses 📊
we found lots of people using muse to run their small business. plumbing businesses, grocery stores, farms, restaurants, and shops.
today we're launching a bunch of connectors to make that easier!
we found lots of people using muse to run their small business. plumbing businesses, grocery stores, farms, restaurants, and shops.
today we're launching a bunch of connectors to make that easier!
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Xiaolong Wang retweeted
Teaming up with Shopify to make shopping and checkout easier in Muse. Shoppers find more. Shops sell more. More partnerships like this coming soon.
We are excited to announce we are partnering deeply with Muse to enable agentic checkout with Shop Pay on all Shopify stores, offering people an easy and delightful way to shop and check out with Muse.
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Xiaolong Wang retweeted
We are excited to announce we are partnering deeply with Muse to enable agentic checkout with Shop Pay on all Shopify stores, offering people an easy and delightful way to shop and check out with Muse.
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Super exciting!
some belated life updates: earlier this year, i left academia and joined meta to work on personal superintelligence. these days i’ve mostly been trying to make our models really good at browser use. back in 2020, i wrote in my phd sop that i hoped one day my mom could use a
i guess that day is here :)
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Xiaolong Wang retweeted
we're opening muse connectors to developers!
we have seen so much excitement in the developer community, integrating muse into everything from robots to mood lights and more.
plug your API into muse, then people can use your service just by asking for it. every request runs in ill ask before anything consequential.
come build with us! muse.ai/platform
we have seen so much excitement in the developer community, integrating muse into everything from robots to mood lights and more.
plug your API into muse, then people can use your service just by asking for it. every request runs in ill ask before anything consequential.
come build with us! muse.ai/platform
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Xiaolong Wang retweeted
Opening access for developers to build Muse connectors. You bring the API -- Muse brings the agent, the browser, and the context of what the person actually wants. People reach your service just by asking for it, and their agent takes it from there.
New connectors are live us. muse.ai/platform
New connectors are live us. muse.ai/platform
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Xiaolong Wang retweeted
muse for mac is HERE!! your agent can now get stuff done right on your computer — files, messages, calendar, notes, all of it.
you're in control of what it can access, and it always asks before doing anything sensitive.
Add it to the dock - ai.meta.com/muse/download/
you're in control of what it can access, and it always asks before doing anything sensitive.
Add it to the dock - ai.meta.com/muse/download/
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Xiaolong Wang retweeted
Evolving dexterity with GPT-6 Astra 🖐️
Been trying Astra recently. Its zero-shot dexterous manipulation is already quite surprising. More interesting is seeing it learn and improve through simulation training, from pen spinning and Rubik's Cube to hammer use.
The real goal dexterity in the real world.
github.com/jianglongye/de…
Been trying Astra recently. Its zero-shot dexterous manipulation is already quite surprising. More interesting is seeing it learn and improve through simulation training, from pen spinning and Rubik's Cube to hammer use.
The real goal dexterity in the real world.
github.com/jianglongye/de…
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