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First, let’s gain some perspective.
A recent paper by Harvard and University of Chicago economists compare AI to steam which enabled the Industrial Revolution.
Where and Why is this happening? Perhaps you are unaware but AI is already a vibrant element of our economy. Since 1982 Optical Character Recognition has read mailing address labels. We have all at least experimented with Siri. Call centers are rapidly being transformed from humans to Speech Recognition and response with ‘chat boxes’ powered by Natural Language Processing.
There has been a steady progression of AI exceeding human performance. This includes chess, go, spam detection, image recognition, and sentiment analysis.
We will discuss image recognition in a future blog. Well, what about language translation. Machines are capable, but below human performance for the reasons developed below.
That brings us to our challenge, Story Generation. This is a hard problem! Why, because a story is composed from, hopefully, a plot, characters, changing moods, and narrative development {long term dependencies across the pages). Each of these is a challenge for current AI algorithms.
I will elaborate on these challenges by reading some beautifully crafted works and later through a workbook insert with examples and drawings. One demonstration of our minds scope: On the narrative, how soon can you identify the works I am reading? Even if you fail to recall the piece you probably can place a period and genre.
How can you contribute? There are many ways.
Develop your unique ideas by contributing a blog. To do this simply send a comment with your name and email address and we will grant you author status to a blog.
Contribute plot, characters, and stories which will be used to generate future stories.
Perhaps you are a Data Scientist, or a class doing a Data Science project. Excellent! I can share the github repository for your contributions.