# Machine Learning Turns Data into New Forms of Understanding by Gary Marcus > “No, I don't literally mean that we should stop believing in, or collecting, Big Data. But we should stop pretending that Big Data is magic. There are few fields that wouldn't benefit from large, carefully collected data sets. But lots of people, even scientists, put more stock in Big Data than they really should. Sometimes it seems like half the talk about understanding science these days, from physics to neuroscience, is about Big Data, and associated tools like "dimensionality reduction", "neural networks", "machine learning algorithms" and "information visualization".” > **— Gary Marcus**, *2014, Edge Annual Question, “What Scientific Idea Is Ready For Retirement?”* ## Sources and Context - **Direct Edge response and surrounding essay:** [Big Data](https://www.edge.org/response-detail/25512) — Edge published this exact passage in its 2014 Annual Question collection, *WHAT SCIENTIFIC IDEA IS READY FOR RETIREMENT?*. The response page preserves the surrounding argument and qualifications. - **Complete local collection index:** [[research/Edge 2014 Full Quotation Curation|Edge 2014 Full Quotation Curation]] — retained source-first record for the complete response cohort and this passage's promotion status. ## Related Articles and Collections - **Collection:** [[collections/Edge|Edge]] - **Collection:** [[collections/Machine Succession|Machine Succession]] - **Article:** [[articles/Modern Artificial Intelligence in the 1970s|AI in the 1970s]] - **Article:** [[articles/Christopher Nolan's Odyssey at the Threshold of Machine Succession|Nolan's Odyssey]] - **Article:** [[articles/Cyber-Physical Lessons from Imperial Beekeeping|Cyber-Physical Beekeeping]] - **Wiki map:** [[wiki/Artificial Intelligence|Artificial Intelligence]] ## Related Topics - [[wiki/Artificial Intelligence|Artificial Intelligence]] - [[wiki/Machine Learning|Machine Learning]] - [[wiki/Infrastructural Superintelligence|Infrastructural Superintelligence]] - [[wiki/Machine Succession|Machine Succession]] ## Share on Social Media ``` “No, I don't literally mean that we should stop believing in, or collecting, Big Data. But we should stop pretending that Big Data is magic. There are few fields that wouldn't benefit from large, carefully collected data sets. But lots of people, even scientists, put more stock in Big Data than they really should. Sometimes it seems like half the talk about understanding science these days, from physics to neuroscience, is about Big Data, and associated tools like "dimensionality reduction", "neural networks", "machine learning algorithms" and "information visualization".” — Gary Marcus, 2014, Edge Annual Question, “What Scientific Idea Is Ready For Retirement?” https://bryantmcgill.com/simple-reminders-gary-marcus-machine-learning-turns-data-new ```