@pantheoninc, prev posttrain @spacexsi
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Eric Li retweeted
We recently published the eight-week process behind scaling our UMI dataset to 1M+ tasks and 45k+ new tasks a day.
Now, we鈥檙e open-sourcing DiverseUMI-100, a collection of 12,000+ tasks from a 100-hour sample of our dataset, complete with dense annotations by Argus, our advanced robotics annotation pipeline.
How do you build the most diverse UMI dataset in robotics?
In the last 8 weeks, we scaled an international UMI data collection operation from 5 to 90 operators, built out a dataset of over 1M+ unique tasks, and continue to capture over 45k+ new tasks each day.
Robotic World Models require much higher diversity of tasks than imitation learning. Here's the why and how behind our operations. 馃У
Eric Li retweeted
Another cool update from the robotics world! While we're all wow-ed in mental land, there's a ton of progress and i feel like acceleration happening in physical land too now.
My guess is in good part also (but not only) thanks to the coding models progress over the last year.
How do you build the most diverse UMI dataset in robotics?
In the last 8 weeks, we scaled an international UMI data collection operation from 5 to 90 operators, built out a dataset of over 1M+ unique tasks, and continue to capture over 45k+ new tasks each day.
Robotic World Models require much higher diversity of tasks than imitation learning. Here's the why and how behind our operations. 馃У
Eric Li retweeted
How do you build the most diverse UMI dataset in robotics?
In the last 8 weeks, we scaled an international UMI data collection operation from 5 to 90 operators, built out a dataset of over 1M+ unique tasks, and continue to capture over 45k+ new tasks each day.
Robotic World Models require much higher diversity of tasks than imitation learning. Here's the why and how behind our operations. 馃У
Eric Li retweeted
We (@PantheonInc) have been working on a robotics data quality pipeline that uncovered a series of major problems in public robotics datasets, especially for world modeling.
To improve the quality of data available to open-source robotics, we're publishing annotations for four of the most popular datasets. Some examples of issues, and our report 馃У