Machine Learning Storytelling

Deep learning is a novel approach to teaching machines by experience, rather than through direct programming. Three years ago Ryan Kiros from the University of Toronto published an open-source project on GitHub called a neural storyteller. The neural network was trained on a bunch of romance novels to deliver somewhat tongue-in-cheek descriptions for images. The algorithm’s artistic abilities may seem modest but it’s important to remember how complex human speech can be for machines. It’s logical to wonder if AI can become an augmented breed of a storytelling animal.

Researchers from Facebook have taught a neural network to write stories. The team sourced over 300,000 human written stories from Reddit and fed that data as a ‘summer reading’ The algorithm, after learning what and how others wrote, was tasked with creating a multi-stage story that would be relevant to a particular writing prompt. After applying several different approaches to teaching the network the basics of writing and helping it optimize the output, the team received over one hundred short stories drafted by AI.

A recent joint project by McKinsey and MIT Media Lab explored how AI can be deployed to identify the key emotional arcs in video stories. While the developed algorithm cannot create stories of its own, it can zero in on how creators can ramp up their stories, amend dialogues, dial up on plot twists or just add a dramatic tune at a crucial moment. Such AI advisory can steer us towards telling better stories that prove certain actions, rather than fly under the viewer’s radar.

Story_auto1

Neural storytelling: how AI is attempting content creation

Github