#47 - Catherine Olsson & Daniel Ziegler on the fast path into high-impact ML roles


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Notes

  • After dropping out of a machine learning PhD at Stanford, Daniel Ziegler needed to decide what to do next. He’d always enjoyed building stuff and wanted to shape the development of AI, so he thought a research engineering position at an org dedicated to aligning AI with human interests could be his best option.
  • Catherine Olsson, who has also worked at OpenAI, and left her computational neuroscience PhD to become a research engineer at Google Brain. She and Daniel share this piece of advice for those curious about this career path: just dive in. If you’re trying to get good at something, just start doing that thing, and figure out that way what’s necessary to be able to do it well.
  • Daniel emphasizes that the most important thing was to practice exactly those things that he knew he needed to be able to do.
  • Google brain and open AI
  • 2 parts of AI system
  • Giving correct objective
  • Optimizing for objective robustly
  • AI safety is general