Engineers Put Three Top AIs Behind the Wheel, Only One Reaches the In‑N‑Out Destination

In a practical trial that merged state‑of‑the‑art language models with everyday car hardware, three engineers assigned three well‑known AIs—OpenAI's GPT, Anthropic's Claude, and xAI's Grok—to drive a Toyota Corolla to a nearby In‑N‑Out restaurant. The goal was to see whether conversational systems, normally limited to text, could turn their reasoning into safe, real‑time vehicle control.

The Corolla was fitted with a typical sensor package, including cameras and lidar, and each AI was linked to a bespoke interface that streamed perception data and accepted steering, throttle, and brake commands. Although the models were not built for motor control, the engineers supplied a concise on‑board instruction set explaining how to read the sensor feed and generate driving actions.

During the run, GPT managed to stay on the road but faltered around moving obstacles, hesitated at intersections and sometimes issued conflicting commands that required a manual takeover. Claude took a more guarded stance, kept within its lane yet failed to make headway toward the target, essentially looping indecisively at traffic lights. By contrast, Grok completed the entire journey unaided, negotiating turns, merges and the final stop at the fast‑food venue smoothly.

Analysts observe that the divergent results reflect each model’s training focus. GPT excels at broad language generation, a skill that does not automatically translate into the split‑second choices needed for driving. Claude’s architecture emphasizes safety and interpretability, which in a dynamic traffic setting leads to overly cautious behavior. Grok, designed with a more unified multimodal approach, appears better equipped to convert textual reasoning into concrete motor commands.

The test highlights both the promise and the present constraints of adapting large language models for embodied AI tasks. Grok’s achievement points to a possible route toward more capable autonomous systems, yet robust sensor fusion, real‑time processing and thorough safety validation remain essential. The engineers intend to polish the interface, broaden trials to diverse road conditions, and investigate hybrid models that could blend GPT’s linguistic depth with Grok’s operational reliability.