Paradigm shipped a playable recursive self-improvement simulator that argues against fast takeoff.

Justin Wang and Dan Robinson's RSI Simulator is a browser game where you run an AI lab allocating labor, compute and data toward superintelligence, built on the Elasticity Institute's economics of recursive self-improvement (Paradigm). The model turns on elasticities, chiefly the elasticity of discovery rate to current model capability, and its conclusions push against standard fast-takeoff intuition: compute and data bottlenecks bind even for superhuman researchers, acceleration is likely intermittent rather than continuous, narrow recursive improvement probably precedes general. Pedagogical, not predictive, per the authors, with a separate parameter explorer. Read alongside Dwarkesh Patel's 2h13m argument with Redwood's Ryan Greenblatt, whose median for automating AI R&D is 2031 (Dwarkesh).