Computers are uniquely qualified to handle massive data sets since they can simultaneously keep track of all the important conditions necessary for the analysis. Though they could reflect human errors they’re programmed with, computers can deal with large amounts of data efficiently and they aren’t biased toward the familiar, as human investigators might be. Computers can also be taught to look for specific patterns in experimental data sets – a concept termed machine learning, first proposed in the 1950s, most notably by mathematician Alan Turing. An algorithm that has learned the patterns from data sets can then be asked to make predictions based on new data it’s never encountered before. Machine learning has revolutionized biological research since we can now utilize big data sets and ask computers to help understand the underlying biology.
Director at Learning Change Project – Research on society, culture, art, neuroscience, cognition, critical thinking, intelligence, creativity, autopoiesis, self-organization, rhizomes, complexity, systems, networks, leadership, sustainability, thinkers, futures ++
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