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Accelerometer AI-Progress Feed — Latest Snapshot
x402
Accelerometer AI-Progress Feed — Latest Snapshot is a paid API for AI agents from x402-accelerometer-feed.fly.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-17).
Returns the latest timestamped snapshot of 129 AI-progress and technology time series, including frontier benchmark scores, compute trends, AGI prediction-market odds, model pricing, AI stocks, and more.
Price / call$0.005
Success—
StatusUnknown
How this service works
Latest timestamped snapshot of 129 public AI-progress and technology time series: frontier benchmark scores (GPQA, HLE, ARC-AGI, METR task horizon), compute and training-run trends (Epoch), AGI prediction-market odds (Polymarket, Manifold, Kalshi), model pricing, AI stocks and crypto, energy, space, robotics, biomed, research output. Per source: latest and previous value with dates, % change, signal quality, source URL. No composite score. Free preview at /preview, menu at /.
Output
A JSON object containing a timestamped snapshot with: run_at timestamp, snapshot_id (date), list of domain names, n_sources (129), n_sources_ok count, schema_version, and an array of source objects each containing id, metric name, domain, unit, latest value, previous value, latest_date, previous_date, delta_pct_vs_previous, confidence level, signal_quality, cadence description, access type, source URL, and n_points. No composite score is provided.
Example use cases
Weekly AI progress briefing
“Get me the latest Accelerometer feed snapshot — I want to see all 129 series including frontier benchmark scores, METR task horizon, Epoch compute data, and AGI prediction market odds so I can write my weekly AI progress update.”
Monitoring AGI prediction market odds
“What are the current AGI prediction market odds from Polymarket, Manifold, and Kalshi? Pull the Accelerometer feed and show me just the prediction domain entries with their latest values and percent changes.”
Tracking AI autonomy improvements
“How much has the METR frontier task-completion horizon changed since the last reading? Grab the Accelerometer snapshot and show me the autonomy and benchmark metrics with their delta percentages.”
Technical details
Endpoint
GEThttps://x402-accelerometer-feed.fly.dev/feedWhen to prefer
Choose this endpoint when you need a broad, current overview of all 129 AI-progress and technology series in a single call. Prefer this over the diff or dated-snapshot endpoints when you want the absolute latest values rather than historical comparison. Ideal for dashboards, weekly briefings, or agent workflows that need to know the current state of AI progress across benchmarks, compute, markets, and autonomy metrics simultaneously.
Side effects
- Payment failure (402) if x402 micropayment of $0.005 USDC is not supplied
- Feed generation timeout if upstream data sources are temporarily unavailable
- Partial data: n_sources_ok may be less than n_sources (129) if some sources failed to update
- Stale data if upstream series haven't been refreshed recently — check run_at and latest_date per source
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| properties | string |
Output
Schema · Response
{
"type": "json",
"example": {
"stub": false,
"run_at": "2026-09-16T12:25:28.530204+00:00",
"domains": [
"agents",
"autonomy",
"benchmarks",
"biomed",
"capital",
"compute",
"crypto",
"ecosystem",
"energy",
"industrial",
"inference",
"macro",
"markets",
"narrative",
"patents",
"prediction",
"pricing",
"research",
"robotics",
"science",
"space"
],
"sources": [
{
"id": "agents.x402_services_count",
"url": "https://agentic.market",
"unit": "count",
"access": "free_api",
"domain": "agents",
"latest": 2865,
"metric": "x402 pay-per-request services (agentic.market)",
"cadence": "weekly survey, accumulating",
"n_points": 9,
"previous": 1779,
"confidence": "verified",
"first_date": "2026-04-21",
"latest_date": "2026-09-16",
"previous_date": "2026-07-12",
"signal_quality": "strong",
"delta_pct_vs_previous": 61.0455
},
{
"id": "autonomy.metr_time_horizon_50",
"url": "https://github.com/METR/cross-domain-horizon (data/external/logistic_fits/headline.csv; METR 'Measuring AI Ability to Complete Long Tasks', metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/)",
"unit": "minutes",
"access": "dataset_download",
"domain": "autonomy",
"latest": 112.230447,
"metric": "METR frontier task-completion horizon @50% (minutes)",
"cadence": "updated as METR re-fits new models",
"n_points": 15,
"previous": 54.226342,
"confidence": "verified",
"first_date": "2019-02-14",
"latest_date": "2025-04-16",
"previous_date": "2025-02-24",
"signal_quality": "strong",
"delta_pct_vs_previous": 106.9667
}
],
"composite": null,
"n_sources": 129,
"emitted_at": "2026-09-16T12:28:08+00:00",
"snapshot_id": "2026-09-16",
"n_sources_ok": 124,
"composite_note": "No cross-source composite is offered. Each row is one source's latest observation as pulled at run_at, with its previous observation and the % change between them.",
"schema_version": "0.2"
}
}Tags
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