{
  "id": 7924117,
  "title": "Double descent is the principle of least action",
  "url": "https://urgent.news/2026/09/16/double-descent-is-the-principle-of-least-action",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-16T17:17:46.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.19076v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "The test error of a model plotted against its number of parameters $d$ falls, peaks when the model can just fit the training data, and falls again, exhibiting the double descent phenomenon. We explain the phenomenon with statistical mechanics. The training trajectory of a stochastic gradient-based method is a particle wandering over the energy landscape of the training loss at an induced…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}