AI Compute Timeline
Training compute from early electronic computing to frontier AI, with proxies and speculative projections labeled separately.
Manifest-driven data visualization atlas
Interactive timelines showing how compute, energy, coordination, memory, and adoption compound into civilizational acceleration.
Each chart is an audit surface: historical observations, estimates, proxies, and speculative projections are labeled so the story remains readable without hiding uncertainty.
Log scales turn multiplicative change into visible slopes. Circle markers indicate observed or estimated history; alternate markers and badges identify proxies, forecasts, and source-review needs. Use the interactive links for hover text and the data links to inspect source fields directly.
Training compute from early electronic computing to frontier AI, with proxies and speculative projections labeled separately.
Time-to-scale proxies across computing, connectivity, mobile, cloud, and AI paradigms.
Biology, hardware efficiency, AI training compute, and foraging energetics compared with clean source datasets.
Five civilizational lanes: energy, coordination, memory, replication, and latency over log-time.
Per-person energy command relative to the metabolic baseline, with period anchors labeled explicitly.
Language model parameter counts over time, separating disclosed counts from estimates and unreleased projections.
Benchmark progress against human baselines across knowledge, coding, software engineering, and reasoning tasks.
Training cost, FLOPs, and capability over time, showing the efficiency paradox at the frontier.
A synchronized overview of the atlas inventory using the same manifest as the homepage, README, build, and validator.
| # | Entry | Scope | Confidence |
|---|---|---|---|
| 1 | AI Compute Timeline | Training compute from early electronic computing to frontier AI, with proxies and speculative projections labeled separately. | mixed |
| 2 | Adoption Timeline | Time-to-scale proxies across computing, connectivity, mobile, cloud, and AI paradigms. | mixed |
| 3 | Energetic Scaling | Biology, hardware efficiency, AI training compute, and foraging energetics compared with clean source datasets. | mixed |
| 4 | Civilization Scaling | Five civilizational lanes: energy, coordination, memory, replication, and latency over log-time. | mixed |
| 5 | Energy Leverage | Per-person energy command relative to the metabolic baseline, with period anchors labeled explicitly. | high |
| 6 | Model Sizes | Language model parameter counts over time, separating disclosed counts from estimates and unreleased projections. | speculative |
| 7 | AI Benchmark Progress | Benchmark progress against human baselines across knowledge, coding, software engineering, and reasoning tasks. | mixed |
| 8 | Cost to Train | Training cost, FLOPs, and capability over time, showing the efficiency paradox at the frontier. | mixed |
| 9 | Unified Dashboard | A synchronized overview of the atlas inventory using the same manifest as the homepage, README, build, and validator. | mixed |