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280 | François Chollet on Deep Learning and the Meaning of Intelligence
Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas
Evolve to Innovate
The process of using genetic algorithms begins with defining a genome and a fitness function to evaluate its quality. By generating a population of genomes, applying the fitness function, and selecting the best performers, one can create new generations through mechanisms like random mutations or crossover techniques. This iterative approach enables the exploration of a vast search space, potentially leading to innovative solutions. Unlike traditional methods, LLMs primarily interpolate rather than search, which can create challenges for novelty in their findings, underscoring the importance of understanding these dynamics in the context of creative design.
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