Recently, the field of artificial intelligence has witnessed a remarkable new breakthrough. Claude, an unreleased research version developed by Anthropic, attempted to challenge one of the highest peaks in the mathematical world, the Riemann Hypothesis. Although it did not fully solve this century-old problem, it unexpectedly increased the lower bound of the proportion of zeros on the critical line of the Riemann zeta function from 41.6%, which had been maintained for decades, to 67.2% during the exploration process.

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This achievement quickly sparked heated discussions in the academic community. It should be clarified that this does not mean the Riemann Hypothesis has been proven to 67.2%. The study does not provide definitive guidance for the hypothesis itself. However, its real significance lies in the new form of scientific research demonstrated by AI. During this multi-round effort, Claude did not rely on traditional search for known answers, but instead orchestrated approximately 60 sub-Agents to form a "virtual research team," experiencing hundreds of failures, independently reviewing massive literature, and recombining classical methods. Ultimately, it explored innovative boundaries that had never been established before in the open and unknown field of mathematics.

Industry experts point out that this breakthrough not only showcases the hard-core capabilities of artificial intelligence in complex, long-range, multi-agent collaboration, and autonomous error verification, but also signals a potential revolution in future research workflows. AI may no longer be limited to solving known problems, but instead, by undertaking intensive trial-and-error processes and cross-referencing vast amounts of literature, it will significantly reduce the marginal search costs for humans in unknown fields, ushering in a new era of scientific exploration.