Summary of V-irl: Grounding Virtual Intelligence in Real Life, by Jihan Yang et al.
V-IRL: Grounding Virtual Intelligence in Real Life
by Jihan Yang, Runyu Ding, Ellis Brown, Xiaojuan Qi, Saining Xie
First submitted to arxiv on: 5 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Vision and Pattern Recognition (cs.CV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed V-IRL platform aims to bridge the realism gap between digital AI agents and the physical world by enabling them to interact with reality in a virtual yet realistic environment. This scalable platform allows for the development of agents that can accomplish practical tasks, perceive, decide, and interact with real-world data globally. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine having a super-smart robot or computer program that can do things we can’t, like see, hear, and move around our world in ways that are as natural as humans. That’s what scientists want to achieve by creating an “embodied” AI that can interact with the real world. To make this happen, they need a special kind of computer simulation called V-IRL (Virtual Interactive Real-world Learning). This platform lets agents practice and learn new skills in a virtual environment that feels like our own. |
