Google DeepMind researcher @iamtrask reveals how confidential compute lets AI labs take benchmark tests they can never see: "An AI lab develops a benchmark, evaluates their own model on that benchmark, hill climbs on it, and then publishes a statement saying their model is very aligned along some dimension." "This is an old problem in machine learning. People have been hill climbing on benchmarks since the dawn of benchmarks." "One fundamentally new paradigm is double blind evaluations. An…