YOLOE-26
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Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models
arXiv:2606.03748v1 Announce Type: new Abstract: Real-time vision demands models that are accurate, efficient, and simple to deploy across diverse hardware. The YOLO family has become widely deployed for this reason, yet most YOLO detectors still rely on non-maximum suppression at inference, carry heavy detection heads due to Distribution Focal Loss, require long training schedules, and can leave the smallest objects without positive label assignments. We present Ultralytics YOLO26, a unified...
Fine-tuning an LLM to write docs like it's 1995
Fine-tuning an LLM to write docs like it's 1995 In my predictions for 2030 I wrote that tech writers would be using specialized LLMs, running locally on powerful hardware. I see hints of this move to “local first” among engineering pundits, but we’re not there yet, in part because of how much more powerful connected frontier models are. That doesn’t mean we can’t experiment, though.