
creating intelligent robots @microagi | bitter-lesson pilled
SF/LDN
Joined April 2015
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moritz💭 retweeted
We're releasing dense Argus-format annotations for >5,000 hours (290k episodes) of public robot data (ABC-130k, MolmoAct2 YAM, DROID, GM-100, ABC-Sim), labeled with GPT 6.1 Sol.
Per-hand subgoals and actions, plus outcomes, mistakes, recoveries and object-state changes 👇🧵
🤗 huggingface.co/datasets/nkal…
moritz💭 retweeted
Very proud that Odyssey-3 is the most physics-accurate world model in...the world!
moritz💭 retweeted
Today we release FLUX 3 Action - an open-weight 7B world-action model, achieving SOTA performance and efficiency on various leaderboards such as RoboLab.
I am incredible proud of the team - and both backbone and embodiment-specific finetunes are open weight, alongside the training recipes!
Introducing FLUX 3 Action.
An open weights 7B World Action Model that achieves first place on the RoboLab benchmark.
It outperforms the previous best open model by 6.1 percentage points while using 56% fewer parameters and running up to 3.95x faster.
FLUX 3 Action removes the usual trade-off between world action model performance and VLA speed: it still predicts video and actions together, but plans more than twice as far ahead and runs faster per second of robot motion than the strongest open VLA.
Teams can fine-tune FLUX 3 Action on their own demonstrations to create policies for a particular robot and task. Together with @nvidia, we also integrated FLUX 3 Action natively into @huggingface's LeRobot, with fine-tuning recipes included and edge deployment on NVIDIA Jetson.
Beyond robotics, we’re also seeing promising results training task-specific policies for acting in simulated environments like gaming, controlling a vehicle, computer use, and wherever else a model needs to understand a visual environment and then choose what to do next.
FLUX 3 Action builds on the same image, video, and audio pretraining as FLUX 3, but uses a smaller architecture designed for practical deployment. In midtraining, we trained the model to predict actions and future frames together.
We’re releasing the weights, code, fine-tuning recipe, benchmarks, and reproducible examples so researchers and developers can build on the model with their own robots, environments, and tasks (see below).
moritz💭 retweeted
If you are in AI space lets grab some drinks together luma.com/wzgreunl









