Why it’s time for “data-centric artificial intelligence”
Machine learning pioneer Andrew Ng argues that focusing on the quality of data fueling AI systems will help unlock its full power.
«Ng advocates for “data-centric AI,” which he describes as “the discipline of systematically engineering the data needed to build a successful AI system.”»
More from MIT Sloan School of Management
Machine learning, explained
Machine learning is a powerful form of artificial intelligence that is affecting every industry. Here’s what you need to know about its potential and limitations and how it’s being used.
«Machine learning is a subfield of artificial intelligence that gives computers the ability to learn without explicitly being programmed.»
6 steps for leading successful data science teams
To support data science teams, start by pointing them toward the right problem.
«When a model improves performance on a selected metric, it may do so at the expense of other important metrics.»
Why distributed leadership is the future of management
Managing the future of work requires a nimble mindset focusing on small, short-term wins, and a ‘cultivate and coordinate’ approach to leadership.
«distributed leadership as collaborative, autonomous practices managed by a network of formal and informal leaders across an organization.»
How Wayfair and Spotify use machine learning to engage customers
Armed with lots of data, Wayfair and Spotify use the power of machine learning to create personalized experiences for their customers.
10 smart — not soft — skills for leaders
In her new book, MIT Sloan international faculty fellow Loredana Padurean shares 10 smart skills to help leaders manage the most complex of variables: people.
«listening is an active skill because it requires full attention. This requires you to be present in the moment.”»
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