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Recent developments in artificial intelligence reveal its ability to solve complex mathematical problems at astonishing speed. A new model from OpenAI successfully solved 370 mathematical questions out of around 4,000 tested, covering fields such as probability and statistical physics. These results have significantly impacted the world of mathematics, notably renowned French mathematician Hugh Doumeng Coubain, a Fields Medal laureate, who declared that AI has "eliminated" his field—citing achievements that once took years to accomplish now being completed within hours. This progress raises concerns about the changing role of researchers, as the rapid generation of proofs diminishes the need for the cognitive processes that form the foundation of learning and scientific development. There is apprehension that this trend might shorten lengthy research phases and undermine the human spirit of innovation and experimentation in science. While machine-generated results still require verification for accuracy, increasing reliance on AI prompts questions about its impact on understanding mathematical knowledge and the skills of emerging researchers. There are fears that this advancement could weaken the human position as the primary source of knowledge and threaten the continued independent accumulation of scientific experience.
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