# Algorithmic Improvement Without Data Scaling **Entity class:** AI progress mechanism **Domain:** Artificial intelligence / Model training **Maturity:** Developed ## Definition Algorithmic improvement without data scaling increases capability or efficiency through architecture, optimization, scheduling, representation, or systems design while holding the training-data scale roughly fixed. ## Mechanism and significance Speedrun benchmarks make this form of progress visible by rewarding better use of a constrained computational and data budget. ## Relationships - **Research dossier:** [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] - **Ontology route:** [[ASI and RSI Timeline Ontology#Model Architecture and Compute Economics|Model Architecture and Compute Economics]] - **Primary fields:** [[Machine Intelligence]] · [[AI Infrastructure]] · [[Compute Race]] - **Adjacent concepts:** [[nanochat]] · [[NanoGPT Speedrun]] · [[Compact Reasoning Kernel]] · [[Externalized Model Knowledge]] ## Sources and provenance - [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] — immediate source for this node's role in the broadcast research map. ## Evidence boundary The research dossier establishes why this entity or concept belongs in the Moonshots ontology. Time-sensitive organizational, product, policy, and performance claims should be checked against the linked primary source or a current authoritative source before reuse as settled fact.