OpenAI kicked off this week with a major announcement: the launch of Universe, a software platform for "measuring and training an AI's general intelligence across the world's supply of games, websites and other applications." For those unfamiliar, OpenAI is Elon Musk's $1B brainchild devoted to being the first organization to develop human-level AI. It kicked off pretty quietly toward the end of last year and slowly brought on partners, interns, and advisers throughout most of the beginning of 2016. But it has quickly warmed up with the launch of its first platform, Gym, and now Universe.

Universe is unlike many of the developments that we've come to expect from other top AI innovation corporations like Google's DeepMind: it's actually not AI at all. Instead, it looks as if OpenAI has dedicated its first year of existence to laying the ground work for future innovation. Universe is a huge step in that direction.

What is it?

If you're interested, you should definitely check out OpenAI's full announcement of the Universe platform. It's pretty approachable, even for those new to the space. In short: Universe is a platform that AI developers can use to train and test reinforcement learning deep learning algorithms. Without getting too technical, deep learning is the technology that has led to the resurgence of AI in the past few years and reinforcement learning is a way of training deep learning models in complex environments. You could argue that the root of human intelligence is nothing more than a complex biological implementation of reinforcement learning and deep learning.

Specifically, Universe has hooked up to a variety of online environments for AI training. Mostly flash games and basic websites (think travel booking). They're looking for online tasks that humans currently perform which could theoretically be done by AI in the short- to medium-term. Where an AI developer previously would have been required to custom develop an AI agent to interact with the game Swap The Dots, that developer can now use Universe's pre-built connections and focus on what actually matters: programming an AI to play the game well.

So...?

So what exactly is the relevance of a platform for measuring and training AI on general tasks? Well, according to one DeepMind employee:

AI’s new strategic battleground is about environments and computation, rather than static datasets

If true, that would be a tidal shift in the field. Most experts agree that differentiation in the white-hot field of AI comes from two things: 1) deep learning expertise and 2) proprietary datasets. The first point is gradually shifting due to the increasing popularity of deep learning frameworks like TensorFlow and Torch. Up until now, the value of unique datasets had been unquestioned. But in a world where everyone is developing general AIs in publicly available training environments? That's a different paradigm.

Just to be clear, I'm not fully on board the paradigm-shift train yet. The value of proprietary datasets often refers to enterprise data, a space that Universe doesn't appear to be close to dominating: I didn't see any mention of an enterprise data environment being integrated at launch. And while this form of environment and reinforcement learning agent is powerful for things like playing games and performing basic tasks, my understanding is that it is not the ideal method for tackling problems like Natural Language Understanding (NLU) or the broader set of generative AI problems (e.g., making a picture from scratch), both of which are core to the broader effort to create human-level AI.

Either way, it's exciting to see OpenAI progressing toward its goal to "solve" the general AI problem. It has brought many of the most talented AI researchers and engineers in the world to bear on the problem and has released some really neat projects in its first year. As it gets more of its pieces set, I'm looking forward to seeing the steps it takes toward pushing AI research more directly.

If you want to chat AI in more detail, have any questions, or want to argue with me, hit me up on Twitter.