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These Researchers Made AI Drive a Toyota Corolla to Get In-N-Out
AI InsightThree engineers deployed GPT, Claude, and Grok to control a real Toyota Corolla, with only one model successfully completing the task of getting food. This experiment shows that off-the-shelf LLMs exhibit divergence in real-world physical interaction, and their practical boundaries require observation of their actual application architectures.Key TakeawayTesting three mainstream LLMs in real vehicle control shows significant performance divergence, with only one model successfully completing the task.Why It MattersEvaluating general-purpose LLMs in real-world physical control provides a concrete case reference for understanding initial practices of model-physical world interaction.Who's Affected- WatchingAutonomous Driving DevelopersSuch on-car tests reflect the initial performance and divergence of different LLMs in physical-world task execution.
What's NextSubsequent focus can be directed toward more public details regarding the specific model that succeeded in the experiment and its underlying control methods.Importance 65/100