>Take autonomous driving for example - a driver of a car sees a person attempting to cross a street in front of them. A human can decide to slam the brake or th

>Take autonomous driving for example - a driver of a car sees a person attempting to cross a street in front of them. A human can decide to slam the brake or the gas depending on the context - is the person crossing the car some old granny on a walker or a soccer player? Or a human sees a ball being kicked into the air on the sidewalk behind some cars, with no humans visible. The human can infer "whoops, there might be children playing here, better slow down and be prepared for a child to suddenly step out onto the street from between the cars" These are just post-hoc rationalizations. No-one making those split-second decisions under those circumstances has those chains-of-thoughts. The brain doesn't 'think' that fast. >but an object detection/classification lacks that ability to even recognize the ball as being a potentially relevant piece of context. We're talking about LLMs right ? They can make these sort of inferences. https://wayve.ai/thinking/lingo-2-driving-with-language/ https://wayve.ai/thinking/lingo-2-driving-with-language/