Crene is investment thesis review infrastructure. The platform decomposes macro, labor, AI transition, and investment thesis questions into falsifiable components using four frontier AI models (Claude, GPT, Gemini, Grok). The system produces three product types: thesis maps (binary decomposition into assumptions), factors (continuous decomposition into drivers), and scenarios (hybrid decomposition into coherent pathways). Cross model disagreement is the primary signal. Calibrated against 1,161 resolved events with a Brier score of 0.114.

How does AI prediction calibration work at Crene?

Calibration applies at the consensus layer, not at the underlying model layer. Crene queries four frontier models in isolation, computes a cross model median consensus, and tracks resolution against a tiered source allowlist. Every resolved event becomes a permanent calibration point. Per tier accuracy, per model Brier scores, and per domain accuracy are computed live and published at https://crene.com/methodology.

What is a Brier score?

A Brier score is the proper scoring rule for probability forecasts on binary outcomes. It is the mean squared error between the forecast probability and the realized outcome (0 or 1). Lower scores indicate better calibration. The no skill baseline is 0.25 (always predicting 0.5); a perfect forecaster scores 0.0. Crene publishes the consensus Brier score and per model Brier scores across the resolved event corpus.

Crene serves investment teams that need a repeatable thesis review process: hedge funds, asset managers, macro PMs, CIO offices, family offices, and thematic investment teams. A team brings one thesis it is actively debating. Crene maps what the thesis depends on, where models disagree, what changed each week, and what would force a rethink. Data and API access remain available as the proof layer behind the workflow.

What is the difference between an event, a thesis map, and a factor at Crene?

Crene has four product types. Events are base binary outcomes with scalar probabilities. Thesis maps decompose binary anchor questions into child situations. Factor maps decompose continuous variables into drivers. Scenarios map long horizon investment questions into coherent pathways across live systems including Empire by Default, AI Labor Transition, European Rearmament, and India as the Third Growth Pole.

Bring your own thesis

Get this same map built on a thesis your team is debating.

Assumptions, model disagreement, and rethink triggers, updated weekly before your PM, risk, or IC discussion. Currently accepting one macro thesis and one AI-economy thesis for July.

Map one thesis

Back to thesis map Part ofWill AI generated content exceed human generated content on the US internet before 2030?

Event · VISUAL, VIDEO & ENTERTAINMENT

Will a fully AI generated film gross over $50M at the US box office by 2030?

Resolves Dec 31, 2030

Probability

48%

4-model average

Confidence

LOW

building category history

Stability

—

Models

Diverging

50pt spread

Current read

Consensus sits at 48% across the four models and is — (loading). Models are diverging at a 50pt spread, so the average conceals live disagreement worth inspecting below. Category confidence is LOW (building category history).

Confidence reflects category-level track record. Stability tracks estimate movement. Models shows whether the four agree.

Belief trajectory

Loading belief trajectory...

Per-model probabilities

GPT-4o

65%+17 vs avg

The film industry has seen a significant interest in AI-generated content, with several short films and experimental projects already making waves, though mainstream success is limited. However, advancements in AI technology, alongside increasing acceptance by audiences, suggest a growing potential for a fully AI-generated film to resonate and achieve box office success. The moderate successes of films like "The AI" showcase this potential, though they have yet to meet the $50M threshold, indicating that surpassing this figure by 2030 remains plausible.

Key uncertaintyRegulatory frameworks and ethical considerations surrounding AI-generated content could either bolster support for such films or hinder their production and acceptance in the market.

Gemini

35%-13 vs avg

While AI's creative capabilities are rapidly advancing, the $50M US box office threshold is substantial for a film that may struggle with audience reception and originality compared to human-directed content. Current box office trends show strong performance for established franchises and star power, which an AI-generated film would likely lack initially, suggesting a long path to such a financial success.

Key uncertaintyThe speed of advancement in AI's ability to generate compelling narratives and emotional resonance that consistently captivates broad audiences.

Claude

22%-26 vs avg

AI-generated films face significant structural barriers to $50M+ box office success by 2030. Currently, no fully AI-generated feature film has achieved theatrical release or meaningful box office performance; the highest-profile AI film projects (like those from Runway or similar studios) remain in development or went direct-to-streaming. Historical precedent shows niche/experimental films rarely breach $50M domestically—even well-funded indie films typically max out at $20-30M unless they achieve mainstream cultural penetration. The 6-year timeline is tight given that AI filmmaking technology, regulatory frameworks for IP/labor, and consumer acceptance of fully synthetic content remain nascent. However, exponential improvements in AI video generation, potential cost advantages enabling wide theatrical distribution, and the possibility of a breakout novelty success preventing zero probability justify a low-double-digit estimate rather than single digits.

Key uncertaintyWhether consumer appetite for fully AI-generated films will develop sufficient cultural legitimacy by 2030 to drive mainstream box office returns, versus remaining a niche technical curiosity—this depends heavily on early critical reception and word-of-mouth quality metrics that are currently unmeasurable.

Grok

72%+24 vs avg

The 2023-2024 success of AI-assisted VFX pipelines at $150-400M budgets (e.g., The Creator's $80M cost with 90% AI backgrounds) shows studios can already cut live-action spend by 25-40%, and Weta/ILM 2025 roadmaps target full character animation by 2027; if a mid-budget genre title ($40-60M production) releases in 2028-2029 with 60%+ AI-generated footage, domestic marketing of $30-40M plus established distribution yields a 2.5-3x domestic multiple that clears $50M. Precedents like 2019's The Irishman ($160M budget) and 2022's Avatar re-release show genre titles with novel tech routinely open above $30M domestic.

Key uncertaintyUnion-mandated work rules or SAG-AFTRA/AICP strike language that could block wide release of fully AI-generated content before 2030.

Key disagreementGrok (72%) vs Claude (22%): Different weighting of factors

CRENE-AICD-VV02Generated Jul 3, 2026