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Starting with the story of Galois group theory, the article delves into the boundaries of AI's capabilities in mathematics, distinguishing between two types of progress: "connecting lightning" (cross-domain connections) and "building mountains" (creating new frameworks). It analyzes the limitations of the RLVR training method and introduces the concept of "grindability" to explain AI's rapid advancements in mathematics and coding.
Google DeepMind researchers discuss the core differences between AI agents and large language models, their current capabilities and limitations, and the new economy and new path toward AGI that could emerge when millions of agents trade and collaborate with each other.