AI Forecast Time Machine
An interactive timeline that maps AI capability predictions from classic papers (Good 1965, Turing 1950, etc.) through to today's headlines, scoring each prediction against what actually happened.
AI-curious professionals, students, and policy folks who want grounded context on AI hype cycles
- Searchable archive of predictions from seminal AI papers, each tagged by author, date, and topic
- 'What actually happened' verdict on each prediction, with the gap visualized on a timeline
- Side-by-side comparison view of 1960s vs 2010s vs 2020s forecasts on the same capability
- Shareable 'prediction card' graphics for social media that contextualize the latest AI claim against history
I.J. Good's 1965 paper is being widely re-read as today's AI labs race toward 'ultraintelligent' systems — there is no good consumer-facing source that puts classic predictions in historical context.
Hacker News thread on the Good 1965 paper pulled 69 points / 32 comments — solid niche interest but not viral; searches for retrospective AI-prediction timelines return a few content pages rather than high-traffic consumer products.Hacker News discusses 1965 paper 'Speculations Concerning the First Ultraintelligent Machine' ↗AI Predictions & Adoption Timeline: What Happened, What's Coming ↗
Prediction-market platforms (Metaculus, Polymarket, Kalshi, Manifold) are forward-looking and AI forecasting tools (Digital Project Manager, CFO Club) target business finance — no interactive product scores classic AI capability predictions against historical outcomes.Metaculus vs Polymarket vs Kalshi: Which Forecasting Platform Should You Use ↗8 Best AI Forecasting Tools Reviewed in 2026 ↗
AI education market is large ($8.3B → $57B by 2033) but AI newsletter/content monetization is commoditized in 2026, and retrospective prediction-scoring is a niche intellectual curiosity play with unclear paid demand — no established WTP signal.AI Newsletter Revenue Calculator — Subscribers × Monetization ↗AI In Education Market Size, Share And Growth Report, 2033 ↗
Classic AI papers (Good 1965, Turing 1950) keep getting re-read with each hype cycle; AI capability forecasting is a permanently relevant cultural topic and the content is evergreen rather than news-cycle dependent.History of Information – I.J. Good / singularity concept origin ↗
Mostly data curation (a few dozen well-documented predictions) plus a standard interactive timeline frontend — low technical risk, buildable solo in weeks, no AI/infra heavy lifting required.Speculations Concerning the First Ultraintelligent Machine (Good 1965) PDF ↗