OCTOBER 2018CIOAPPLICATIONS.COM8Prescriptive analytics driven by natural language processing and graph architecture.Any leader following technical trends is aware that the world is abuzz with the latest wave of techno-hyperbole. Big data and prescriptive analytics are being overshadowed as artificial intelligence (AI) enters the mainstream conversation. While enthusiasm for what is next is certainly a necessary element for technology leadership, this enthusiasm could use some tempering. Or, we may experience AI's little Ice Age or (less creatively) AI Winter 2.0.This is not to say that AI technology has no merit and will not enjoy success and the value generation that comes with it. It just means that there should be a reasonable expectation in line with reality. Organizations should not expect to make short-term investments in hardware and software to deliver on the promise of AI. They should expect to make investments in people and develop new approaches to challenges in their domain over years. These new initiatives require a shift in thinking and new data models.As an example, our organization has set about machine learning from a large repository of technical documents that were written by service technicians while diagnosing issues and repairing large industrial machines. "The data was especially good by the standards of the computational linguist," notes Ryan Chandler, Senior Data Scientist at Bringing Artificial Intelligence Down to Earth MORGAN VAWTER, CHIEF ANALYTICS DIRECTOR, CATERPILLAR INCMorgan VawterIN MY VIEW
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