MIRI Updates
Hubinger et al.'s “Risks from Learned Optimization in Advanced Machine Learning Systems”, one of our new core resources on the alignment problem, is now available on arXiv, the AI Alignment Forum, and LessWrong. In other news, we received an Ethereum...
Evan Hubinger, Chris van Merwijk, Vladimir Mikulik, Joar Skalse, and Scott Garrabrant have a new paper out: “Risks from learned optimization in advanced machine learning systems.” The paper’s abstract: We analyze the type of learned optimization that occurs when a...
Evan Hubinger, Chris van Merwijk, Vladimir Mikulik, Joar Skalse, and Scott Garrabrant have released the first two (of five) posts on “mesa-optimization”: The goal of this sequence is to analyze the type of learned optimization that occurs when a learned...
Our primary focus at MIRI in 2018 was twofold: research—as always!—and growth. Thanks to the incredible support we received from donors the previous year, in 2018 we were able to aggressively pursue the plans detailed in our 2017 fundraiser post....
Updates A new paper from MIRI researcher Vanessa Kosoy, presented at the ICLR SafeML workshop this week: "Delegative Reinforcement Learning: Learning to Avoid Traps with a Little Help." New research posts: Learning "Known" Information When the Information is Not Actually Known; Defeating Goodhart and the...
MIRI Research Associate Vanessa Kosoy has written a new paper, “Delegative reinforcement learning: Learning to avoid traps with a little help.” Kosoy will be presenting the paper at the ICLR 2019 SafeML workshop in two weeks. The abstract reads: Most...
