AI scaling laws require exponentially more compute and resources to produce only linear gains in model intelligence.

Added to korrents 20 Sept 2026 · How quotes work · Something wrong? Tell us

Shared subject first, then similar wording. They may agree or disagree.

• A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. NBNoam Brown26 Jun 2026scaling laws
• A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. DPDylan Patel13 Mar 2026scaling laws
• After pre-training, post-training and test-time scaling, the fourth scaling law is agentic: multiplying AI by spawning agents, and the whole loop scales on one thing, compute. JHJensen Huang23 Mar 2026scaling laws
• As models keep scaling up, modularity will become essential to how they are developed. SRSebastian Ruder23 Feb 2023scaling laws
• Bet on a system that is maximally learned and minimally constrained, and add structure only where it improves the scaling laws. DDDmitri Dolgov3 Aug 2026scaling laws

See this claim on the map