one thing from our agent research that i can't stop thinking about:
@OpenAI's computer-use agent would sometimes click an imprecise location, fail, and then repeatedly click around the same location until it ran out of steps.
we called it "coordinate persistence."
which is a very academic way of saying:
the model had enough intelligence to operate a computer but not enough self-awareness to realize it was doing the same dumb shit over and over
i think a lot of current agent failures look like this
less “the model isn't smart enough.”
more “the system has no reliable model of whether its last action actually worked."
Running different browser agents on non-Webvoyager tasks clearly shows two things:
1) OpenAI's Operator is clearly better than the others
2) self-reported Webvoyager results don't mean anything
openai trained deep research end-to-end using reinforcement learning 🧪
if you’re building ai agents and not thinking about rl, you’re already behind.
this is how the most powerful agents will get built.
thread below 🧵👇