I made you a list of everyone in robotics:
ROBOTICS
-
2018 autonomous vehicle struggles with lane keeping and urban navigation
By
–
You all need to suffer the way I did. When I got my 2018 it barely could stay in the lane and didn’t drive through city at all! 🙂
-
NeuralFeels: Neural Fields for Visuotactile In-Hand Manipulation
By
–
Newly published in this issue of Science Robotics today from Meta FAIR: NeuralFeels with neural fields — Visuotactile perception for in-hand manipulation https://
go.fb.me/2cv7r6 -
Tesla’s New End-to-End Highway Stack Transforms Autonomous Driving
By
–
Mine has, but depends on the circumstances. Also, our Y just got new end-to-end highway stack, and that will behave far differently than previous FSDs.
-
Dogs Learn Better From Own Actions Than Expert Data
By
–
Having the dog learn from its own actions is essential. The team put LucidSim against the alternative, where an expert teacher provides substantially more training data. Robots learn from expert data only succeeded 15% of the time — and even quadrupling the amount of expert
-
LucidSim Surpasses Domain Randomization for Robot Navigation
By
–
LucidSim outperforms domain randomization, a go-to method from 2017 that produces diverse data, but lacks realism. LucidSim addresses both diversity & realism problems, helping a robot recognize and navigate obstacles in real environments.
-
Dreams In Motion accelerates robot visual simulation 7x faster
By
–
To make short, 140 millisecond videos that serve as visual "experiences" for the robot, the scientists hacked together a trick called "Dreams In Motion (DIM)" using a mix of image magic.
— MIT CSAIL (@MIT_CSAIL) 13 novembre 2024
This trick made LucidSim 7x times faster by moving pixels of a single generated image… pic.twitter.com/SzAeznWhWWTo make short, 140 millisecond videos that serve as visual "experiences" for the robot, the scientists hacked together a trick called "Dreams In Motion (DIM)" using a mix of image magic. This trick made LucidSim 7x times faster by moving pixels of a single generated image
-
AI-Generated Images Train Robot Dog Parkour Without Real Data
By
–
LucidSim used AI-generated images to train a robot dog to do parkour — w/o real-world data.
-
MIT LucidSim Uses GenAI Physics Engines Robot Training
By
–
For roboticists, one challenge towers above the others: there isn’t enough data.
— MIT CSAIL (@MIT_CSAIL) 13 novembre 2024
To accelerate the deployment of intelligent robots in the real world, MIT CSAIL’s "LucidSim" uses genAI & physics engines to create diverse & realistic virtual training grounds for robots. W/o any… pic.twitter.com/vISnzrv7QJFor roboticists, one challenge towers above the others: there isn’t enough data. To accelerate the deployment of intelligent robots in the real world, MIT CSAIL’s "LucidSim" uses genAI & physics engines to create diverse & realistic virtual training grounds for robots. W/o any
-
Revolutionary Innovation in American Transportation Industry
By
–
He's the only one who innovated in America's transportation industry. Agree. No other can do this: https://
x.com/TeslaCamera/st
atus/1856600732222296396
…