Skip to main content

March 15, 2018

Report from the OpenAI hackathon

On March 3rd, we hosted our first hackathon with 100 members of the artificial intelligence community.

Hackathon Followup

Illustration: Ruby Chen

On March 3rd, we hosted our first hackathon(opens in a new window) with 100 members of the artificial intelligence community. We had over 500 RSVPs arrive within two days of announcing the event—if you didn’t make it this time, please RSVP again in the future!

Thank you to Cirrascale(opens in a new window) for providing GPU machines during the hackathon.

The crowd

Our applicants included high schoolers, industry practitioners, engineers for nonprofits (not just at OpenAI!), researchers at universities, and more, with interests spanning healthcare to AGI. We could only accommodate one hundred people this time so we tried to pick a balanced crowd with a wide range of backgrounds and levels of experience. In particular, we strove to achieve gender balance; many attendees told us that this kind of representation made a positive difference for their experience of the hackathon.

The talks

Two people seated in armchairs holding and talking into microphones

We kicked the day off with a series of talks on OpenAI’s mission and the technical topics that we focus on in our research. Sam Altman took questions on AGI timelines, safety issues, and the importance of avoiding AI arms races. Sam described how he personally came to focus on AI safety: he saw it as an underfunded, under-explored area with the potential to impact everyone. Josh Achiam gave an introduction to reinforcement learning, which is one of our main research areas; we’ve open-sourced the slides and sample code(opens in a new window) from his talk. Ilya Sutskever talked about self-play with RL agents; for an overview of the work covered, see our recent blog(opens in a new window) posts(opens in a new window) and code(opens in a new window) releases(opens in a new window). Alec Radford provided a tutorial and survey of the many different kinds of GANs and we’ve made the tutorial code(opens in a new window) available.

The hacking

Aerial shot of a group of people sitting around a large table, working on their laptops

After the talks wrapped up, the hacking began. Over the course of an 8-hour code sprint participants authored dozens of AI projects on topics ranging from safety to healthcare. Some of our favorites:

  • Jiale Xian, Clarence Leung, Kyle Zheng, Madeline Hawkins, and Stergios Hetelekides worked on an image classifier to identify purine-rich seafoods that gout patients should avoid.

Person looking over the shoulder of people sitting around a table with laptops

We got a lot(opens in a new window) of(opens in a new window) helpful(opens in a new window) feedback(opens in a new window) from(opens in a new window) hackathon attendees, which we’ll use to make even more interesting events in the future: stay tuned! If you’d like to work on AI as your day job, you may be interested in our Scholars(opens in a new window) or Fellows(opens in a new window) programs (you’re of course always welcome to apply full-time(opens in a new window)).