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用户强烈推荐Pierre Marion的文章，讨论若LLM将科研中的公式计算、写代码、检索文献等环节提速10到100倍，稀缺资源将转向选题、建模与价值判断；作者批评以论文数量和h-index为核心的评价体系正在失效，主张用AI扩展探索空间，把人类时间留给判断、品味与培养下一代研究者。
Guest post by Jeremy Avigad on Terence Tao's blog reflecting on how recent AI capabilities are disrupting mathematical research workflows, and arguing that mathematicians must adapt by pursuing harder problems and deeper understanding in the age of AI.
Mathematician Christian Szegedy publishes a reflective essay arguing that mathematics may not be ending, but rather 'graduating' into a new era shaped by AI, using analogies about exploration, competitions, and the structure of the field to frame the future of the discipline.
The essay explores how AI systems are becoming superhuman at mathematics and proposes a positive vision for adapting academic institutions to maintain human understanding and progress in mathematics.
CMU PhD student Emmy Liu reflects on the evolution of ML/NLP research, from manual work to AI-assisted to the Agent era, discussing the value of researchers in the new age.