According to the amateur online-business advisers of YouTube, the age of easily accessible AI is the age of asking and receiving. ChatGPT and other AI tools are ascendant in popular culture, as is the idea that you can ask them for anything. You can even ask them to make you rich. Joshua Mayo, a YouTube personality who makes videos about work-from-home "side hustles" and methods for becoming a millionaire before age 30, told me recently that his audience of mostly young people doesn't want to work a standard 9-to-5 job for several decades and then retire off of their 401(k). "A lot of them don't find that appealing," he said.

In this work, we propose a goal-driven collaborative task that contains language, vision, and action in a virtual environment as its core components. Specifically, we develop a Collaborative image-Drawing game between two agents, called CoDraw. Our game is grounded in a virtual world that contains movable clip art objects. The game involves two players: a Teller and a Drawer. The Teller sees an abstract scene containing multiple clip art pieces in a semantically meaningful configuration, while the Drawer tries to reconstruct the scene on an empty canvas using available clip art pieces. The two players communicate via two-way communication using natural language. We collect the CoDraw dataset of ~10K dialogs consisting of ~138K messages exchanged between human agents. We define protocols and metrics to evaluate the effectiveness of learned agents on this testbed, highlighting the need for a novel crosstalk condition which pairs agents trained independently on disjoint subsets of the training data for evaluation. We present models for our task, including simple but effective nearest-neighbor techniques and neural network approaches trained using a combination of imitation learning and goal-driven training. All models are benchmarked using both fully automated evaluation and by playing the game with live human agents.

Will artificial intelligence bring the age of artists to an abrupt end one day? Will machines really take over? Probably not any time soon, but the latest experiment from Google is a potent reminder that there's still much potential to tap in AI. Today, we can pose as skilled artists thanks to machine learning. AutoDraw is a new website from Google that turns your amateurish doodles into recognizable clip art.

The thing about AutoDraw is that it isn't just saying, Oh, I see you've drawn a zebra, but also suggesting, And here's what that should look like, actually. This can be quite helpful if you're just a person trying to find some quick clip art. But it's also a way of erasing the lovely and nuanced evidence of how differently people see and interpret the world around them. AutoDraw is based on an earlier Google experiment, Quick Draw, which turned the training of its neural network into a simple and pleasing sketching game. Quick Draw is a little like playing Pictionary with a computer as your teammate.