A Master Coder Tries To Get AI To Write His Article- And Gives Up

I tried to teach an AI to write this article, gave up, and wrote it my damn self

- Paul Ford

What a time for artificial intelligence! Google announced a new AI-powered set of products and services at its I/O conference for developers, including one called Duplex that makes phone calls for you and sounds just like a real person, which freaked everyone right out. The Trump administration held some sort of AI summit with representatives from Amazon, Facebook, Microsoft, Nvidia, and buttermaker Land O’Lakes, presumably because the White House has so much churn. Add to this the public reveal that the musician Grimes and Elon Musk are dating, after the two shared a joke about AI.

And yet when people ask what the software company I run is doing with machine learning, I say, calmly, “Nothing.” Because at some level there’s just nothing to do.

The hotness of the moment is machine learning, a subfield of AI. In machine learning you take regular old data— pictures, emails, songs—and run it all through some specialized software. That software builds up a “model.” Since the model encodes what came before, it’s predictive—you can feed the model incomplete data and it will suggest ways to complete it. A trivial example: Anyone, including you and I, can feed the alphabet to a “recurrent neural network,” or RNN. That makes a model of the alphabet. Now you execute that model (maybe by running a script) and give it the letters “ABC.” If your specially trained neural network is having a good day, it’ll say “D.”

Go up a level: Feed your neural network a million pictures with captions, then feed it a picture without a caption and ask it to fill in the missing caption. Feed it countless emails with replies, then show it one without a reply and ask it what to say.