Thinking is expensive. That sounds obvious when the thinker is a human consultant billing by the hour. It sounds less obvious when the thinker is a large reasoning model producing long chains of thought, checking itself, trying another route, doubting the first answer, then generously spending another few thousand tokens to arrive at the same wrong place with better punctuation. ...
Image work has always had a small credibility problem: people can say where they looked, but we do not always know whether they actually looked there. The same problem shows up in multimodal AI. A model can answer a question about a chart, a photograph, a geometry diagram, or a robotic scene, then produce a neat textual chain of thought afterwards. It may sound procedural. It may mention “examining the relevant region.” It may even say “the graph shows…” with the confidence of a consultant holding a laser pointer. ...