INSUBCONTINENT EXCLUSIVE:
Meta today presented V-JEPA 2, a 1.2-billion-parameter world model trained primarily on video to support understanding, prediction, and
planning in robotic systems
Built on the Joint Embedding Predictive Architecture (JEPA), the design is created to help robotics and other “& ldquo; AI representatives
& rdquo; navigate unfamiliar environments and jobs with limited domain-specific training.V-JEPA 2 follows a two-stage training procedure all
without extra human annotation
In the first, self-supervised phase, the model learns from over 1 million hours of video and 1 million images, catching patterns of physical
The 2nd stage introduces action-conditioned knowing utilizing a small set of robotic control information (about 62 hours), enabling the
model to consider representative actions when predicting outcomes
This makes the design usable for planning and closed-loop control tasks.Meta stated it has actually already checked this new model on
robotics in its laboratories
Meta reports that V-JEPA 2 performs well on common robotic tasks like and pick-and-place, utilizing vision-based goal representations
For easier jobs such as pick and place, the system creates prospect actions and examines them based upon forecasted outcomes
For tougher tasks, such as getting an object and putting it in the ideal spot, V-JEPA2 utilizes a series of visual subgoals to direct
behavior.In internal tests, Meta said the design revealed appealing capability to generalize to new things and settings, with success rates
varying from 65% to 80% on pick-and-place jobs in previously unseen environments.“& ldquo; We think world models will usher a brand-new
age for robotics, making it possible for real-world AI representatives to aid with chores and physical tasks without requiring astronomical
quantities of robotic training data,” & rdquo; said Meta & rsquo; s chief AI researcher Yann LeCun.Although V-JEPA 2 shows improvements
over previous designs, Meta AI stated there remains a noticeable space in between model and human performance on these benchmarks
Meta suggests this points to the need for designs that can run throughout numerous timescales and methods, such as incorporating audio or
tactile information.To examine development in physical understanding from video, Meta is likewise launching the following 3 criteria:
IntPhys 2: examines the design’& rsquo; s ability to compare physically possible and implausible scenarios.MVPBench: tests whether models
rely on real understanding instead of dataset faster ways in video question-answering
CausalVQA: analyzes thinking about cause-and-effect, anticipation, and counterfactuals.The V-JEPA 2 code and design checkpoints are offered
for industrial and research use, with Meta aiming to encourage more comprehensive exploration of world designs in robotics and embodied
AI.Meta signs up with other tech leaders in developing their own world designs
Google DeepMind has actually been developing its own version, Genie, which can imitate whole 3D environments
And World Labs, a startup established by Fei-Fei Li, raised $230 million to develop big world models.The post Meta V-JEPA 2 world design
uses raw video to train robots appeared first on The Robot Report.
