tl;dr: AI Safety has an extremely minor share of resources in AI, current approaches developed by labs are not satisfactory, current “safe by design” or “guaranteed safe” approaches are still in development - how satisfactory they are is still speculative at this point. Status: This is a public-facing, edited version...
tl;dr: * The virally shared figures of 10 trillion parameters and $10 billion training cost come from no identifiable source; * Cybersecurity capabilities represent a significant leap, but are in line with previous models; * Updated Responsible Scaling Policy removed threat models related to radiological and nuclear weapons with no...
TL;DR: This paper takes existing mathematical results to build the most general and rigorous case for why we should be very cautious about pushing optimization too far in General-Purpose AI systems, as it likely leads to catastrophic Goodhart failures, and ultimately loss of control. Written by Antoine Maier, AI Security...