Defining a metric for intelligence is tricky, but we need one to measure our progress and focus our research. We’re thus building a living metric which measures how well an agent can achieve its user’s intended goal in a wide range of environments.

The metric will consist of a variety of OpenAI Gym⁠(opens in a new window) environments with a unified action and observation space⁠(opens in a new window) (so a single agent can run across all of them), including games, robotics, and language-based tasks. Our implementation will evolve over time, and we’ll keep the community updated along the way.

A significant fraction of our research bandwidth is being spent on fundamental research. We’ll always be developing and testing new ideas, especially those that don’t fit neatly into our current worldview. This is important—our current ideas will not be enough to achieve our long-term goal.

We’ve also formed teams around specific projects. The intention isn’t just to solve these problems, but to develop general learning algorithms in the process. These algorithms will, in turn, help us build agents that are more capable according to our metric. These projects are: