The AI Simulation Lab
Forget it Let’s look at a real conversation between a user and an agent [1], in which the user is asking for help managing their e-sim, and the agent struggles to help the user. The agent suggests a
Controllability vs. Realism in User Simulation Everyone building user simulators wants two things at once: a stand-in that does exactly what it’s told, and one that behaves like a real human - who
or ensuring that your hillclimbing budget is spent right :) tldr; based on my current understanding of evaluations, RL environments, and the hill-climbing loop: an environment (or evaluation) is fair
More data won't fix the AI verification problem. Different taste might. The man who passed every check Kim Philby, standing in his mother’s flat in Drayton Gardens, London, before an array of
Nuclear physics solved for k_eff. What's the AGI equivalent? The race to AGI isn’t being won by whoever has the most compute or the cleverest architecture. It’s being won by whoever solves a quieter,
tl;dr: We find that frontier AI agents struggle on the YC Bench compared to other time-simulated benchmarks, such as the Vending Bench 2, highlighting capability gaps in planning and resource
