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(Facebook declined to say how many of those workers it has, or to make M available to try.) That design is too expensive to scale to the 1.2 billion people who use Facebook Messenger, so Facebook offered M to a few thousand users in 2015 as a kind of semi-public R&D project.
Entwining human workers and algorithms was intended to reveal how people would react to an omniscient virtual assistant, and to provide data that would let the algorithms learn to take over the work of their human “trainers.” “Everybody in this field is dreaming of creating the assistant that will finally be very, very, very smart,” says Alex Lebrun, who started the project. Now two years down that path, Facebook’s research project can justifiably be called successful.
Nina becomes smarter over time by learning from past and current live agent interactions, and other engagements happening in your digital channels to constantly optimize the behavior and improve the accuracy of the responses.
A virtual assistant provides the quickest way to give customers the answers they need, using natural conversation.
Facebook is taking a step toward more conversational AI with Parl AI (par-lay), its open-source research platform for chatbot developers.
The platform, unveiled Tuesday, is being promoted as the “one-stop shop for dialog research,” giving developers access to each other’s research and training simulations.
It has learned millions of new phrases and responses since its release, due to its self-learning technology.These efforts come as many businesses and users were left unenthused with overhyped chatbots on the market.