वीडियो पर वापस

1X

NEO is Starting to Learn on Its Own

प्लैटफ़ॉर्म
YouTube
अवधि
4:30
बोली जाने वाली भाषा
अंग्रेज़ी
व्यूज़
93.8 हज़ार
औसत कट
11.80s
स्क्रीन पर चेहरा
70%
गहरे फ़्रेम
12%
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NEO is Starting to Learn on Its Own की ट्रांसक्रिप्ट

फ़िल्म के अपने ऑडियो से एक स्पीच मॉडल द्वारा लिखा गया, ब्रांड द्वारा नहीं। उस पल पर जाने के लिए किसी भी पंक्ति पर क्लिक करें।

  1. 0:16Today we're releasing the 1x world model.
  2. 0:19NIO can now turn any prompt into autonomous action.
  3. 0:23With the latest update to the 1x world model, NIO learns from internet-scale data
  4. 0:27and applies it to the real world.
  5. 0:29By visualizing future actions with a video model grounded in physics,
  6. 0:34Neo can generalize to new tasks it's never seen before.
  7. 0:37This opens a new path for robotics learning,
  8. 0:41one where robots learn by teaching themselves,
  9. 0:43using the data they generated on their own,
  10. 0:45and grow in AI capabilities alongside the rapidly improving video modes.
  11. 0:55Our world model is pre-trained on web-scale video data that captures human interaction,
  12. 1:01and then post-trained on robot data to ground that understanding in real-world physics
  13. 1:06and Neo's humanoid embodiment. This allows Neo to visualize future actions and use a built-in
  14. 1:12inverse dynamics model to turn those visualizations into movement. Today, we'll use the world model
  15. 1:19as Neo's cognitive core to execute autonomous action sequences several
  16. 1:23seconds long. How it works is you'll give Neo a prompt with voice or text. For this
  17. 1:29example I'll use the world model desktop interface to illustrate how it comes
  18. 1:33together and start with something simple like having Neo pack this orange into
  19. 1:38the lunchbox.
  20. 1:45Once you prompt Neo, it'll take what it sees as input to generate a visualization of how
  21. 1:50to complete the request.
  22. 1:51As you can see on the screen below, Neo is visualizing how to perform this task using
  23. 1:56its world model.
  24. 1:58You can either have Neo automatically execute the generation or choose the best one to run
  25. 2:03from among several parallel generations.
  26. 2:10While NEO has never seen these objects before, there are still some examples of pick and
  27. 2:15place tasks in our dataset.
  28. 2:17So one might assume it's generalizing to a similar task to create this visualization.
  29. 2:23But this is not the case.
  30. 2:25With the world model, NEO can perform any task with any object, whether there is existing
  31. 2:30data or not.
  32. 2:34Not only has NEO never seen his toilet, but it has never performed a task anywhere near similar.
  33. 2:40Without any prior data on how to operate a toilet seat, the transfer of human knowledge
  34. 2:45becomes a lot more apparent. The world model is also really useful for handling unpredictable
  35. 2:56environments. Traditional AI models for robots are often overly sensitive to the
  36. 3:02surroundings, like changes in lighting or even random objects in the environment.
  37. 3:07NEO's world model, by contrast, applies human knowledge of how to navigate highly
  38. 3:13dynamic settings to handle even the most extreme changes in environment.
  39. 3:24Given a world model can generate just about anything you can imagine, there is no limit
  40. 3:30to a NEO can try and execute autonomously.
  41. 3:58We still have work to do to increase the length and success rate of each generated ability
  42. 4:05to make the world model more useful.
  43. 4:07But with the world model, NEO can create unlimited data of itself doing real-world tasks, creating
  44. 4:13a flywheel that enables NEO to teach itself anything, marking a true paradigm shift in
  45. 4:20AI and robotics.
45 पंक्तियाँ · 504 शब्द

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