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title: Vision AI in 2025 — Peter Robicheaux, Roboflow | daily.dev
description: Computer vision models significantly lag behind language models in intelligence and capability. Current vision evaluations like ImageNet and COCO are saturated...
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og:description: Computer vision models significantly lag behind language models in intelligence and capability. Current vision evaluations like ImageNet and COCO are saturated...
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# Vision AI in 2025 — Peter Robicheaux, Roboflow

**[AI Engineer](https://daily.dev/sources/aidotengineer)** · 17 min read · 1 upvotes · 0 comments

## Summary

Computer vision models significantly lag behind language models in intelligence and capability. Current vision evaluations like ImageNet and COCO are saturated and don't require true visual intelligence. Vision-language models struggle with basic visual tasks like reading analog clocks or determining object orientation. The gap exists because vision models don't effectively leverage large-scale pre-training like language models do. Roboflow introduces RF-DETR, which uses DINOv2 pre-trained backbones for real-time object detection, and RF100VL, a new benchmark dataset with 100 diverse object detection tasks to better measure visual model intelligence across different domains and imaging modalities.

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#computer-vision](https://daily.dev/tags/computer-vision), [#transformers](https://daily.dev/tags/transformers), [#object-detection](https://daily.dev/tags/object-detection)

[View this post on daily.dev](https://daily.dev/posts/vision-ai-in-2025-peter-robicheaux-roboflow-k3dyzqmb4)

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