Accenture reveals secret sauce for AI and machine learning

How do data scientists differentiate themselves in a world of rapidly advancing artificial intelligence and machine learning? This is something that hedge funds and asset management firms, which are heavily invested in new technology, think about a great deal. Separate components often referred to in order of importance are: data, algorithms and hardware. But while these are crucial, the secret sauce (a fitting epithet in this case) is often how these ingredients are combined. It’s well documented that data-hungry buyside firms scour land, sea and space looking for data sets that their peers haven’t encountered yet. Meanwhile, Google’s Tensor Processing Unit (TPU) and other application specific processers for machine learning are in a hardware arms race. Add to this the vibrant big data open source community, which has even been driven by hedge funds like AQR and Man AHL. “The question is what will become a commodity and what will differentiate,” said Sharad Sachdev, managing director, Accenture, Artificial Intelligence and Analytics. “If everyone can afford the same hardware, is it the algorithm or the data – and to what extent does data also become a commodity? I think it’s a trick question. All of these are important, but it’s more…


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