{
 "id": "iss-ml-benchmark",
 "entry": null,
 "name": "Neural networks benchmarked on phone-class chips aboard the International Space Station",
 "group": "ran",
 "class": "perception",
 "location": "space station",
 "operator": "Hewlett Packard Enterprise (the host computer)",
 "developer": "NASA Jet Propulsion Laboratory, with Ubotica",
 "host": "HPE Spaceborne Computer-2, International Space Station",
 "catalogue": null,
 "dates": {
  "launched": null,
  "ran": "by 2022",
  "reported": "2022",
  "ended": null
 },
 "hardware": "Qualcomm Snapdragon 855 and Intel Movidius Myriad X, hosted by HPE Spaceborne Computer-2",
 "software": "Deep learning models for Mars rover imagery, spectral unmixing and ship detection, by the paper's title",
 "did": "Ran deep learning inference on two commercial processors aboard the station, to measure how they perform there.",
 "marks": [
  {
   "stage": "R",
   "evidence": 2,
   "basis": [
    "c1"
   ]
  }
 ],
 "claims": [
  {
   "id": "c1",
   "kind": "quote",
   "text": "We benchmark deep learning inference on Movidius Myriad X and Snapdragon processors onboard the ISS.",
   "speaker": "Dunkel et al., JPL and Ubotica, the experiment's team",
   "relation": "experimenter",
   "source": "jpl-iss-benchmark-paper",
   "url": "https://ai.jpl.nasa.gov/public/documents/papers/Dunkel-DL-ISS-ASTRA-2022.pdf",
   "source_title": "Testing Mars Rover, Spectral Unmixing, and Ship Detection Neural Networks, and Memory Checkers on Embedded Systems Onboard the ISS",
   "publisher": "Dunkel and co-authors, JPL and Ubotica (the experiment's team)",
   "source_kind": "paper",
   "published": "2022",
   "published_basis": "year in the file's address; no date read in the text",
   "accessed": "2026-10-04",
   "copy_route": "direct",
   "read": "in part: four sentences of 34,900 characters"
  },
  {
   "id": "c2",
   "kind": "quote",
   "text": "The Snapdragon 855 and Movidius are onboard the International Space Station supported by the Spaceborne Computing-2 by Hewlett Packard Enterprise.",
   "speaker": "JPL Artificial Intelligence Group",
   "relation": "developer",
   "source": "jpl-iss-benchmark",
   "url": "https://ai.jpl.nasa.gov/public/projects/iss/",
   "source_title": "Artificial Intelligence and Advanced Flight Computing on the International Space Station",
   "publisher": "JPL Artificial Intelligence Group",
   "source_kind": "project-page",
   "published": "undated",
   "published_basis": "no date on the page",
   "accessed": "2026-10-04",
   "copy_route": "direct",
   "read": "in part: four sentences of 4,100 characters"
  },
  {
   "id": "c3",
   "kind": "quote",
   "text": "We benchmark a suite of flight software (FSW) applications on the Qualcomm Snapdragon 855 handheld Development Kit (HDK), a high performance embedded processor used in mobile phones.",
   "speaker": "JPL Artificial Intelligence Group",
   "relation": "developer",
   "source": "jpl-iss-benchmark",
   "url": "https://ai.jpl.nasa.gov/public/projects/iss/",
   "source_title": "Artificial Intelligence and Advanced Flight Computing on the International Space Station",
   "publisher": "JPL Artificial Intelligence Group",
   "source_kind": "project-page",
   "published": "undated",
   "published_basis": "no date on the page",
   "accessed": "2026-10-04",
   "copy_route": "direct",
   "read": "in part: four sentences of 4,100 characters"
  }
 ],
 "conflicts": [],
 "notes": "The models were trained on the ground and their inputs were prepared in advance; this is a test of processors, not of a model at work. The release about Dynamic Targeting says the same team ran similar algorithms on the station in 2022, which this appears to be.",
 "changed": "Added on 4 October 2026, in the second round of reading.",
 "headline": "R2"
}