At Fast Forward, we do Quarterly Reports on new technologies and AI.

So what does that mean? We’ve done things such as Natural Language generation from structured data (and how to make it fast using probabilistic data structures on massively distributed systems). We’ve done image classification and automatic text summarization using Recurrent and Convolutional Neural Networks. Most recently we have done probabilistic programming (which is a new paradigm in programming languages that add bayasen primitives). For all of these things, we write in depth reports that includes interview with the people working on the technology, prototypes, and reference implementations. We take the approach that we don’t understand the space until we can code it.

So much of my role is really looking for what’s new in AI. I try to focus on what’s possible today that maybe was wasn’t possible a year ago.

The audience should be people who will take an idea and then spent the weekend hacking on it. It’s not necessarily a goal to give them what they need to build a production system, but it will be enough to give them the tools to move that way (to play).

I’ll try to touch briefly on some of the mathematical intricacies (maybe 10 seconds at a time scattered throughout the talk), so that if there are ML experts in the audience you’ll still be interested. But that’s not going to be the primary focus. The focus is to jumpstart developers with deep learning.