The Next Evolution of AI Is Learning From Your Dodgy Gaming Skills
Researchers are exploring the use of video game data to train 'world models' that help AI understand physical cause and consequence. By leveraging the vast, diverse environments found in games, startups like Worldmodeldata aim to overcome the limitations of LLMs that are trained only on text.
Why it matters
This approach could bridge the gap between digital intelligence and physical-world tasks like robotics and autonomous navigation.
There is a growing belief in corners of the AI industry that large language models will ultimately be limited by their inability to navigate the physical world. Trained only on words, LLMs are perhaps ill-equipped to pilot autonomous vehicles, steer robotic arms, or perform any other action that requires finesse and precision. To remedy that shortcoming, a crop of celebrated researchers including Fei-Fei Li and Yann LeCun are focusing their efforts on a different class of AI: world models.
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