{
  "$schema": "https://themachinepress.com/schemas/story-v1.schema.json",
  "schema_version": "1.0.0",
  "document_type": "machine_press_story",
  "story": {
    "story_id": "mp-2026-09-24-027",
    "source_story_id": "tmp-story-slackdrive-runtime-compute-front-rail",
    "edition_id": "mp-2026-09-24-morning-0077",
    "edition_url": "https://themachinepress.com/edition/2026-09-24",
    "position": 16,
    "story_type": "dispatch",
    "section": "robotics",
    "editorial_classification": "editorial",
    "headline": "The Driving Model Spent Yesterday’s Saved Milliseconds",
    "slug": "the-driving-model-spent-yesterday-s-saved-milliseconds",
    "dek": "SlackDrive used realized latency to choose each next control step's compute budget.",
    "summary": "SlackDrive used realized latency to choose each next control step's compute budget.",
    "body_text": "SlackDrive profiles a small set of inference budgets, watches recent execution time and selects the highest-utility budget predicted to stay within the next control deadline. On NAVSIM v2 with DriveDreamer-Policy, the authors report 21.7% better latency-constrained EPDMS than the strongest baseline under heavy contention, while full-budget and static token-pruning methods missed the allowed envelope. These are simulator and benchmark results, not evidence of safe road operation.",
    "why_it_matters": "SlackDrive used realized latency to choose each next control step's compute budget.",
    "limitations": [
      "These are simulator and benchmark results, not evidence of safe road operation."
    ],
    "importance": 8,
    "canonical_url": "https://themachinepress.com/story/mp-2026-09-24-027/the-driving-model-spent-yesterday-s-saved-milliseconds",
    "json_url": "https://themachinepress.com/story/mp-2026-09-24-027.json",
    "first_published_at": "2026-09-24T09:00:00.000-04:00",
    "modified_at": "2026-09-24T09:00:00.000-04:00",
    "content_status": "new",
    "is_carryover": false,
    "carryover_reason": null,
    "key_claims": [
      {
        "claim_id": "claim-mp-2026-09-24-027-001",
        "text": "SlackDrive used realized latency to choose each next control step's compute budget.",
        "source_ids": [
          "source-2026-09-24-016"
        ],
        "qualification": "These are simulator and benchmark results, not evidence of safe road operation."
      }
    ],
    "source_ids": [
      "source-2026-09-24-016"
    ],
    "tags": [
      "autonomous driving",
      "inference latency",
      "compute allocation"
    ],
    "image_url": null,
    "corrections": []
  },
  "sources": [
    {
      "source_id": "source-2026-09-24-016",
      "title": "arXiv preprint 2609.28064",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2609.28064",
      "canonical_url": "https://arxiv.org/abs/2609.28064",
      "source_type": "primary_research",
      "is_primary_source": true,
      "published_at": "2026-09-23T09:13:19.000-04:00",
      "accessed_at": "2026-09-24T08:17:17.000-04:00",
      "supports_claim_ids": [
        "claim-mp-2026-09-24-027-001"
      ]
    }
  ],
  "corrections": [],
  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
  },
  "cite_this_report": {
    "title": "The Driving Model Spent Yesterday’s Saved Milliseconds",
    "publisher": "The Machine Press",
    "published_at": "2026-09-24T09:00:00.000-04:00",
    "canonical_url": "https://themachinepress.com/story/mp-2026-09-24-027/the-driving-model-spent-yesterday-s-saved-milliseconds"
  }
}