Natural language search on #Nutron: “Harsh braking on the motorway”. 7 scenarios found in the open L2D dataset hosted on Hugging Face—the largest dataset for autonomous driving research.
Try it now: https://t.co/aRZrOis5Jk
#AI#OpenSource#Autonomous
Natural language search on #Nutron: “Make a multilane right turn at the traffic lights”. 22 scenarios found in the open L2D dataset hosted on @huggingface the largest dataset for autonomous driving research.
Try it now: https://t.co/3ERJo79n8A
#AI#OpenSource#Autonomous
Natural language search on #Nutron: “Give way to any oncoming traffic, then enter the roundabout”. 293 scenarios found in the open L2D dataset hosted on @huggingface—the largest dataset for autonomous driving research.
Try it now: https://t.co/jVh23z8xYS
#AI#OpenSource#ML
@huggingface We’re expanding our open-source datasets across robotics, autonomous driving, and beyond. We’d love your input on which datasets you would like us to support!
Natural language search on #Nutron: "Harsh braking from a speed above 20". 270 scenarios found on the L2D dataset on @huggingface. The biggest open dataset for self-driving!
Try it yourself at https://t.co/y9ljGEVTAx
Just found 20k scenarios on the autobahn on L2D, the biggest open dataset for self-driving.
I am using @Yaak_AI 's search engine (cc @42loops)
More info in comments 👇
A banger just got released 💥
Here is a snapshot of L2D, the biggest self-driving dataset by far!
- 90 TeraBytes of data
- 5000 hours of driving
- 6 surrounding HD cameras
- OPENLY AVAILABLE
- Train your car to drive like @Tesla at home
🧵 More details in thread
A sneak peek 👀 of what our e2e AI for robotics (spatial intelligence) learns to attend, when trained entirely through self-supervision on RGB camera and expert policies. Zero annotations needed.
Attention visualized with Rerun (https://t.co/Qw6CLjHetg)