These projects investigated problems such as analyzing how GPT-2 represents grammar, measuring the interpretability of models trained on Coinrun, and predicting epileptic seizures using brain recordings. More information about the next class of Scholars and how to apply will be announced this fall.
The OpenAI Scholars program provides stipends and mentorship to individuals from underrepresented groups to study deep learning and open-source a project.
Our Scholars have demonstrated core technical skills across various expert domains and self-motivation—critical competencies for a self-directed program like this one. They each entered the field of machine learning as relative newcomers, and we hope their progress shows how accessible machine learning is.
Mentor: Christine Payne
Social links for Alethea Power
Looking for Grammar in All The Right Places
Mentor: Melanie Subbiah
Social links for Andre Carerra
Semantic Parsing English to GraphQL
Mentor: Jerry Tworek
Social links for Cathy Yeh
Long Term Credit Assignment with Temporal Reward Transport
Mentor: Karl Cobbe
Social links for Jorge Orbay
Quantifying Interpretability of Models Trained on Coinrun
Mentor: Natasha Jaques
Social links for Kamal Ndousse
Social Learning in Independent Multi-Agent Reinforcement Learning
Mentor: Johannes Otterbach
Social links for Kata Slama
Towards Epileptic Seizure Prediction with Deep Network
Mentor: Alec Radford
Social links for Pamela Mishkin
Universal Adversarial Perturbations and Language Models
Diversity is core to AI having a positive effect on the world—it’s necessary to ensure the advanced AI systems in the future are built to benefit everyone.
If you’re excited to begin your own journey into ML, check out some of our educational materials. More information about the next class of scholars and how to apply will be announced this fall. Stay tuned!
Huge thanks to Microsoft for providing Azure compute credits to scholars, to our mentors for their time and commitment, and to all the supporters that made this program possible.