The Story of Mathematics: 5,000 Years of Human Genius

From Clay Tablets to Artificial Intelligence

A person-focused lecture on the history of mathematics, from the Ishango bone (~20,000 BCE) to Large Language Models (2026). Designed for high school senior mathematics students.

Download Slides (PDF)
Slides101 slides across 14 sections
Mathematicians84 named mathematicians with dates and contributions
Islamic Golden Age14 slides, 11 mathematicians (largest section)
Duration~90-120 minutes (splittable into 3 sessions)
Fact-check items51 items flagged for verification

Preview

Sections

  1. Opening (Slides 1-3)
  2. Pre-Classical Mathematics: Ishango, Babylon, Egypt, Maya (4-14)
  3. Greek Mathematics (15-24)
  4. Indian Mathematics (25-31)
  5. Chinese Mathematics (32-36)
  6. Islamic Golden Age (37-50) - largest section
  7. Medieval European Mathematics (51-55)
  8. Renaissance & Early Modern (56-65)
  9. Age of Analysis (66-70)
  10. 19th Century Foundations (71-78)
  11. Early 20th Century (79-83)
  12. Mid-Late 20th Century (84-91)
  13. 21st Century & AI/ML/LLMs (92-99)
  14. Closing (100-101)

Generated with Claude Code. Plan reviewed via 2-iteration RALPLAN (Planner + Critic consensus).

Companion Lecture: The Building Blocks of LLMs

From Archimedes to Attention: 2,000+ Years of Mathematics Inside Your AI

Traces every mathematical concept powering modern Large Language Models back to its historical origin. 10 building blocks, 69 mathematicians/scientists, from linear algebra to the transformer architecture.

Download LLM Slides (PDF)
Slides78 slides across 10 sections + opening/closing
Scientists69 named mathematicians and computer scientists
Duration~93 minutes (3 sessions recommended)
ClimaxSlide 73: Annotated transformer diagram -- every piece traced to history

The 10 Building Blocks

  1. Linear Algebra -- the skeleton (Grassmann, Cayley, Mikolov)
  2. Calculus & Optimization -- how it learns (Newton, Cauchy, Hinton)
  3. Probability & Statistics -- language of uncertainty (Bayes, Fisher, Boltzmann)
  4. Information Theory -- measuring meaning (Shannon, Zipf)
  5. Logic & Computation -- the substrate (Boole, Turing, GPUs)
  6. Function Approximation -- why it works (Fourier, Cybenko)
  7. The Neuron -- biology to math (McCulloch-Pitts, Rosenblatt, He)
  8. Sequence Modeling -- path to language (Markov, LSTM, attention)
  9. The Transformer -- where everything converges (Vaswani et al. 2017)
  10. Scaling to LLMs -- the final leap (GPT, Claude, 2018-2026)

Preview

Generated with Claude Code. Plan reviewed via 2-iteration RALPLAN (Planner + Critic consensus).