OpenAI Scholars 2018: Meet our Scholars

OpenAI has announced its 2018 Scholars cohort, bringing together a diverse group of individuals with backgrounds in physics, neuroscience, linguistics, and the arts to conduct research in artificial intelligence. This initiative aims to support researchers from non-traditional backgrounds to enter the field of AI research.

Research Focus Areas and Scholar Contributions

The 2018 OpenAI Scholars are pursuing research across a wide spectrum of AI applications, ranging from theoretical machine learning to creative and medical applications.

Multi-Agent Systems and Simulation

Christine Payne, a physicist and neuroscientist, is utilizing a soccer simulation to study inter-agent communication and team dynamics.

Natural Language Processing and Linguistics

Several scholars are focusing on the intersection of language and computation:

  • Dolapo Martins: Focused on building machines that learn language like human children and developing computational models to assist in the decrypting of ancient scrolls, such as the Herculaneum papyri.
  • Nadja Rhodes: A software engineer previously with Microsoft, who is researching language modeling for the purpose of creative text generation.

AI and the Arts

AI is being applied to generative art and music to explore the intersection of technology and creativity:

  • Hannah Davis: A generative musician researching "subjective data" and creating unique datasets for machine learning to score films and translate literature and emotional data into music via her program, TransProse.
  • Holly Grimm: A Navajo software developer and painter researching Reinforcement Learning (RL) to apply it to art generation. She has specifically studied improvements to Deep Q-Networks and used a Rainbow RL algorithm to train "Sonic the Hedgehog."

Engineering and Applied AI

Other scholars are focusing on the practical application of AI in business and medicine:

  • Ifu Aniemeka: A software engineer interested in machine locomotion and the medical applications of machine learning.
  • Munashe Shumba: The founder and CEO of Everyday AI, who is focusing on creating customized AI solutions for small- and medium-sized businesses and communicating deep learning techniques in non-technical language.
  • Sophia Arakelyan: A former professional ballerina and award-winning journalist who has transitioned into writing for AI startups in Silicon Valley and completing machine learning projects.

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