Ocado actually first used TensorFlow to manage the flow of emails coming into its contact centre. Before TensorFlow the contact centre was dealing with emails on a first-in basis, with no sense of prioritisation. This would become an issue if bad weather hit and the volume of emails went up by three to four times and where issues with delivery would be much more pressing than something like website issues.
Dan Nelson, head of data at Ocado Technology told Computerworld UK: "So the business wanted to solve how to get a better grasp of what emails to deal with first, and that presented itself as a natural language problem," Nelson said. "So we wanted to intercept email as it arrived, understand the sentiment of it and also what they were talking about."
He says that the problem was too bespoke for Google's off the shelf natural language processing offering, so they turned to the TensorFlow library to solve the issue.
Ocado is a Google shop anyway, using the search giant's Big Query in the Google Cloud for much of its query and storage needs. Nelson said that deploying TensorFlow with Google certainly makes things far easier. "If we didn't use any cloud provider you would have to provision some pretty serious hardware, but they will still execute there. You don't have to use Google, but the fact that Tensor came out of there certainly helps for that process," he said.
Speaking about the tool more generally Nelson had a dose of realism to offer: "Essentially TensorFlow allows you to access through the libraries different learning models. You need to train and adapt them, but it accelerates your learning.
"TensorFlow doesn't solve the problem, but gives you the toolkit to abstract away from academics of a convolutional neural net and use one to solve your problem," he said.
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