--- url: "https://predictiontoolkit.com/tools/ai-bubble-oracle/" publisher: "PredictionToolkit" dateModified: "2026-11-03" --- [← Dashboards]() Research tool # AI Bubble Oracle: inspect the assumptions behind the historical analogy AI Bubble Oracle is an experimental dashboard aligning dot-com history with AI-era indicators. A hierarchy combines valuation, concentration, capital investment, speculation and monetary context, while a separate page monitors a named Polymarket contract. [**2.5**/ 5Editorial rating]() [Editorial assessment]() [Open AI Bubble Oracle]() aibubbleoracle.com **Available on:** Web **Pricing:** The public experimental dashboard is accessible without a displayed paid plan. [Screenshots]() [Explore alternatives]() [Dashboards]() [Forecasting]() +2 more [Economic research]() [Company & earnings data]() ## Screenshots and interface Product preview1 / 1 Metric contributions and projected dates. ## What is AI Bubble Oracle? Then and Now places the eras on a normalized clock. Expand a projection to see its contributing metrics, then change anchors, smoothing, matching rules or weights. Metrics that do not fit can show no projection; those counterexamples are part of the analysis. The contract monitor is independent of the analogy and has no resolution authority. Its legend separates a current crossing, a crossing retained after recovery and a condition without an automated source. Missing automation does not mean false; read the original rules and the UMA resolution process. ### Who it is for - Technology-cycle researchers. - Users testing historical-anchor sensitivity. - Readers comparing macro context and contracts. ## Research coverage and methods - **Metric hierarchy** Expand parent and leaf contributors. - **Era alignment** Compare both eras on a shared normalized timeline. - **Starting anchors** Choose alternative starting events for either era. - **Smoothing** Compare 1-month and 3-month smoothing. - **Shape matching** Compare first-crossing and dominant-climb matching. - **Editable weights** Inspect and change parent contributions. - **Visible counterexamples** Retain no-projection series that fail the analogy. - **CSV export** Download the displayed analytical data. - **Projection drift** Sort by movement in estimated dates. - **Contract-condition monitor** The named contract uses a 3-of-6 condition rule over 90 days; the legend distinguishes present, recovered and unautomated conditions. ## Research tasks ### Inspect a headline date Expand the branches and identify the largest contributors. ### Test assumptions Change anchors, smoothing and matching and compare resulting dates. ### Read counterevidence Inspect no-projection metrics before accepting the historical analogy. ### Separate contract status Distinguish a current crossing from a retained 90-day crossing and missing automation, then read original contract rules. ## Pricing and total cost The public experimental dashboard is accessible without a displayed paid plan. ## Research inputs and access 1. Open Then and Now, expand a branch and read Options & assumptions. 2. Compare anchors and smoothing and inspect no-projection series. 3. Export the data when needed. [Read methodology and data inputs]() [Open the contract-condition monitor]() ## Useful links ### What to check - The timeline is an experimental shape comparison. - Short anchor histories can destabilize dates or exceed the display horizon. - Centered smoothing differs from real-time signal information. - A condition lacking automation must not be classified as false. - Projected dates are historical-shape analogies, not calibrated event probabilities. A closer look ## Ratings & reviews Editorial rating **2.5**/ 5 0 user reviews PredictionToolkit editorial ### Our take on AI Bubble Oracle Editable assumptions and exports expose how the analogy is constructed. The timeline remains an experimental comparison rather than a calibrated forecast. **Assessment criteria:** Task usefulness, documented scope, setup clarity, and access and cost transparency. **Assessment date:** 2026-10-05 **Documentation reviewed:** 2026-10-01 Documentation-based assessment. [How we rate]() ### User reviews 0 The main score switches to user ratings after 5 published reviews. **Be the first to share your experience** A specific example helps the next person choose the right tool. ## Related tools [Browse category]() ![Election Betting Odds probabilities and electoral map]() [Election Betting Odds]() Research tool**3.5**Editorial Election research linking cross-venue probability summaries with bid/ask ranges, past race movements and state maps. - Access Web Directly market-implied probabilities. ![ElonTracker post history and moving averages for a selected account]() ![ElonTracker logo]()[ElonTracker]() Research tool**3.0**Editorial Research posting activity and count brackets through web analytics and the linked Telegram bot. - Access Web · Telegram Also in Dashboards and Charts. ![PredictionBell trader and sports-research modes]() ![PredictionBell logo]()[PredictionBell]() Analytics**3.0**Editorial A free research screener for sports, financial and macro contracts on Polymarket and Kalshi. - Trading mode Read-only - Access Web Current macro-event contracts. ## Frequently asked questions about AI Bubble Oracle ### Why is there no projection for a metric? Its shape does not fit the chosen analogy. ### Can assumptions change? Anchors, smoothing and weights are editable. ### Is the headline a market probability? It is a model timeline conditional on assumptions. ### Does the monitor resolve the contract? No. The author points to Polymarket’s UMA process and human interpretation; this independent monitor has no authority. ### Is H100 a complete rental benchmark? Vast.ai is listed as a rental proxy, with its own coverage rather than every supplier and contract. In this profile