A playable toy model of frontier AI lab capex decisions
I made a lightweight web game about compute CAPEX tradeoffs: https://darios-dilemma.up.railway.app/ No signup, runs on mobile/desktop. Loop per round: 1. choose compute capacity 2. forecast demand 3. allocate capacity between training and inference 4. random demand shock resolves outcome You can end profitable, cash constrained, or bankrupt depending on allocation + forecast error. Goal was to make the decision surface intuitive in 2–3 minutes per run. It’s a toy model and deliberately omits many real world factors. Note: this is based on what I learned after listening to…
A playable toy model of frontier AI lab capex decisions launched on February 14, 2026 with 8 votes, #1,230 of 16,627 launches that month and more than 75% of that year's launches.
What it does
You are Dario. Allocate compute, forecast demand, survive volatility.
In the maker’s words, at launch
I made a lightweight web game about compute CAPEX tradeoffs: https://darios-dilemma.up.railway.app/ No signup, runs on mobile/desktop. Loop per round: 1. choose compute capacity 2. forecast demand 3. allocate capacity between training and inference 4. random demand shock resolves outcome You can…
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FabraixMay 2026 · fabraix.com · ▲196We built Adversarial Cost to Exploit (ACE), a benchmark that measures the token expenditure an autonomous adversary must invest to breach an LLM agent. Instead of binary pass/fail, ACE quantifies adversarial effort in dollars, enabling game-theoretic analysis of when an attack is economically rational. We tested six budget-tier models (Gemini Flash-Lite, DeepSeek v3.2, Mistral Small 4, Grok 4.1 Fast, GPT-5.4 Nano, Claude Haiku 4.5) with identical agent configs and an autonomous red-teaming attacker. Haiku 4.5 was an order of magnitude harder to break than every other model; $10.21 mean…
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