Why Machines Still Can’t Learn So Good
- Man AHL took three years to create machine-learning strategy
- Algorithms fail at 90% rate in live tests, a quant says
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Anthony Ledford and his colleagues at Man AHL spent three painstaking years building a machine-learning model to do something mere mortals often can’t: find fresh ideas in an avalanche of data.
But even Ledford, chief scientist at the $19 billion Man AHL in London, rolls his eyes when he hears people say that machine learning, a type of artificial intelligence, is going to transform hedge funds tomorrow. To Ledford, a lot of the buzz smacks of hype. The technology is more robust than its predecessors but hardly revolutionary.