From the source
From the source
Google Research publishes a paper introducing the first quantitative scaling principles for AI agent systems.
The study evaluates 180 agent configurations across five architectures and finds that multi-agent coordination improves performance on parallelizable tasks but degrades it on sequential ones.
From the source
In our new paper, “Towards a Science of Scaling Agent Systems”, we challenge this assumption. Through a large-scale controlled evaluation of 180 agent configurations, we derive the first quantitative scaling principles for agent systems, revealing that the "more agents" approach often hits a ceiling, and can even degrade performance if not aligned with the specific properties of the task.
research.google