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This editorial examines the nature of scientific discovery by studying the characteristics, methods, and tools that have historically defined a 'successful scientist'. It first considers the traditional hypothesis-driven model of science founded on existing knowledge, testable hypotheses, and experiments based on precise measurements. Through illustrative examples, it distinguishes three types of highly successful scientific contributors: those who formulated novel hypotheses and theories that proved groundbreaking, those who developed transformative measurement tools that enabled experimental testing, and those who managed to do both, even in multiple scientific fields. While success has historically depended on access to knowledge, exceptional creativity, perseverance, and experimental rigor, this editorial reminds that serendipity and timing have also played important roles. It also points to the limits of science when hypotheses remain untestable and theories unfalsifiable. It then reviews modern developments that challenge traditional approaches, such as genome-wide association studies (GWAS), where clear and specific hypotheses are no longer a prerequisite for important novel discoveries, and where discovery can emerge from data mining, rather than from pre-existing knowledge and creative hypothesis. The editorial then progresses onto the emergence of machine-led scientific discovery, using the example of the DeepMind team's development of AlphaFold - an artificial intelligence (AI) system that accurately predicted protein folding without relying on traditional hypotheses. AlphaFold learned directly from data and revolutionised the entire field of structural biology, bringing a new era of machine-inferred and AI-based science. The described frameworks are then used to analyse the development of an emerging field of science, 'ideometrics', based on the theory of the brain's 'sense of ideas', explaining how it could potentially contribute to understanding the purpose of consciousness as a complex trait in evolutionary terms. Being conscious provides an advantage by enabling the brain's 'sense of ideas' to reduce informational entropy of all possible future states of a conscious being to a narrower range of the outcomes that are perceived as more favourable for its survival. Perception of time and space in humans is, therefore, intertwined with their conscious 'sense of ideas', both while awake and dreaming, and further research in neuroscience will be required to elucidate these relationships. In conclusion, the editorial offers a comprehensive reflection on how the definition of a 'successful scientist' is being substantially reshaped in the 21st century.