Today Hugging Face (LeRobot) & Yaak are releasing the worlds largest open source self driving dataset for training end-to-end models.
We are inviting the entire AI & robotics community to search curate datasets for training end2end models.
To search the data, Yaak is launching Nutron - A tool that is revolutionizing natural language search of robotics data. Check out the video to see how it works (We promise to step-up our video game some day)
TL;DR
Natural language search of multi-modal data
Open sourcing L2D dataset - 5,000 hours of multi-modal self-driving data
Community powered dataset curation.
Tech Blog: https://lnkd.in/dPaPv554
Try Nutron: https://lnkd.in/dvBzAX5N
Is it possible to sift through the set and create a selection of instances where the self-driving vehicles hit birds, curbs, and run over wildlife critters and train a model specifically on those?
Let’s take some liberty with the fact that if we’re going to train things, shouldn’t we understand the worst case outcomes possible as a ground to check against?
You can search the dataset and curate dataset collections.
We are releasing a TriageAI soon. Trained in expert behavior it will score all the data compared to what a driving instructor would do. If the driving decision deviates too much from what a local expert would have done, the scenario will get a low score.
Next version of search you will be able to search the dynamic environment in the scene as well.
You can already now search harsh breaking events etc.
Today Hugging Face (LeRobot) & Yaak are releasing the worlds largest open source self driving dataset for training end-to-end models.
We are inviting the entire AI & robotics community to search curate datasets for training end2end models.
To search the data, Yaak is launching Nutron - A tool that is revolutionizing natural language search of robotics data. Check out the video to see how it works (We promise to step-up our video game some day)
TL;DR Natural language search of multi-modal data Open sourcing L2D dataset - 5,000 hours of multi-modal self-driving data Community powered dataset curation. Tech Blog: https://lnkd.in/dPaPv554 Try Nutron: https://lnkd.in/dvBzAX5N
[flagged]
Noob here doing noob things
You can't have both text and and a link in most posts but it doesn't really matter, either is fine.
very cool!
Is it possible to sift through the set and create a selection of instances where the self-driving vehicles hit birds, curbs, and run over wildlife critters and train a model specifically on those?
Let’s take some liberty with the fact that if we’re going to train things, shouldn’t we understand the worst case outcomes possible as a ground to check against?
You can search the dataset and curate dataset collections. We are releasing a TriageAI soon. Trained in expert behavior it will score all the data compared to what a driving instructor would do. If the driving decision deviates too much from what a local expert would have done, the scenario will get a low score.
Next version of search you will be able to search the dynamic environment in the scene as well.
You can already now search harsh breaking events etc.