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Interactive timelines: AI compute scaling (1900–2026), tech adoption acceleration (1957–2030+), and energetic/biological efficiency parallels. Shows exponential growth, compression, and power laws.

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Interactive timelines of exponential tech progress – showing growth, compression, and scaling laws enabling modern AI.

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1. AI Compute Timeline (1900–2026)

Training FLOPs milestones for AI history – from vacuum tubes to frontier models.

AI Compute Timeline

Zoom recommended for 2010+ frontier cluster (10²⁴–10²⁷+ range).


2. Accelerating Paradigms in Computing & Connectivity (1957–2030+)

Time to ~50M users adoption – shows exponential compression from years to days.

Adoption Timeline

From ~10 years (1957) to ~60 days (2022) – a 60x+ acceleration, with AI pushing toward near-instant scaling.


3. Energetic Scaling: Biology vs. Technology

Neural efficiency vs. body size (Biology) and compute efficiency vs. time (Tech) – both reveal power laws.

Energetic Scaling

Humans are the biological outlier (EQ~7); AI is the technological outlier (75 quadrillion-fold compute/$ since 1939).


4. Scaling Civilization: Energy, Coordination, Memory, Replication

Multi-lane log-time timeline showing how four fundamental metrics have scaled from 1M years ago to 2030+.

Civilization Scaling

Log-time compresses ~99% of human existence (pre-writing) into the left side, expanding modern acceleration on the right. Phase flips (Fire → Agriculture → Writing → Printing → Internet → AI) stack to enable exponential progress.


5. Energy Leverage per Person (NEW)

How much total energy does an average human command compared to the metabolic baseline (~114 W)?

Energy Leverage

Humans went from ~1–2× body energy (foragers) to ~17× body energy (modern). The post-1750 coal/steam and post-1950 oil/electricity jumps dominate the visual story.


Why These Plots?

Timeline Shows Trend
Compute Training FLOPs (10⁰ → 10²⁷) Exponential growth
Adoption Time to 50M users Exponential compression
Energetic Neurons/kg & cps/$ Power laws (log-log linear)
Civilization Energy/Coord/Memory/Repl Stacking infrastructure layers
Energy Leverage Watts/person vs metabolic ~17× body energy (modern)

Together they illustrate:

  • Compute: Raw exponential growth enabling AI scale
  • Adoption: Ecosystem acceleration compressing timelines
  • Energetic: Fundamental scaling rules – humans and AI as outliers
  • Civilization: How infrastructure layers (fire → writing → internet → AI) enable each successive leap
  • Energy Leverage: Per-person energy command from foragers (~2×) to modern (~17×)

Inspired by Kurzweil, Epoch AI, Statista, Asymco, Herculano-Houzel (neuronal scaling), Kleiber (metabolic 0.75), Kaplan/Charnov (LHT/OFT).


Repository Structure

Each plot follows a standardized structure:

<plot-name>/
├── index.html              # Interactive page (uses shared/site.css)
├── data/
│   ├── <slug>.csv          # Source data
│   └── meta.json           # Metadata: title, description, fields, sources
├── output/
│   ├── *_interactive.html  # Plotly interactive chart
│   ├── *_highres.png       # High-res PNG export
│   └── *.svg               # SVG vector export
├── src/
│   ├── *.py                # Matplotlib static generator
│   └── *_plotly.py         # Plotly interactive generator
└── README.md

Shared Assets

  • shared/site.css – Common styles for all pages
  • shared/site.js – Navigation bar injection
  • scripts/validate_all.py – Validate all plots (run: python scripts/validate_all.py)

Development

Install dependencies

pip install -r requirements.txt

Regenerate all plots

python build_all.py

Regenerate a specific plot

cd <plot-name>/src
python <slug>.py           # Static PNG/SVG
python <slug>_plotly.py    # Interactive HTML

Validate all plots

python scripts/validate_all.py

Contributing

Ideas, new milestones, or bug reports welcome! See CONTRIBUTING.md.

License

MIT

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Interactive timelines: AI compute scaling (1900–2026), tech adoption acceleration (1957–2030+), and energetic/biological efficiency parallels. Shows exponential growth, compression, and power laws.

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