{
 "id": "age-of-machines-learning-problem-robot-training-data-physical-ai/libero",
 "title": "Axis data on LIBERO-Plus",
 "subtitle": "How often a robot model completed tasks under unseen conditions, by the data it was pretrained on.",
 "note": "Success rate on LIBERO-Plus tasks run under conditions the model never saw in training. Same model, same fine-tuning, same evaluation.",
 "source": "Source: AXIS-V1 paper (Zhao et al., 2026).",
 "sources": [],
 "report": {
  "title": "Age of Machines: The Learning Problem",
  "url": "https://www.khala.io/age-of-machines-learning-problem-robot-training-data-physical-ai",
  "date_published": "2026-10-16"
 },
 "url": "https://www.khala.io/age-of-machines-learning-problem-robot-training-data-physical-ai#ix-libero-t",
 "publisher": "Khala Research",
 "cite": "Khala Research, \"Axis data on LIBERO-Plus\", in \"Age of Machines: The Learning Problem\", October 16, 2026. https://www.khala.io/age-of-machines-learning-problem-robot-training-data-physical-ai#ix-libero-t",
 "csv": "https://www.khala.io/data/age-of-machines-learning-problem-robot-training-data-physical-ai/libero.csv",
 "columns": [
  "Label",
  "Value",
  "Detail"
 ],
 "rows": [
  {
   "Label": "π0.5 baseline",
   "Value": "83.9%",
   "Detail": "no extra pretraining"
  },
  {
   "Label": "+ RoboCasa365 data",
   "Value": "57.5%",
   "Detail": "an established academic dataset"
  },
  {
   "Label": "+ Axis data",
   "Value": "88.8%",
   "Detail": "AXIS-V1, same amount of data"
  },
  {
   "Label": "0%",
   "Value": "",
   "Detail": "25% 50% 75% 100%"
  }
 ],
 "quantitative": true
}