John Salvatier
I'm a researcher at AI Impacts. I find data to improve our understanding of the likely long run impacts of powerful machine intelligence.
I think humanity's long run future is overwhelmingly important, and mostly ignored. Humanity is not very good at prioritizing the most important problems.
Because of that, I care a lot about rationality and improving humanity's ability to recognize and strategically deal with big important problems, like death, suffering, and existential risk.My work
- Blog - models of emotion and other tools of applied rationality.
- PyMC3 - simple, efficient and robust Bayesian inference for complex models.
- Seattle EA - the Effective Altruism and rationality community in Seattle I built.
Selected publications
Owain Evans, Andreas Stuhlmüller, John Salvatier, and Daniel Filan. Modeling Agents with Probabilistic Programs. http://agentmodels.org.
Abel D, Salvatier J., Stuhlmüller A., Evans O. (2016) Agent-Agnostic Human-in-the-Loop Reinforcement Learning. Future of Interactive Learning Machines Workshop at NIPS 2016
Kreuger D., Leike J., Evans O., Salvatier J. (2016) Active Reinforcement Learning: Observing Rewards at a Cost. Future of Interactive Learning Machines Workshop at NIPS 2016
Salvatier J., Wiecki TV., Fonnesbeck C. (2016) Probabilistic programming in Python using PyMC3. PeerJ Computer Science 2:e55
