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The emergence of large language models (LLMs) has catalyzed a profound re-examination of the fundamental processes of scientific inquiry and knowledge creation. The proposition that these systems, despite being predictive models trained on existing data, can contribute to the furtherance of human knowledge challenges traditional conceptions of research. To address this, it is necessary to first establish a robust philosophical framework, deconstructing the core concepts of "research" and "new knowledge." This examination reveals that knowledge creation is not a monolithic process limited to novel empirical discovery but also encompasses the synthesis of existing information—a process that artificial intelligence is poised to revolutionise on an unprecedented scale.